collaborators

5 papers

cs.CL2026

Kwai Summary Attention Technical Report

Chenglong Chu, Guorui Zhou, Guowang Zhang +35

Long-context ability, has become one of the most important iteration direction of next-generation Large Language Models, particularly in semantic understanding/reasoning, code agen…

cs.CL2026

ReSum: Unlocking Long-Horizon Search Intelligence via Context Summarization

Xixi Wu, Kuan Li, Yida Zhao +13

Large Language Model (LLM)-based web agents excel at knowledge-intensive tasks but face a fundamental conflict between the need for extensive exploration and the constraints of lim…

cs.LG2026

Demystifying Reinforcement Learning for Long-Horizon Tool-Using Agents: A Comprehensive Recipe

Xixi Wu, Qianguo Sun, Ruiyang Zhang +4

Reinforcement Learning (RL) is essential for evolving Large Language Models (LLMs) into autonomous agents capable of long-horizon planning, yet a practical recipe for scaling RL in…

cs.CL2025

MoLoRAG: Bootstrapping Document Understanding via Multi-modal Logic-aware Retrieval

Xixi Wu, Yanchao Tan, Nan Hou +2

Document Understanding is a foundational AI capability with broad applications, and Document Question Answering (DocQA) is a key evaluation task. Traditional methods convert the do…

cs.LG2025

EvoFlow: Evolving Diverse Agentic Workflows On The Fly

Guibin Zhang, Kaijie Chen, Guancheng Wan +5

The past two years have witnessed the evolution of large language model (LLM)-based multi-agent systems from labor-intensive manual design to partial automation (\textit{e.g.}, pro…