collaborators

16 papers

cs.CL2026

Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training

Shengrui Li, Fei Zhao, Kaiyan Zhao +6

Determining an effective data mixture is a key factor in Large Language Model (LLM) pre-training, where models must balance general competence with proficiency on hard tasks such a…

cs.LG2026

Robust Tool Use via Fission-GRPO: Learning to Recover from Execution Errors

Zhiwei Zhang, Fei Zhao, Rui Wang +6

Large language models (LLMs) can call tools effectively, yet they remain brittle in multi-turn execution: after a tool-call error, smaller models often fall into repetitive invalid…

cs.AI2026

GCAgent: Enhancing Group Chat Communication through Dialogue Agents System

Zijie Meng, Zheyong Xie, Zheyu Ye +5

As a key form in online social platforms, group chat is a popular space for interest exchange or problem-solving, but its effectiveness is often hindered by inactivity and manageme…

cs.CV2026

Vision-DeepResearch Benchmark: Rethinking Visual and Textual Search for Multimodal Large Language Models

Yu Zeng, Wenxuan Huang, Zhen Fang +14

Multimodal Large Language Models (MLLMs) have advanced VQA and now support Vision-DeepResearch systems that use search engines for complex visual-textual fact-finding. However, eva…

cs.IR2026

QP-OneModel: A Unified Generative LLM for Multi-Task Query Understanding in Xiaohongshu Search

Jianzhao Huang, Xiaorui Huang, Fei Zhao +9

Query Processing (QP) bridges user intent and content supply in large-scale Social Network Service (SNS) search engines. Traditional QP systems rely on pipelines of isolated discri…

cs.CL2026

Balancing Understanding and Generation in Discrete Diffusion Models

Yue Liu, Yuzhong Zhao, Zheyong Xie +5

In discrete generative modeling, two dominant paradigms demonstrate divergent capabilities: Masked Diffusion Language Models (MDLM) excel at semantic understanding and zero-shot ge…