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20222026
most citedLarge Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!

105 citations · 136 across the 21 of their papers we have counts for

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9 papers · 1 filter

cs.CL2026

Qwen-AgentWorld: Language World Models for General Agents

Yuxin Zuo, Zikai Xiao, Li Sheng +30

A world model predicts environment dynamics based on current observations and actions, serving as a core cognitive mechanism for reasoning and planning. In this work, we investigat…

cs.CL2026

ARES: Automated Rubric Synthesis for Scalable LLM Reinforcement Learning

Xiaoyuan Li, Keqin Bao, Moxin Li +5

Rubric-based rewards offer a promising way to extend reinforcement learning (RL) for large language models beyond tasks with automatically verifiable answers. However, scaling rubr…

cs.CL2026

Unified Data Selection for LLM Reasoning

Xiaoyuan Li, Yubo Ma, Chengpeng Li +6

Effectively training Large Language Models (LLMs) for complex, long-CoT reasoning is often bottlenecked by the need for massive high-quality reasoning data. Existing methods are ei…

cs.CL2026

SkillGraph: Skill-Augmented Reinforcement Learning for Agents via Evolving Skill Graphs

Xiaoyuan Li, Moxin Li, Keqin Bao +4

Skill libraries enable large language model agents to reuse experience from past interactions, but most existing libraries store skills as isolated entries and retrieve them only b…

cs.CL2026

On Predicting the Post-training Potential of Pre-trained LLMs

Xiaoyuan Li, Yubo Ma, Kexin Yang +5

The performance of Large Language Models (LLMs) on downstream tasks is fundamentally constrained by the capabilities acquired during pre-training. However, traditional benchmarks l…

cs.CL2026

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models

Boyi Deng, Xu Wang, Yaoning Wang +15

Large language models have achieved remarkable capabilities across diverse tasks, yet their internal decision-making processes remain largely opaque, limiting our ability to inspec…

cs.CL2026

WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation

Shuangrui Ding, Xuanlang Dai, Long Xing +14

Large language and vision-language models increasingly power agents that act on a user's behalf through command-line interface (CLI) harnesses. However, most agent benchmarks still…

cs.CL2026

ClinConsensus: A Physician-Calibrated Benchmark for Evaluating Clinical Rubric Coverage in Chinese Medical LLMs

Xiang Zheng, Han Li, Wenjie Luo +15

Open-ended medical LLM evaluation remains weakly grounded in physician-calibrated coverage of clinically relevant response criteria, especially in localized clinical settings. We i…

cs.CL2026

EMemBench: Interactive Benchmarking of Episodic Memory for VLM Agents

Xinze Li, Ziyue Zhu, Siyuan Liu +4

We introduce EMemBench, a programmatic benchmark generator for evaluating long-term episodic memory of agents through interactive games. Rather than using a fixed set of questions,…