activity
20242026
collaborators

21 papers

cs.CV2026

GUI-Lens: Coarse-to-Fine Cropping for GUI Grounding with General-Purpose VLMs

Zichuan Fu, Shirong Wang, Wenlin Zhang +10

GUI grounding maps natural-language instructions to click locations and is essential for reliable GUI agents. The task remains difficult on high-resolution, densely populated inter…

cs.AI2026

Bridging Auxiliary Constraints to Resolve Instruction Following in Large Reasoning Models

Zhengyi Zhao, Shubo Zhang, Huimin Wang +7

Large Reasoning Models (LRMs) have demonstrated impressive capabilities in many tasks, yet they struggle with reliably following multiple instructions, either by failing to satisfy…

cs.CL2026

MultiDx: A Multi-Source Knowledge Integration Framework towards Diagnostic Reasoning

Yimin Deng, Zhenxi Lin, Yejing Wang +9

Diagnostic prediction and clinical reasoning are critical tasks in healthcare applications. While Large Language Models (LLMs) have shown strong capabilities in commonsense reasoni…

cs.CL2026

AdapTime: Enabling Adaptive Temporal Reasoning in Large Language Models

Yimin Deng, Yejing Wang, Zhenxi Lin +8

Large language models have demonstrated strong reasoning capabilities in general knowledge question answering. However, their ability to handle temporal information remains limited…

cs.AI2026

Tandem: Riding Together with Large and Small Language Models for Efficient Reasoning

Zichuan Fu, Xian Wu, Guojing Li +7

Recent advancements in large language models (LLMs) have catalyzed the rise of reasoning-intensive inference paradigms, where models perform explicit step-by-step reasoning before…

cs.CL2026

Guaranteeing Knowledge Integration with Joint Decoding for Retrieval-Augmented Generation

Zhengyi Zhao, Shubo Zhang, Zezhong Wang +7

Retrieval-Augmented Generation (RAG) significantly enhances Large Language Models (LLMs) by providing access to external knowledge. However, current research primarily focuses on r…