Reading the Room: When Long-Document Models Finally Learn to Pay Attention
A mechanism-first look at how sentence-aware readability models can turn long-document difficulty assessment from a blunt label into a diagnostic workflow.
A mechanism-first look at how sentence-aware readability models can turn long-document difficulty assessment from a blunt label into a diagnostic workflow.
Tool-RoCo shows why multi-agent LLM systems need evaluation of coordination lifecycle decisions, not just final task success or agent activation.
EvRainDrop shows why sparse event-camera streams may need relational completion before they can become reliable business perception systems.
A business-focused reading of Emmi-Wing, AB-UPT, and what neural CFD surrogates can—and cannot—change in aerodynamic design.
ChatDRex shows why the safest enterprise AI agents may be the ones that stop pretending to know everything and start routing work to validated tools.
A formal causality paper shows why the real business question is not merely what caused an outcome, but which counterfactual language your explanation system is allowed to use.
A mechanism-first analysis of Prune4Web and why reliable web agents may depend less on larger context windows than on better ways to shrink the page before reasoning begins.
A mechanism-first reading of MADRA, a training-free multi-agent debate system that treats embodied AI safety as a decision-gate problem rather than a stronger-prompt problem.
OVOD-Agent shows how a small Markov-Bandit reasoning layer can improve rare-category detection without putting an LLM in the detection loop.
EWE shows how agentic AI can turn extreme-weather diagnosis from a scarce expert workflow into a structured, auditable climate-intelligence pipeline.