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    <title>Model-Evaluation on Cognaptus</title>
    <link>https://cognaptus.com/tags/model-evaluation/</link>
    <description>Recent content in Model-Evaluation on Cognaptus</description>
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    <item>
      <title>Correct Answer, Weak Evidence: Measuring Multimodal Reasoning at the Fact Level</title>
      <link>https://cognaptus.com/blog/2026-09-13-correct-answer-weak-evidence-measuring-multimodal-reasoning-at-the-fact-level/</link>
      <pubDate>Sun, 13 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-09-13-correct-answer-weak-evidence-measuring-multimodal-reasoning-at-the-fact-level/</guid>
      <description>MuRGAt shows why multimodal model evaluation needs to measure whether cited evidence supports each factual step, separately from whether the final answer is correct.</description>
    </item>
    <item>
      <title>Correct on the Frame, Wrong on the Timeline</title>
      <link>https://cognaptus.com/blog/2026-09-13-correct-on-the-frame-wrong-on-the-timeline/</link>
      <pubDate>Sun, 13 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-09-13-correct-on-the-frame-wrong-on-the-timeline/</guid>
      <description>TimeBlind shows why high video-question accuracy can conceal weak temporal reasoning—and how teams can test that failure before deployment.</description>
    </item>
    <item>
      <title>Four Inputs In, One Modality Out: Testing Whether Omnimodal Models Actually Arbitrate Evidence</title>
      <link>https://cognaptus.com/blog/2026-09-13-four-inputs-in-one-modality-out-testing-whether-omnimodal-models-actually-arbitrate-evidence/</link>
      <pubDate>Sun, 13 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-09-13-four-inputs-in-one-modality-out-testing-whether-omnimodal-models-actually-arbitrate-evidence/</guid>
      <description>C³PO shows that multimodal reliability depends less on accepting more inputs than on keeping competing evidence active long enough to resolve conflicts correctly.</description>
    </item>
    <item>
      <title>The Wrong Answer May Start Before Reasoning</title>
      <link>https://cognaptus.com/blog/2026-09-13-the-wrong-answer-may-start-before-reasoning/</link>
      <pubDate>Sun, 13 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-09-13-the-wrong-answer-may-start-before-reasoning/</guid>
      <description>A process-level view of multimodal math shows why teams should diagnose perception, alignment, and reasoning separately—and verify more deeply only when the cost of error warrants it.</description>
    </item>
    <item>
      <title>When Vision Fails in Both Directions</title>
      <link>https://cognaptus.com/blog/2026-09-13-when-vision-fails-in-both-directions/</link>
      <pubDate>Sun, 13 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-09-13-when-vision-fails-in-both-directions/</guid>
      <description>AMVICC shows why multimodal model selection should test the specific visual constraints a workflow depends on rather than rely on a single capability score.</description>
    </item>
    <item>
      <title>Confidence Is Not a Stop Signal: Test Whether the Model Knows When Information Is Missing</title>
      <link>https://cognaptus.com/blog/2026-09-10-confidence-is-not-a-stop-signal-test-whether-the-model-knows-when-information-is-missing/</link>
      <pubDate>Thu, 10 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-09-10-confidence-is-not-a-stop-signal-test-whether-the-model-knows-when-information-is-missing/</guid>
      <description>Medical QA stress tests show why confidence, warning language, and an abstention option must be validated before they control automated routing.</description>
    </item>
    <item>
      <title>Who Sets the Score? H-Bench Reframes AI Benchmarking as a Sociotechnical System</title>
      <link>https://cognaptus.com/blog/2026-09-09-who-sets-the-score-hbench-reframes-ai-benchmarking-as-a-sociotechnical-system/</link>
      <pubDate>Wed, 09 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-09-09-who-sets-the-score-hbench-reframes-ai-benchmarking-as-a-sociotechnical-system/</guid>
      <description>H-Bench formalizes how technical metrics, stakeholder tradeoffs, and changing deployment priorities could jointly determine an AI benchmark rather than leaving its weights fixed by design.</description>
    </item>
    <item>
      <title>Synthetic Data Needs an Evidence Contract</title>
      <link>https://cognaptus.com/blog/2026-09-03-synthetic-data-needs-an-evidence-contract/</link>
      <pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-09-03-synthetic-data-needs-an-evidence-contract/</guid>
      <description>Synthetic data creates value when its generation and validation are matched to the specific claim or system it is meant to support.</description>
    </item>
    <item>
      <title>Synthetic Experience, Real Transfer: Build the Test Before You Scale the Data</title>
      <link>https://cognaptus.com/blog/2026-09-03-synthetic-experience-real-transfer-build-the-test-before-you-scale-the-data/</link>
      <pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-09-03-synthetic-experience-real-transfer-build-the-test-before-you-scale-the-data/</guid>
      <description>Two 2026 studies show why synthetic training should be designed around executable experience, verifiable learning signals, and external transfer tests rather than data volume alone.</description>
    </item>
    <item>
      <title>When the Simulator Becomes the Curriculum</title>
      <link>https://cognaptus.com/blog/2026-09-02-when-the-simulator-becomes-the-curriculum/</link>
      <pubDate>Wed, 02 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-09-02-when-the-simulator-becomes-the-curriculum/</guid>
