AI & Agents
Research on AI & Agents: explanations, evidence, limitations and connections between papers.
7 results
A human-trained user simulator improves agent training
MIMESIS models varied human behavior; agents trained with it score better than GPT-5.5-trained agents across nine simulated users.
A graph result powers faster structured language decoding
A GPU decoding engine recomputes format masks and speeds six JSON extractions on one tested laptop.
CanonQ trains language models to use one shared low-bit codec
CanonQ improves measured accuracy and text prediction for a tested language model under joint low-bit compression.
Home automation can use different models for different calls
A live test of per-call model choices matched all-hosted human judgments on 39 of 43 counted cases, at lower hosted spend.
Visible labels can mislead language model judges
Tests find that visible system labels can distort language model judgments of entity alignment decisions in the studied conditions.
RT-SAFE reveals safety failures hidden by navigation success
RT-SAFE tests urban-agent safety during decisions; hard-route runs exposed risks hidden by successful arrivals in a changing world.
Why language models can overstate their progress
A statistical model and loop tests show why reused examples can make language-model progress scores too optimistic.