New research addresses how to improve language model reasoning during inference without repeated generation or external verification systems. The proposed…
GameWAM addresses a gap between game-playing agents, which typically lack explicit modeling of world dynamics, and game world models, which…
A new benchmark investigates whether current video generation models can function as authentic world models by accurately reproducing the distribution…
New research investigates whether multimodal large language models can translate local visual perception into effective spatial navigation within complex urban…
Researchers propose Test-Time Policy Optimization (TTPO), a label-free training objective for adapting language models to math reasoning tasks at test…
A technical report from Alibaba’s Taobao Live team describes Harness-Aware Training (HAT), a method for training compact models to adapt…
This paper introduces PILOT, a supervisor-worker agent harness that performs self-improvement live during a run rather than only after it…
This study systematically compares Evolution Strategies (ES) against Group Relative Policy Optimization (GRPO) as post-training paradigms for LLM reasoning. It…
WikiSkill is a framework that co-evolves an LLM agent’s reusable skill library alongside a persistent wiki-style knowledge base, separating raw…
CaSKG is a retrieval framework that calibrates the reliability of a skill graph’s edges before using it to retrieve procedural…
This paper formalizes what is required to legitimately ‘replay’ a claim attached to an LLM evaluation metric, then applies that…
VoiceMem is a memory architecture for duplex speech language models built around a parallel ‘informational left brain’ and ’emotional right…
