2 citations · 3 across the 20 of their papers we have counts for
4 papers · 1 filter
ReTTT: Reflection-Driven Test-Time Training via Experience-Based Parametric Memory
Kangcong Li, Hangfan Zhang, Shuyue Hu +2
LLM agents accumulate valuable task-specific information through their actions, observations, and environmental feedback during multi-turn task execution. When effectively used, th…
Loop-Free Inverse Reinforcement Learning via Sequential Value Recovery with Q-Score Matching
Yang Chen, Yang chen, Yitan Zhang +2
Inverse Reinforcement Learning (IRL) aims to recover a reward function that explains expert demonstrations. Existing IRL methods typically rely on a bi-level optimization procedure…
MARTI-MARS: Scaling Multi-Agent Self-Search via Reinforcement Learning for Code Generation
Shijie Wang, Pengfei Li, Yikun Fu +21
While the complex reasoning capability of Large Language Models (LLMs) has attracted significant attention, single-agent systems often encounter inherent performance ceilings in co…
ICL-Router: In-Context Learned Model Representations for LLM Routing
Chenxu Wang, Hao Li, Yiqun Zhang +6
Large language models (LLMs) often exhibit complementary strengths. Model routing harnesses these strengths by dynamically directing each query to the most suitable model, given a…