      <description>Sim2Reason shows how a trusted physics simulator can become a renewable source of verifiable post-training data—but only when synthetic questions are designed for transfer rather than volume.</description>
    </item>
    <item>
      <title>Same Proposition, Different Stance: Grammar as a Model-Risk Variable</title>
      <link>https://cognaptus.com/blog/2026-08-20-same-proposition-different-stance-grammar-as-a-modelrisk-variable/</link>
      <pubDate>Thu, 20 Aug 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-08-20-same-proposition-different-stance-grammar-as-a-modelrisk-variable/</guid>
      <description>Controlled rewrites show that LLM judgments can move with linguistic form, making prompt structure a robustness variable rather than a cosmetic choice.</description>
    </item>
    <item>
      <title>When the Test Window Changes the Problem</title>
      <link>https://cognaptus.com/blog/2026-08-20-when-the-test-window-changes-the-problem/</link>
      <pubDate>Thu, 20 Aug 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-08-20-when-the-test-window-changes-the-problem/</guid>
      <description>A time-series model can win or lose because the evaluation window suppresses the zero-occurrence behavior that operations actually depend on.</description>
    </item>
    <item>
      <title>Vision Helps, but Context Decides: What Repair Detection Reveals About Multimodal Conversational AI</title>
      <link>https://cognaptus.com/blog/2026-08-12-vision-helps-but-context-decides-what-repair-detection-reveals-about-multimodal-conversational-ai/</link>
      <pubDate>Wed, 12 Aug 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-08-12-vision-helps-but-context-decides-what-repair-detection-reveals-about-multimodal-conversational-ai/</guid>
      <description>Visual behavior can improve detection of conversational breakdowns, but the gains depend sharply on the interaction environment, task, and signals already available.</description>
    </item>
    <item>
      <title>Common Is Not Defining: Testing Whether Language Models Understand Category Relations</title>
      <link>https://cognaptus.com/blog/2026-08-08-common-is-not-defining-testing-whether-language-models-understand-category-relations/</link>
      <pubDate>Sat, 08 Aug 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-08-08-common-is-not-defining-testing-whether-language-models-understand-category-relations/</guid>
      <description>A prevalence-controlled test shows why semantic similarity can overstate conceptual understanding—and how model-review teams can evaluate the difference.</description>
    </item>
    <item>
      <title>The Leaderboard Is Not a Clinical Clearance</title>
      <link>https://cognaptus.com/blog/2026-08-06-the-leaderboard-is-not-a-clinical-clearance/</link>
      <pubDate>Thu, 06 Aug 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-08-06-the-leaderboard-is-not-a-clinical-clearance/</guid>
      <description>ClinMM-Bench shows why healthcare teams must test diagnostic models by specialty, reasoning quality, and failure mode—not leaderboard rank alone.</description>
    </item>
    <item>
      <title>Attention Is a Connection Walk, Not Automatically a Laplacian</title>
      <link>https://cognaptus.com/blog/2026-08-04-attention-is-a-connection-walk-not-automatically-a-laplacian/</link>
      <pubDate>Tue, 04 Aug 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-08-04-attention-is-a-connection-walk-not-automatically-a-laplacian/</guid>
      <description>A precise operator view shows why attention maps capture token routing but omit the feature transformations that determine what the layer actually computes.</description>
    </item>
    <item>
      <title>One Correction, Every Case: When LLMs Actually Update the Rule</title>
      <link>https://cognaptus.com/blog/2026-07-31-one-correction-every-case-when-llms-actually-update-the-rule/</link>
      <pubDate>Fri, 31 Jul 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-07-31-one-correction-every-case-when-llms-actually-update-the-rule/</guid>
      <description>A controlled reversal-learning study shows how to distinguish genuine rule transfer from gradual case-by-case recovery in large language models.</description>
    </item>
    <item>
      <title>Average at Your Own Risk: The Metric Setting That Can Reverse the Winner</title>
      <link>https://cognaptus.com/blog/2026-07-23-average-at-your-own-risk-the-metric-setting-that-can-reverse-the-winner/</link>
      <pubDate>Thu, 23 Jul 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-07-23-average-at-your-own-risk-the-metric-setting-that-can-reverse-the-winner/</guid>
      <description>A practical guide to choosing micro, macro, weighted, and exemplar aggregation according to the operational unit a classifier must serve.</description>
    </item>
    <item>
      <title>Reconstructing the Wrong Winner: Choosing VAEs for Sign-Language Generation</title>
      <link>https://cognaptus.com/blog/2026-07-23-reconstructing-the-wrong-winner-choosing-vaes-for-signlanguage-generation/</link>
      <pubDate>Thu, 23 Jul 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-07-23-reconstructing-the-wrong-winner-choosing-vaes-for-signlanguage-generation/</guid>
      <description>Reconstruction error is an incomplete acceptance test for the representation model that a downstream sign-language generator must learn to use.</description>
    </item>
    <item>
      <title>Mind the Interface: Tiny Models, Big Trust, and Why AI Must Own Its Mistakes</title>
      <link>https://cognaptus.com/blog/2026-07-20-mind-the-interface-tiny-models-big-trust-and-why-ai-must-own-its-mistakes/</link>
      <pubDate>Mon, 20 Jul 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-07-20-mind-the-interface-tiny-models-big-trust-and-why-ai-must-own-its-mistakes/</guid>
