Lost in the Links: When World Knowledge Isn’t Enough
LLM-WikiRace shows why agent reliability depends less on stored knowledge and more on planning, recovery, and loop control.
LLM-WikiRace shows why agent reliability depends less on stored knowledge and more on planning, recovery, and loop control.
A mechanism-first reading of IndicJR, a benchmark showing why multilingual chatbot safety cannot be certified by English tests, JSON contracts, or native-script assumptions alone.
DeepContext shows why enterprise AI safety may need stateful intent tracking more than larger stateless guard models.
A mechanism-first reading of how narrow multimodal fine-tuning can turn a localized data problem into broad safety drift across vision-language agents.
A mechanism-first reading of MolHIT, a molecular graph diffusion framework that shows why chemical representation, not just model scale, can decide whether generated molecules are valid, novel, and controllable.
A mechanism-first reading of AutoNumerics, showing why automated PDE solving is less about code generation and more about controlled solver planning, debugging, and verification.
AI GAMESTORE shows why frontier models still struggle with rapid learning, memory, planning, and world-model discovery in interactive tasks humans treat as casual.
A mechanism-first reading of ODESteer, an inference-time alignment method that turns activation steering from one-shot vector editing into adaptive control.
A comparison-based reading of a hybrid CNN–SWIN Transformer lung X-ray model, where the useful lesson is not just accuracy but the trade-off between fusion, privacy, overfitting, and infrastructure cost.
A practical reading of Policy Cards and why autonomous AI agents need machine-readable governance before they can become reliable business infrastructure.