activity
20242026
collaborators

26 papers

cs.CL2026

Mining Useful General Data for Low-Resource Domain Adaptation

Pingjie Wang, Hongcheng Liu, Yusheng Liao +5

Adapting large language models (LLMs) to low-resource domains remains challenging due to the scarcity of domain-specific data. While in-domain data is limited, there exists a vast…

cs.AI2026

MCP-Persona: Benchmarking LLM Agents on Real-World Personal Applications via Environment Simulation

Wenhao Wang, Peizhi Niu, Gongyi Zou +9

The Model Context Protocol (MCP) has emerged as a transformative standard for connecting large language models (LLMs) with external data sources and tools, and has been rapidly ado…

cs.CL2026

LaSR: Context-Aware Speech Recognition via Latent Reasoning

Heyang Liu, Ziyang Cheng, Jiayi Huang +5

Recent advances in Speech Large Language Models (Speech LLMs) have significantly enhanced spoken language understanding and reasoning. However, their contextual awareness is limite…

cs.AI2026

Miner:Mining Intrinsic Mastery for Data-Efficient RL in Large Reasoning Models

Shuyang Jiang, Yuhao Wang, Ya Zhang +2

Current critic-free RL methods for large reasoning models suffer from severe inefficiency when training on positive homogeneous prompts (where all rollouts are correct), resulting…

cs.CL2026

HeteroRAG: A Heterogeneous Retrieval-Augmented Generation Framework for Medical Vision Language Tasks

Zhe Chen, Yusheng Liao, Zhiyuan Zhu +4

Medical large vision-language Models (Med-LVLMs) have shown promise in clinical applications but suffer from factual inaccuracies and unreliable outputs, posing risks in real-world…

cs.CL2026

Cross-Modal Coreference Alignment: Enabling Reliable Information Transfer in Omni-LLMs

Hongcheng Liu, Yuhao Wang, Zhe Chen +5

Omni Large Language Models (Omni-LLMs) have demonstrated impressive capabilities in holistic multi-modal perception, yet they consistently falter in complex scenarios requiring syn…