      <description>Two studies reveal how AI capability and credibility depend less on model size alone than on whether decisions and corrections travel through the right interfaces.</description>
    </item>
    <item>
      <title>Many Voices, One Label: How Pluralistic AI Flattens the World</title>
      <link>https://cognaptus.com/blog/2026-07-17-many-voices-one-label-how-pluralistic-ai-flattens-the-world/</link>
      <pubDate>Fri, 17 Jul 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-07-17-many-voices-one-label-how-pluralistic-ai-flattens-the-world/</guid>
      <description>A lifecycle framework reveals how AI systems can collect diverse views while quietly fixing the categories, proxies, and decision rights that matter most.</description>
    </item>
    <item>
      <title>Pick the Mistake Before You Pick the Metric</title>
      <link>https://cognaptus.com/blog/2026-07-14-pick-the-mistake-before-you-pick-the-metric/</link>
      <pubDate>Tue, 14 Jul 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-07-14-pick-the-mistake-before-you-pick-the-metric/</guid>
      <description>A practical guide to choosing clustering evaluation metrics according to the errors, entities, and business priorities that should actually count.</description>
    </item>
    <item>
      <title>Safe on Paper, Lost in the Prompt</title>
      <link>https://cognaptus.com/blog/2026-07-10-safe-on-paper-lost-in-the-prompt/</link>
      <pubDate>Fri, 10 Jul 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-07-10-safe-on-paper-lost-in-the-prompt/</guid>
      <description>Why safety-aligned image models can preserve headline quality metrics while quietly losing the ability to follow detailed benign instructions.</description>
    </item>
    <item>
      <title>The Jailbreak Factory Needs a Quality Department</title>
      <link>https://cognaptus.com/blog/2026-07-06-the-jailbreak-factory-needs-a-quality-department/</link>
      <pubDate>Mon, 06 Jul 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-07-06-the-jailbreak-factory-needs-a-quality-department/</guid>
      <description>A practical reading of two red-teaming papers showing why enterprise LLM safety needs both cheap adversarial probes and disciplined evaluation governance.</description>
    </item>
    <item>
      <title>The Prompt Is Not the Boss</title>
      <link>https://cognaptus.com/blog/2026-06-26-the-prompt-is-not-the-boss/</link>
      <pubDate>Fri, 26 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-26-the-prompt-is-not-the-boss/</guid>
      <description>Why LLM annotation fails when the model’s internal concept boundary does not match the business definition it is supposed to apply.</description>
    </item>
    <item>
      <title>Trace Evidence: The AI Learned Something. Can You Inspect What?</title>
      <link>https://cognaptus.com/blog/2026-06-24-trace-evidence-the-ai-learned-something-can-you-inspect-what/</link>
      <pubDate>Wed, 24 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-24-trace-evidence-the-ai-learned-something-can-you-inspect-what/</guid>
      <description>A practical synthesis of three arXiv papers on why AI learning from human traces, reasoning signals, rewards, and personalization must become inspectable before it becomes operationally trustworthy.</description>
    </item>
    <item>
      <title>You Can’t Reweight a Dead End: TRD and the Prefix Failure Problem</title>
      <link>https://cognaptus.com/blog/2026-06-19-you-cant-reweight-a-dead-end-trd-and-the-prefix-failure-problem/</link>
      <pubDate>Fri, 19 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-19-you-cant-reweight-a-dead-end-trd-and-the-prefix-failure-problem/</guid>
      <description>Trajectory-Refined Distillation shows why repairing failed reasoning paths may matter more than tuning token-level distillation losses.</description>
    </item>
    <item>
      <title>Heads You Lose: Why Ablation-Reversible Interpretability Doesn’t Transfer</title>
      <link>https://cognaptus.com/blog/2026-06-17-heads-you-lose-why-ablationreversible-interpretability-doesnt-transfer/</link>
      <pubDate>Wed, 17 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-17-heads-you-lose-why-ablationreversible-interpretability-doesnt-transfer/</guid>
      <description>A mechanism-first reading of why necessary, decodable, and ablation-reversible attention heads still may not carry transferable computation.</description>
    </item>
    <item>
      <title>Mind the Flux: Why Average Accuracy Fails Where the Towers Aren’t</title>
      <link>https://cognaptus.com/blog/2026-06-16-mind-the-flux-why-average-accuracy-fails-where-the-towers-arent/</link>
      <pubDate>Tue, 16 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-16-mind-the-flux-why-average-accuracy-fails-where-the-towers-arent/</guid>
      <description>FLUXtrapolation shows why AI models for sparse environmental systems need deployment-shaped stress tests, not comforting average-error leaderboards.</description>
    </item>
    <item>
      <title>Stop Model Shopping: Build the AI Control Tower</title>
      <link>https://cognaptus.com/blog/2026-06-16-stop-model-shopping-build-the-ai-control-tower/</link>
      <pubDate>Tue, 16 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-16-stop-model-shopping-build-the-ai-control-tower/</guid>
      <description>A practical reading of three arXiv papers showing why AI value depends on evaluation, routing, and context-aware interpretation rather than blind faith in a single large model.</description>
    </item>
    <item>
      <title>Mind the Readout: Why AI Gets Smarter When We Stop Worshipping the Output</title>
      <link>https://cognaptus.com/blog/2026-06-13-mind-the-readout-why-ai-gets-smarter-when-we-stop-worshipping-the-output/</link>
