collaborators

6 papers

cs.CL2026

Beyond Reward Engineering: A Data Recipe for Long-Context Reinforcement Learning

Xiaoyue Xu, Sikui Zhang, Xiaorong Wang +2

Long-context reasoning is an essential capability for large language models, particularly when they are deployed as autonomous agents that must reason over lengthy trajectories. Re…

cs.CL2026

MiniCPM-SALA: Hybridizing Sparse and Linear Attention for Efficient Long-Context Modeling

MiniCPM Team, Wenhao An, Yingfa Chen +44

The evolution of large language models (LLMs) towards applications with ultra-long contexts faces challenges posed by the high computational and memory costs of the Transformer arc…

cs.AI2026

AgentCPM-Report: Interleaving Drafting and Deepening for Open-Ended Deep Research

Yishan Li, Wentong Chen, Yukun Yan +12

Generating deep research reports requires large-scale information acquisition and the synthesis of insight-driven analysis, posing a significant challenge for current language mode…

cs.CL2026

LLMMapReduce-V3: Enabling Interactive In-Depth Survey Generation through a MCP-Driven Hierarchically Modular Agent System

Yu Chao, Siyu Lin, xiaorong wang +7

We introduce LLM x MapReduce-V3, a hierarchically modular agent system designed for long-form survey generation. Building on the prior work, LLM x MapReduce-V2, this version incorp…

cs.CL2025

Monocle: Hybrid Local-Global In-Context Evaluation for Long-Text Generation with Uncertainty-Based Active Learning

Xiaorong Wang, Ting Yang, Zhu Zhang +5

Assessing the quality of long-form, model-generated text is challenging, even with advanced LLM-as-a-Judge methods, due to performance degradation as input length increases. To add…

cs.CL2025

LLMMapReduce-V2: Entropy-Driven Convolutional Test-Time Scaling for Generating Long-Form Articles from Extremely Long Resources

Haoyu Wang, Yujia Fu, Zhu Zhang +8

Long-form generation is crucial for a wide range of practical applications, typically categorized into short-to-long and long-to-long generation. While short-to-long generations ha…