collaborators

17 papers

cs.CL2026

Rethinking On-policy Optimization for Query Augmentation

Zhichao Xu, Shengyao Zhuang, Xueguang Ma +6

Recent advances in large language models (LLMs) have led to a surge of interest in query augmentation for information retrieval (IR). Two main approaches have emerged. The first pr…

cs.CV2026

HiPrune: Hierarchical Attention for Efficient Token Pruning in Vision-Language Models

Jizhihui Liu, Feiyi Du, Guangdao Zhu +5

Vision-Language Models (VLMs) encode images and videos into abundant tokens, which contain substantial redundancy and computation cost. While visual token pruning mitigates the iss…

cs.AI2026

UI-AGILE: Advancing GUI Agents with Effective Reinforcement Learning and Precise Inference-Time Grounding

Shuquan Lian, Yuhang Wu, Jia Ma +6

The emergence of Multimodal Large Language Models (MLLMs) has driven significant advances in Graphical User Interface (GUI) agent capabilities. Nevertheless, existing GUI agent tra…

cs.LG2026

GLM-5: from Vibe Coding to Agentic Engineering

GLM-5-Team, :, Aohan Zeng +184

We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering. Building upon the agentic, reasoning, and coding (AR…

cs.CV2026

REVEALER: Reinforcement-Guided Visual Reasoning for Element-Level Text-Image Alignment Evaluation

Fulin Shi, Wenyi Xiao, Bin Chen +2

Evaluating the alignment between textual prompts and generated images is critical for ensuring the reliability and usability of text-to-image (T2I) models. However, most existing e…

cs.LG2026

How Implicit Bias Accumulates and Propagates in LLM Long-term Memory

Yiming Ma, Lixu Wang, Lionel Z. Wang +6

Long-term memory mechanisms enable Large Language Models (LLMs) to maintain continuity and personalization across extended interaction lifecycles, but they also introduce new and u…