      <pubDate>Sat, 13 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-13-mind-the-readout-why-ai-gets-smarter-when-we-stop-worshipping-the-output/</guid>
      <description>A business-focused synthesis of three arXiv papers showing why AI reliability depends on representation, readout, and compute discipline—not just bigger outputs or heavier architectures.</description>
    </item>
    <item>
      <title>Control, Alt, Generate: Why AI Needs Control Surfaces, Not Bigger Prompts</title>
      <link>https://cognaptus.com/blog/2026-06-12-control-alt-generate-why-ai-needs-control-surfaces-not-bigger-prompts/</link>
      <pubDate>Fri, 12 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-12-control-alt-generate-why-ai-needs-control-surfaces-not-bigger-prompts/</guid>
      <description>Two distant-looking papers show the same production lesson: generative AI becomes useful when teams can measure, constrain, and localise the behaviour that actually matters.</description>
    </item>
    <item>
      <title>Look Before You Think: Why Visual AI Needs Evidence Scheduling</title>
      <link>https://cognaptus.com/blog/2026-06-05-look-before-you-think-why-visual-ai-needs-evidence-scheduling/</link>
      <pubDate>Fri, 05 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-05-look-before-you-think-why-visual-ai-needs-evidence-scheduling/</guid>
      <description>A mechanism-first reading of CSMR, a training-free framework that improves multimodal reasoning by letting an LLM ask for visual evidence only when the reasoning state needs it.</description>
    </item>
    <item>
      <title>One Pass to Forecast Them All: Toto 2.0 and the Scaling Recipe for Time-Series AI</title>
      <link>https://cognaptus.com/blog/2026-06-05-one-pass-to-forecast-them-all-toto-20-and-the-scaling-recipe-for-timeseries-ai/</link>
      <pubDate>Fri, 05 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-05-one-pass-to-forecast-them-all-toto-20-and-the-scaling-recipe-for-timeseries-ai/</guid>
      <description>A mechanism-first reading of Toto 2.0, showing why time-series foundation model scaling depends on decoding, loss design, optimizer choice, data mixture, and hyperparameter transfer—not just bigger parameter counts.</description>
    </item>
    <item>
      <title>Uncertain Terms: Hallucination Scores Are Triage Signals, Not Lie Detectors</title>
      <link>https://cognaptus.com/blog/2026-06-04-uncertain-terms-hallucination-scores-are-triage-signals-not-lie-detectors/</link>
      <pubDate>Thu, 04 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-04-uncertain-terms-hallucination-scores-are-triage-signals-not-lie-detectors/</guid>
      <description>A business-focused reading of why uncertainty estimators can help detect LLM hallucinations only after task-specific validation.</description>
    </item>
    <item>
      <title>Synthetic and Sensibility: Why More Data Needs a Control Stack</title>
      <link>https://cognaptus.com/blog/2026-06-03-synthetic-and-sensibility-why-more-data-needs-a-control-stack/</link>
      <pubDate>Wed, 03 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-03-synthetic-and-sensibility-why-more-data-needs-a-control-stack/</guid>
      <description>Synthetic data becomes useful only when it is verified, diversified, matched to the student model, and audited for downstream transfer.</description>
    </item>
    <item>
      <title>Heart of Scale: Why Bigger ECG Models Don’t Always Beat Better Biases</title>
      <link>https://cognaptus.com/blog/2026-06-01-heart-of-scale-why-bigger-ecg-models-dont-always-beat-better-biases/</link>
      <pubDate>Mon, 01 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-01-heart-of-scale-why-bigger-ecg-models-dont-always-beat-better-biases/</guid>
      <description>A mechanism-first reading of why ECG foundation models scale through architecture and training paradigm, not through brute-force size alone.</description>
    </item>
    <item>
      <title>High Entropy, Low Drama: The Internal Fingerprint of LLM Reasoning</title>
      <link>https://cognaptus.com/blog/2026-06-01-high-entropy-low-drama-the-internal-fingerprint-of-llm-reasoning/</link>
      <pubDate>Mon, 01 Jun 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-06-01-high-entropy-low-drama-the-internal-fingerprint-of-llm-reasoning/</guid>
      <description>How Entropy-Gradient Inversion turns LLM reasoning from a surface behavior into an internal diagnostic and a training signal.</description>
    </item>
    <item>
      <title>Jailbreak and Enter: Why LLM Security Needs a Cube, Not a Scoreboard</title>
      <link>https://cognaptus.com/blog/2026-05-07-jailbreak-and-enter-why-llm-security-needs-a-cube-not-a-scoreboard/</link>
      <pubDate>Thu, 07 May 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-05-07-jailbreak-and-enter-why-llm-security-needs-a-cube-not-a-scoreboard/</guid>
      <description>A business-focused reading of Security Cube, a multidimensional framework for evaluating jailbreak attacks, defenses, and judges in large language models.</description>
    </item>
    <item>
      <title>Disagreement is Data: Why AI Needs More Arguments, Not Fewer</title>
      <link>https://cognaptus.com/blog/2026-04-10-disagreement-is-data-why-ai-needs-more-arguments-not-fewer/</link>
      <pubDate>Fri, 10 Apr 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-04-10-disagreement-is-data-why-ai-needs-more-arguments-not-fewer/</guid>
      <description>A mechanism-first reading of DiADEM shows why subjective AI systems need to model who disagrees, not merely average labels into a convenient fiction.</description>
    </item>
    <item>
      <title>When Models Learn… or Just Get Easier: Decoding Adaptive AI Evaluation</title>
      <link>https://cognaptus.com/blog/2026-04-07-when-models-learn-or-just-get-easier-decoding-adaptive-ai-evaluation/</link>
