most citedA Call for Collaborative Intelligence: Why Human-Agent Systems Should Precede AI Autonomy

1 citations · 1 across the 2 of their papers we have counts for

collaborators

9 papers

cs.CL2025

RECODE-H: A Benchmark for Research Code Development with Interactive Human Feedback

Chunyu Miao, Henry Peng Zou, Yangning Li +28

Large language models (LLMs) show the promise in supporting scientific research implementation, yet their ability to generate correct and executable code remains limited. Existing…

cs.CL2025

Deep Research with Open-Domain Evaluation and Multi-Stage Guardrails for Safety

Wei-Chieh Huang, Henry Peng Zou, Yaozu Wu +12

Deep research frameworks have shown promising capabilities in synthesizing comprehensive reports from web sources. While deep research possesses significant potential to address co…

cs.CL2025

MADIAVE: Multi-Agent Debate for Implicit Attribute Value Extraction

Wei-Chieh Huang, Cornelia Caragea

Implicit Attribute Value Extraction (AVE) is essential for accurately representing products in e-commerce, as it infers latent attributes from multimodal data. Despite advances in…

cs.AI2025

PSG-Agent: Personality-Aware Safety Guardrail for LLM-based Agents

Yaozu Wu, Jizhou Guo, Dongyuan Li +9

Effective guardrails are essential for safely deploying LLM-based agents in critical applications. Despite recent advances, existing guardrails suffer from two fundamental limitati…

cs.CL2025

Teaching According to Talents! Instruction Tuning LLMs with Competence-Aware Curriculum Learning

Yangning Li, Tingwei Lu, Yinghui Li +6

Efficient instruction tuning aims to enhance the ultimate performance of large language models (LLMs) trained on a given instruction dataset. Curriculum learning as a typical data…

cs.CL2025

Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs

Yangning Li, Weizhi Zhang, Yuyao Yang +17

Retrieval-Augmented Generation (RAG) lifts the factuality of Large Language Models (LLMs) by injecting external knowledge, yet it falls short on problems that demand multi-step inf…