activity
20242026
most citedAgentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses

1 citations · 1 across the 25 of their papers we have counts for

collaborators
Showing cs.CLShow all

31 papers · 1 filter

cs.CL2026

SPIEval: Evaluating Large Language Models as Mobile Assistants over Scattered Personal Information

Junjie Ye, Zhuohui Sheng, Shaofan Liu +12

Large language models (LLMs) are increasingly deployed as mobile assistants, where a key challenge is leveraging personal information scattered across multiple applications (apps)…

cs.CL2026

IACM-RL: Intent-Aware Context Management and Reinforcement Learning for Complex Tool Invocation under Dynamic Intent Fluctuations

Dingwei Zhu, Jiahan Li, Chengjun Pan +22

Executing long-horizon tool invocations in real-world environments is severely challenged by dynamic user intent noise. Existing methods attempt robustness via implicit history sca…

cs.CL2026

Learning Query-Specific Rubrics from Human Preferences for DeepResearch Report Generation

Changze Lv, Jie Zhou, Wentao Zhao +12

Nowadays, developing reliable DeepResearch-style long-form report generation remains challenging, as training and evaluation lack verifiable reward signals. Accordingly, rubric-bas…

cs.CL2026

SciAgentGym: Benchmarking Multi-Step Scientific Tool-use in LLM Agents

Yujiong Shen, Yajie Yang, Zhiheng Xi +17

Scientific reasoning inherently demands integrating sophisticated toolkits to navigate domain-specific knowledge. Yet, current benchmarks largely overlook agents' ability to orches…

cs.CL2026

LLMEval-Logic: A Solver-Verified Chinese Benchmark for Logical Reasoning of LLMs with Adversarial Hardening

Ming Zhang, Qiyuan Peng, Yinxi Wei +13

Evaluating large language models (LLMs) on natural-language logical reasoning is essential because rule-governed tasks require conclusions to follow strictly from stated premises.…

cs.CL2026

Can Deep Research Agents Retrieve and Organize? Evaluating the Synthesis Gap with Expert Taxonomies

Ming Zhang, Jiabao Zhuang, Wenqing Jing +18

Deep Research Agents increasingly automate survey writing, yet existing benchmarks do not jointly test whether they retrieve the papers experts consider essential and organize thos…