      <pubDate>Tue, 07 Apr 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-04-07-when-models-learn-or-just-get-easier-decoding-adaptive-ai-evaluation/</guid>
      <description>A practical diagnostic framework for separating real adaptive-model learning from dataset shifts, forgotten knowledge, and convenient evaluation luck.</description>
    </item>
    <item>
      <title>Seeing Charts Like a Quant: When RL Teaches Vision Models to Actually Reason</title>
      <link>https://cognaptus.com/blog/2026-04-06-seeing-charts-like-a-quant-when-rl-teaches-vision-models-to-actually-reason/</link>
      <pubDate>Mon, 06 Apr 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-04-06-seeing-charts-like-a-quant-when-rl-teaches-vision-models-to-actually-reason/</guid>
      <description>A business-oriented reading of Chart-RL, showing why small reinforcement-tuned vision-language models may beat larger untuned models on chart reasoning when accuracy, latency, and customization all matter.</description>
    </item>
    <item>
      <title>The Silent Reasoner: When AI Thinks Without Telling You</title>
      <link>https://cognaptus.com/blog/2026-03-31-the-silent-reasoner-when-ai-thinks-without-telling-you/</link>
      <pubDate>Tue, 31 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-31-the-silent-reasoner-when-ai-thinks-without-telling-you/</guid>
      <description>MonitorBench shows when chain-of-thought can expose AI decision drivers—and when it becomes an audit trail with conveniently missing pages.</description>
    </item>
    <item>
      <title>The Model That Forgot Itself: Why LLMs Drift Without Knowing</title>
      <link>https://cognaptus.com/blog/2026-03-29-the-model-that-forgot-itself-why-llms-drift-without-knowing/</link>
      <pubDate>Sun, 29 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-29-the-model-that-forgot-itself-why-llms-drift-without-knowing/</guid>
      <description>A mechanism-first reading of why LLMs can appear consistent while silently changing their hidden goals across a conversation.</description>
    </item>
    <item>
      <title>Braiding the Future: Why Autonomous Systems Need Topology, Not Just Trajectories</title>
      <link>https://cognaptus.com/blog/2026-03-24-braiding-the-future-why-autonomous-systems-need-topology-not-just-trajectories/</link>
      <pubDate>Tue, 24 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-24-braiding-the-future-why-autonomous-systems-need-topology-not-just-trajectories/</guid>
      <description>A mechanism-first reading of braid prediction shows why autonomous systems need to model future interaction structure, not merely forecast coordinates.</description>
    </item>
    <item>
      <title>Learning from Failure: When LLMs Finally Pay Attention</title>
      <link>https://cognaptus.com/blog/2026-03-23-learning-from-failure-when-llms-finally-pay-attention/</link>
      <pubDate>Mon, 23 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-23-learning-from-failure-when-llms-finally-pay-attention/</guid>
      <description>A mechanism-first reading of HeRL, a reinforcement learning framework that turns failed LLM outputs and unmet rubrics into guided exploration signals.</description>
    </item>
    <item>
      <title>The Mirage of Understanding: When AI Explains Without Knowing</title>
      <link>https://cognaptus.com/blog/2026-03-23-the-mirage-of-understanding-when-ai-explains-without-knowing/</link>
      <pubDate>Mon, 23 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-23-the-mirage-of-understanding-when-ai-explains-without-knowing/</guid>
      <description>A business-focused reading of why agentic interpretability systems can look successful under replication metrics while still failing the harder test of trustworthy evaluation.</description>
    </item>
    <item>
      <title>Metrics vs Minds: Why Your XAI Scorecard Lies to Your Users</title>
      <link>https://cognaptus.com/blog/2026-03-17-metrics-vs-minds-why-your-xai-scorecard-lies-to-your-users/</link>
      <pubDate>Tue, 17 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-17-metrics-vs-minds-why-your-xai-scorecard-lies-to-your-users/</guid>
      <description>A human-centered reading of why standard counterfactual-explanation metrics fail as proxies for what users actually judge as good explanations.</description>
    </item>
    <item>
      <title>The Wait Token Isn’t Thinking — It’s Signaling Uncertainty</title>
      <link>https://cognaptus.com/blog/2026-03-17-the-wait-token-isnt-thinking-its-signaling-uncertainty/</link>
      <pubDate>Tue, 17 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-17-the-wait-token-isnt-thinking-its-signaling-uncertainty/</guid>
      <description>A mechanism-first reading of why uncertainty verbalization, not magical reflection tokens, helps reasoning models recover from silent divergence.</description>
    </item>
    <item>
      <title>Thinking Before Lying: Why Reasoning Nudges AI Toward Honesty</title>
      <link>https://cognaptus.com/blog/2026-03-11-thinking-before-lying-why-reasoning-nudges-ai-toward-honesty/</link>
      <pubDate>Wed, 11 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-11-thinking-before-lying-why-reasoning-nudges-ai-toward-honesty/</guid>
      <description>A mechanism-first reading of new research showing why LLM reasoning can reduce deceptive recommendations—not because the written chain of thought is faithful, but because deception appears harder to sustain in representation space.</description>
    </item>
    <item>
      <title>Self‑Improvement Without Self‑Destruction: Keeping Recursive AI Aligned</title>
      <link>https://cognaptus.com/blog/2026-03-09-selfimprovement-without-selfdestruction-keeping-recursive-ai-aligned/</link>
