activity
20242026
most citedEnhancing LLM Character-Level Manipulation via Divide and Conquer

1 citations · 1 across the 10 of their papers we have counts for

collaborators

14 papers

cs.CL2026

DiffuPlan: Editable Planning State for Diffusion Language Model Agents

Qisheng Zhou, Zhen Xiong, Qiaoyu Tan

Diffusion language models (dLLMs) are emerging as an alternative to autoregressive (AR) language models, yet dLLM agents largely inherit an interaction protocol designed for AR gen…

cs.LG2026

TRACE: Trajectory Selection for Parallel Scaling of Search Agents

Qisheng Zhou, Zhen Xiong, Qiaoyu Tan

Parallel search may generate a correct answer that final-answer voting fails to select. We formulate this consolidation stage as trajectory selection and introduce TRACE (Trajector…

cs.AI2026

EASE: Behavior-Adaptive Skill Curation for Self-Evolving Agents

Zhen Xiong, Qiaoyu Tan

Agent skills provide a lightweight mechanism for self-evolving agents to accumulate reusable procedural knowledge without updating model parameters. However, existing learned skill…

cs.SE2026

AsynCodeBench: Benchmarking Collaboration of Asynchronous Multi-Agent Systems in Software Engineering

Kaituo Zhang, Zhen Xiong, Zhimeng Jiang +8

Multi-agent coding has emerged as an increasingly active direction in software engineering, where complex development tasks are decomposed across multiple specialized agents workin…

cs.AI2026

Are Tools All We Need? Unveiling the Tool-Use Tax in LLM Agents

Kaituo Zhang, Zhen Xiong, Mingyu Zhong +4

Tool-augmented reasoning has become a popular direction for LLM-based agents, and it is widely assumed to improve reasoning and reliability. However, we demonstrate that this conse…

cs.CL2025

Not in Sync: Unveiling Temporal Bias in Audio Chat Models

Jiayu Yao, Shenghua Liu, Yiwei Wang +5

Large Audio Language Models (LALMs) are increasingly applied to audio understanding and multimodal reasoning, yet their ability to locate when events occur remains underexplored. W…

cs.CV2025

Generalist Scanner Meets Specialist Locator: A Synergistic Coarse-to-Fine Framework for Robust GUI Grounding

Zhecheng Li, Guoxian Song, Yiwei Wang +3

Grounding natural language queries in graphical user interfaces (GUIs) presents a challenging task that requires models to comprehend diverse UI elements across various application…

cs.CL2025

Thinking with Sound: Audio Chain-of-Thought Enables Multimodal Reasoning in Large Audio-Language Models

Zhen Xiong, Yujun Cai, Zhecheng Li +2

Recent Large Audio-Language Models (LALMs) have shown strong performance on various audio understanding tasks such as speech translation and Audio Q\&A. However, they exhibit signi…

cs.CV2025

: Advancing Img2LaTeX Conversion via Visual Reasoning with Attention-Guided Refinement

Zhecheng Li, Guoxian Song, Yiwei Wang +3

Img2LaTeX is a practically important task that involves translating mathematical expressions and structured visual content from images into LaTeX code. In recent years, vision-lang…

cs.CL2025

Unveiling the Potential of Diffusion Large Language Model in Controllable Generation

Zhen Xiong, Yujun Cai, Zhecheng Li +1

Controllable generation is a fundamental task in NLP with many applications, providing a basis for function calling to agentic communication. However, even state-of-the-art autoreg…

cs.CL2025

Mapping the Minds of LLMs: A Graph-Based Analysis of Reasoning LLM

Zhen Xiong, Yujun Cai, Zhecheng Li +1

Recent advances in test-time scaling have enabled Large Language Models (LLMs) to display sophisticated reasoning abilities via extended Chain-of-Thought (CoT) generation. Despite…

cs.CL2025★ 1 cited

Enhancing LLM Character-Level Manipulation via Divide and Conquer

Zhen Xiong, Yujun Cai, Bryan Hooi +3

Large Language Models (LLMs) have demonstrated strong generalization capabilities across a wide range of natural language processing (NLP) tasks. However, they exhibit notable weak…

cs.CL2025

Texture or Semantics? Vision-Language Models Get Lost in Font Recognition

Zhecheng Li, Guoxian Song, Yujun Cai +3

Modern Vision-Language Models (VLMs) exhibit remarkable visual and linguistic capabilities, achieving impressive performance in various tasks such as image recognition and object l…

cs.CL2024

Vulnerability of LLMs to Vertically Aligned Text Manipulations

Zhecheng Li, Yiwei Wang, Bryan Hooi +4

Vertical text input is commonly encountered in various real-world applications, such as mathematical computations and word-based Sudoku puzzles. While current large language models…