collaborators

7 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.CL2026

Towards Pareto-Optimal Tool-Integrated Agents with Pareto Ranking Policy Optimization

Junyi Li, Xiaowei Qian, Yingyi Zhang +6

Recent advances in tool-integrated language agents have significantly improved their ability to solve complex reasoning tasks. However, existing alignment methods predominantly foc…

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

Chinese-SkillSpan: A Span-Level Dataset for ESCO-Aligned Competency Extraction from Chinese Job Ads

Guojing Li, Zichuan Fu, Junyi Li +6

Job Skill Named Entity Recognition (JobSkillNER) aims to automatically extract key skill information from large-scale job posting data, which is important for improving talent-mark…

cs.CL2026

Job Skill Extraction via LLM-Centric Multi-Module Framework

Guojing Li, Zichuan Fu, Junyi Li +8

Span-level skill extraction from job advertisements underpins candidate-job matching and labor-market analytics, yet generative large language models (LLMs) often yield malformed s…

cs.LG2026

Attention Needs to Focus: A Unified Perspective on Attention Allocation

Zichuan Fu, Wentao Song, Guojing Li +6

The Transformer architecture, a cornerstone of modern Large Language Models (LLMs), has achieved extraordinary success in sequence modeling, primarily due to its attention mechanis…