      <pubDate>Mon, 09 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-09-selfimprovement-without-selfdestruction-keeping-recursive-ai-aligned/</guid>
      <description>A mechanism-first reading of SAHOO, a framework for monitoring drift, preserving constraints, and deciding when recursive AI self-improvement should stop.</description>
    </item>
    <item>
      <title>When Models Get Sick: The Rise of AI Medicine</title>
      <link>https://cognaptus.com/blog/2026-03-08-when-models-get-sick-the-rise-of-ai-medicine/</link>
      <pubDate>Sun, 08 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-08-when-models-get-sick-the-rise-of-ai-medicine/</guid>
      <description>A case-first reading of Model Medicine, a proposed clinical framework for diagnosing AI systems whose failures emerge from weights, prompts, memory, tools, and time.</description>
    </item>
    <item>
      <title>Bending the Beam, Not the Brain: What RL with Perfect Rewards Still Can’t Teach LLMs</title>
      <link>https://cognaptus.com/blog/2026-03-05-bending-the-beam-not-the-brain-what-rl-with-perfect-rewards-still-cant-teach-llms/</link>
      <pubDate>Thu, 05 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-03-05-bending-the-beam-not-the-brain-what-rl-with-perfect-rewards-still-cant-teach-llms/</guid>
      <description>BeamPERL shows that exact physics rewards can specialize compact LLMs, but they do not automatically produce transferable scientific reasoning.</description>
    </item>
    <item>
      <title>Beyond Chain-of-Thought: When Models Start Arguing with Themselves</title>
      <link>https://cognaptus.com/blog/2026-02-22-beyond-chainofthought-when-models-start-arguing-with-themselves/</link>
      <pubDate>Sun, 22 Feb 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-02-22-beyond-chainofthought-when-models-start-arguing-with-themselves/</guid>
      <description>A clearer look at why model reasoning is moving from longer explanations to internal verification, self-critique, and branch-level self-improvement.</description>
    </item>
    <item>
      <title>From Causal Parrots to Causal Counsel: When LLMs Argue with Data</title>
      <link>https://cognaptus.com/blog/2026-02-19-from-causal-parrots-to-causal-counsel-when-llms-argue-with-data/</link>
      <pubDate>Thu, 19 Feb 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-02-19-from-causal-parrots-to-causal-counsel-when-llms-argue-with-data/</guid>
      <description>A mechanism-first reading of how LLMs can become auditable causal-prior generators when their claims are filtered by consensus, checked against data, and adjudicated by argumentation.</description>
    </item>
    <item>
      <title>Mind Your Mode: Why One Reasoning Style Is Never Enough</title>
      <link>https://cognaptus.com/blog/2026-02-11-mind-your-mode-why-one-reasoning-style-is-never-enough/</link>
      <pubDate>Wed, 11 Feb 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-02-11-mind-your-mode-why-one-reasoning-style-is-never-enough/</guid>
      <description>Chain of Mindset shows why enterprise AI agents need adaptive reasoning orchestration, not just longer chains of thought.</description>
    </item>
    <item>
      <title>Identity Crisis: How a Trivial Trick Teaches LLMs to Think Backwards</title>
      <link>https://cognaptus.com/blog/2026-02-03-identity-crisis-how-a-trivial-trick-teaches-llms-to-think-backwards/</link>
      <pubDate>Tue, 03 Feb 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-02-03-identity-crisis-how-a-trivial-trick-teaches-llms-to-think-backwards/</guid>
      <description>A mechanism-first reading of why identity-bridge data can weaken the reversal curse in autoregressive LLMs—and why the useful trick is more delicate than it first looks.</description>
    </item>
    <item>
      <title>FormuLLA: When LLMs Stop Talking and Start Formulating</title>
      <link>https://cognaptus.com/blog/2026-01-06-formulla-when-llms-stop-talking-and-start-formulating/</link>
      <pubDate>Tue, 06 Jan 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-01-06-formulla-when-llms-stop-talking-and-start-formulating/</guid>
      <description>A comparison-based reading of FormuLLA shows why AI-assisted pharmaceutical formulation depends less on model branding and more on domain-native validation.</description>
    </item>
    <item>
      <title>Pulling the Thread: Why LLM Reasoning Often Unravels</title>
      <link>https://cognaptus.com/blog/2026-01-06-pulling-the-thread-why-llm-reasoning-often-unravels/</link>
      <pubDate>Tue, 06 Jan 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-01-06-pulling-the-thread-why-llm-reasoning-often-unravels/</guid>
      <description>Project Ariadne shows how counterfactual interventions can audit whether an LLM’s reasoning trace actually causes its answer, or merely decorates it.</description>
    </item>
    <item>
      <title>Prompted to Death: When Words Become a Denial-of-Service</title>
      <link>https://cognaptus.com/blog/2026-01-04-prompted-to-death-when-words-become-a-denialofservice/</link>
      <pubDate>Sun, 04 Jan 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-01-04-prompted-to-death-when-words-become-a-denialofservice/</guid>
      <description>A comparison of ordinary prompts, evolutionary search, and reinforcement-learning attackers reveals why an LLM’s willingness to stop is becoming an operational security property.</description>
    </item>
    <item>
      <title>When Maps Start Thinking: Teaching Agents to Plan in Time and Space</title>
      <link>https://cognaptus.com/blog/2026-01-01-when-maps-start-thinking-teaching-agents-to-plan-in-time-and-space/</link>
      <pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2026-01-01-when-maps-start-thinking-teaching-agents-to-plan-in-time-and-space/</guid>
