works on

From the 1 of 8 linked papers with an AI index.

collaborators

8 papers

cs.CL2026

MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems

Xinle Deng, Ruobin Zhong, Hujin Peng +15

The paper introduces MemTrace, a framework that converts large language model memory pipelines into executable graphs to trace and attribute errors, and provides a benchmark (MemTr…

cs.AI2026

Which Tokens Matter? Adaptive Token Selection for RLVR with the Relative Surprisal Index

Outongyi Lv, Yanzhao Zheng, Yuanwei Zhang +5

Reinforcement learning (RL) has become a powerful tool for propelling Large Language Models (LLMs) beyond imitation-based training towards more robust reasoning capabilities. Among…

cs.CL2026

Rethinking Memory as Continuously Evolving Connectivity

Jizhan Fang, Buqiang Xu, Zhixian Wang +12

Existing memory-augmented LLM agents often treat memory as a static repository with pre-defined representations and fixed retrieval pipelines, which is brittle in dynamic agentic e…

cs.CL2026

Rubrics to Tokens: Bridging Response-level Rubrics and Token-level Rewards in Instruction Following Tasks

Tianze Xu, Yanzhao Zheng, Pengrui Lu +11

Rubric-based Reinforcement Learning (RL) has emerged as a promising approach for aligning Large Language Models (LLMs) with complex, open-domain instruction following tasks. Howeve…

cs.AI2026

ContextBudget: Budget-Aware Context Management for Long-Horizon Search Agents

Yong Wu, YanZhao Zheng, TianZe Xu +9

LLM-based agents show strong potential for long-horizon reasoning, yet their context size is limited by deployment factors (e.g., memory, latency, and cost), yielding a constrained…

cs.LG2026

SkillRouter: Skill Routing for LLM Agents at Scale

YanZhao Zheng, ZhenTao Zhang, Chao Ma +8

Reusable skills let LLM agents package task-specific procedures, tool affordances, and execution guidance into modular building blocks. As skill ecosystems grow to tens of thousand…