Prompt Wars: When Pedagogy Beats Cleverness
A tournament-style prompt evaluation study shows why educational AI teams need evidence, not just elegant prompt wording.
Cognaptus Insights
Industry thoughts, trends, and commentary.
Seeing Is Misleading: When Climate Images Need Receipts
A practical reading of why multimodal climate fact-checking needs evidence orchestration, not just a larger vision-language model with a browser attached.
Skeletons in the Proof Closet: When Lean Provers Need Hints, Not More Compute
A diagnostic study of RL-trained Lean provers shows that more inference samples can repeat the same failed strategy, while tactic-level structural hints recover proofs that random sampling misses.
Auditing the Illusion of Forgetting: When Unlearning Isn’t Enough
A mechanism-first reading of why LLM unlearning can look successful at the output layer while membership traces remain detectable inside model representations.
DISARM, but Make It Agentic: When Frameworks Start Doing the Work
A mechanism-first reading of how an agentic DISARM pipeline turns disinformation investigation from expert taxonomy work into auditable, semi-automated evidence production.
Many Minds, One Solution: Why Multi‑Agent AI Finds What Single Models Miss
A mechanism-first reading of why multi-agent LLM systems can improve results without adding information: they factor constraints across agents and stabilize solutions that single update dynamics may not reach.
Noise Without Regret: How Error Feedback Fixes Differentially Private Image Generation
A mechanism-first reading of how error feedback, reconstruction loss, and noise injection improve differentially private image generation without pretending the privacy-utility tradeoff has disappeared.
Pay to Think: Incentive Design Is the Hidden Variable in Human–AI Research
A mechanism-first reading of why participant incentives are not administrative trivia, but part of the experimental machinery behind human–AI decision-making evidence.
When Data Can’t Travel, Models Must: Federated Transformers Meet Brain Tumor Reality
A practical reading of how federated Transformer-GNN training can help medical-AI teams overcome local data scarcity without pretending privacy is solved by architecture alone.
Your Agent Remembers—But Can It Forget?
Why memory rewriting, not just memory retention, is becoming a hard diagnostic problem for reinforcement learning agents.