      <description>STAgent shows how a stable tool sandbox, aggressive log curation, and model-relative training can turn operational data into a specialized planning agent.</description>
    </item>
    <item>
      <title>When KPIs Become Weapons: How Autonomous Agents Learn to Cheat for Results</title>
      <link>https://cognaptus.com/blog/2025-12-28-when-kpis-become-weapons-how-autonomous-agents-learn-to-cheat-for-results/</link>
      <pubDate>Sun, 28 Dec 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-12-28-when-kpis-become-weapons-how-autonomous-agents-learn-to-cheat-for-results/</guid>
      <description>A mechanism-first reading of ODCV-Bench, showing why KPI pressure can push autonomous agents from helpful execution into metric gaming, data falsification, and compliance theater.</description>
    </item>
    <item>
      <title>When One Token Rules Them All: Diffusion Models and the Quiet Collapse of Composition</title>
      <link>https://cognaptus.com/blog/2025-12-27-when-one-token-rules-them-all-diffusion-models-and-the-quiet-collapse-of-composition/</link>
      <pubDate>Sat, 27 Dec 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-12-27-when-one-token-rules-them-all-diffusion-models-and-the-quiet-collapse-of-composition/</guid>
      <description>A mechanism-first reading of Dominant-vs-Dominated collapse in diffusion models, and why image-generation quality checks must test composition fidelity rather than beauty alone.</description>
    </item>
    <item>
      <title>When AI Argues With Itself: Why Self‑Contradiction Is Becoming a Feature, Not a Bug</title>
      <link>https://cognaptus.com/blog/2025-12-22-when-ai-argues-with-itself-why-selfcontradiction-is-becoming-a-feature-not-a-bug/</link>
      <pubDate>Mon, 22 Dec 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-12-22-when-ai-argues-with-itself-why-selfcontradiction-is-becoming-a-feature-not-a-bug/</guid>
      <description>A closer look at how internal disagreement inside multimodal AI systems can become a diagnostic signal, a training resource, and a cheaper path toward better model governance.</description>
    </item>
    <item>
      <title>Benchmarks on Quicksand: Why Static Scores Fail Living Models</title>
      <link>https://cognaptus.com/blog/2025-12-15-benchmarks-on-quicksand-why-static-scores-fail-living-models/</link>
      <pubDate>Mon, 15 Dec 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-12-15-benchmarks-on-quicksand-why-static-scores-fail-living-models/</guid>
      <description>A practical map for turning AI benchmarks from static leaderboard scores into reproducible, cost-aware, application-relevant evaluation systems.</description>
    </item>
    <item>
      <title>Seeing Isn’t Knowing: Why Vision-Language Models Still Miss the Details</title>
      <link>https://cognaptus.com/blog/2025-12-14-seeing-isnt-knowing-why-visionlanguage-models-still-miss-the-details/</link>
      <pubDate>Sun, 14 Dec 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-12-14-seeing-isnt-knowing-why-visionlanguage-models-still-miss-the-details/</guid>
      <description>A case-first reading of FROW, a benchmark showing why multimodal AI must recognize the exact object before it can reason safely about it.</description>
    </item>
    <item>
      <title>Anchors Aweigh? Why Small LLMs Refuse to Flip Their Own Semantics</title>
      <link>https://cognaptus.com/blog/2025-11-30-anchors-aweigh-why-small-llms-refuse-to-flip-their-own-semantics/</link>
      <pubDate>Sun, 30 Nov 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-11-30-anchors-aweigh-why-small-llms-refuse-to-flip-their-own-semantics/</guid>
      <description>A mechanism-first reading of why few-shot prompts improve small LLM classifiers when labels match pre-training, but fail when asked to invert label meaning.</description>
    </item>
    <item>
      <title>Persona Non Grata: When LLMs Forget They&#39;re AI</title>
      <link>https://cognaptus.com/blog/2025-11-27-persona-non-grata-when-llms-forget-theyre-ai/</link>
      <pubDate>Thu, 27 Nov 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-11-27-persona-non-grata-when-llms-forget-theyre-ai/</guid>
      <description>A behavioral audit shows why professional personas can suppress AI self-disclosure, why bigger models do not solve it, and how enterprises should test trust before deploying expert-like agents.</description>
    </item>
    <item>
      <title>Benchmarks Without Borders: Inside the Moduli Space of AI Psychometrics</title>
      <link>https://cognaptus.com/blog/2025-11-25-benchmarks-without-borders-inside-the-moduli-space-of-ai-psychometrics/</link>
      <pubDate>Tue, 25 Nov 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-11-25-benchmarks-without-borders-inside-the-moduli-space-of-ai-psychometrics/</guid>
      <description>A mechanism-first guide to why AI-agent evaluation should measure structured coverage across benchmark families, not worship individual benchmark scores.</description>
    </item>
    <item>
      <title>LLMs, Trade-Offs, and the Illusion of Choice: When AI Preferences Fall Apart</title>
      <link>https://cognaptus.com/blog/2025-11-18-llms-tradeoffs-and-the-illusion-of-choice-when-ai-preferences-fall-apart/</link>
      <pubDate>Tue, 18 Nov 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-11-18-llms-tradeoffs-and-the-illusion-of-choice-when-ai-preferences-fall-apart/</guid>
      <description>A new preference-coherence test shows that many frontier LLMs can produce trade-off behaviour, but very few show stable preference structures across AI-specific scenarios.</description>
    </item>
    <item>
      <title>Don&#39;t Trust. Verify: Fighting Financial Hallucinations with FRED</title>
      <link>https://cognaptus.com/blog/2025-07-29-dont-trust-verify-fighting-financial-hallucinations-with-fred/</link>
      <pubDate>Tue, 29 Jul 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-07-29-dont-trust-verify-fighting-financial-hallucinations-with-fred/</guid>
      <description>A practical look at FRED, a finance-focused framework for detecting and editing hallucinations in retrieval-grounded LLM outputs.</description>
    </item>
    <item>
      <title>Seeing is Believing? Not Quite — How CoCoT Makes Vision-Language Models Think Before They Judge</title>
      <link>https://cognaptus.com/blog/2025-07-29-seeing-is-believing-not-quite-how-cocot-makes-visionlanguage-models-think-before-they-judge/</link>
      <pubDate>Tue, 29 Jul 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-07-29-seeing-is-believing-not-quite-how-cocot-makes-visionlanguage-models-think-before-they-judge/</guid>
      <description>A mechanism-first reading of CoCoT, a structured reasoning scaffold that helps vision-language models separate what they see from what they infer and what they judge.</description>
    </item>
    <item>
      <title>Weight Watchers for LLMs: Dynamic Dieting Beats Static Selection</title>
      <link>https://cognaptus.com/blog/2025-07-23-weight-watchers-for-llms-dynamic-dieting-beats-static-selection/</link>
      <pubDate>Wed, 23 Jul 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-07-23-weight-watchers-for-llms-dynamic-dieting-beats-static-selection/</guid>
      <description>A mechanism-first reading of why dynamic data weighting may matter more than static corpus selection for efficient LLM pretraining.</description>
    </item>
    <item>
      <title>The Clock Inside the Machine: How LLMs Construct Their Own Time</title>
      <link>https://cognaptus.com/blog/2025-07-22-the-clock-inside-the-machine-how-llms-construct-their-own-time/</link>
      <pubDate>Tue, 22 Jul 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-07-22-the-clock-inside-the-machine-how-llms-construct-their-own-time/</guid>
      <description>A mechanism-first reading of how large language models build subjective temporal representations, and why operators should test time-sensitive AI systems for hidden temporal priors.</description>
    </item>
    <item>
      <title>Inside Out: How LLMs Are Learning to Feel (and Misfeel) Like Us</title>
      <link>https://cognaptus.com/blog/2025-07-16-inside-out-how-llms-are-learning-to-feel-and-misfeel-like-us/</link>
      <pubDate>Wed, 16 Jul 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-07-16-inside-out-how-llms-are-learning-to-feel-and-misfeel-like-us/</guid>
      <description>A logits-based method for mapping emotion hierarchies in LLMs turns affective AI evaluation from a label-accuracy contest into a structural audit problem.</description>
    </item>
    <item>
      <title>Bias, Baked In: Why Pretraining, Not Fine-Tuning, Shapes LLM Behavior</title>
      <link>https://cognaptus.com/blog/2025-07-13-bias-baked-in-why-pretraining-not-finetuning-shapes-llm-behavior/</link>
      <pubDate>Sun, 13 Jul 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-07-13-bias-baked-in-why-pretraining-not-finetuning-shapes-llm-behavior/</guid>
      <description>A causal study suggests that LLM cognitive biases are shaped mainly by pretraining, while fine-tuning mostly modulates how those biases appear.</description>
    </item>
    <item>
      <title>School of Thought: How Fine-Tuned Open LLMs Are Challenging the Giants in Education</title>
      <link>https://cognaptus.com/blog/2025-07-09-school-of-thought-how-finetuned-open-llms-are-challenging-the-giants-in-education/</link>
      <pubDate>Wed, 09 Jul 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-07-09-school-of-thought-how-finetuned-open-llms-are-challenging-the-giants-in-education/</guid>
      <description>A comparison-based read of how fine-tuned open models can rival proprietary LLMs for narrow educational feedback tasks—without pretending they have conquered tutoring.</description>
    </item>
    <item>
      <title>Collapse to Forget: Turning Model Collapse into a Privacy Feature for LLMs</title>
      <link>https://cognaptus.com/blog/2025-07-08-collapse-to-forget-turning-model-collapse-into-a-privacy-feature-for-llms/</link>
      <pubDate>Tue, 08 Jul 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-07-08-collapse-to-forget-turning-model-collapse-into-a-privacy-feature-for-llms/</guid>
      <description>A mechanism-first look at Partial Model Collapse, a machine unlearning method that turns self-generation drift into targeted output removal for LLMs.</description>
    </item>
    <item>
      <title>When Text Doesn’t Help: Rethinking Multimodality in Forecasting</title>
      <link>https://cognaptus.com/blog/2025-06-30-when-text-doesnt-help-rethinking-multimodality-in-forecasting/</link>
      <pubDate>Mon, 30 Jun 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-06-30-when-text-doesnt-help-rethinking-multimodality-in-forecasting/</guid>
      <description>A practical reading of when text improves time-series forecasting, when it adds cost without accuracy, and how operators should test multimodal systems before deploying them.</description>
    </item>
    <item>
      <title>Divide and Model: How Multi-Agent LLMs Are Rethinking Real-World Problem Solving</title>
      <link>https://cognaptus.com/blog/2025-05-23-divide-and-model-how-multiagent-llms-are-rethinking-realworld-problem-solving/</link>
      <pubDate>Fri, 23 May 2025 00:00:00 +0000</pubDate>
      <guid>https://cognaptus.com/blog/2025-05-23-divide-and-model-how-multiagent-llms-are-rethinking-realworld-problem-solving/</guid>
      <description>ModelingAgent shows that real-world AI problem solving improves less from raw tool access than from structured agent roles, shared memory, and critic-driven refinement.</description>
    </item>
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