83 citations · 242 across the 62 of their papers we have counts for
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WavefrontDiffusion: Dynamic Decoding Schedule for Improved Reasoning
Haojin Yang, Rui Hu, Zequn Sun +3
Diffusion Language Models (DLMs) have shown strong potential for text generation and are becoming a competitive alternative to autoregressive models. The denoising strategy plays a…
AudioMotionBench: Evaluating Auditory Motion Perception in Audio LLMs
Zhe Sun, Yujun Cai, Jiayu Yao +1
Large Audio-Language Models (LALMs) have recently shown impressive progress in speech recognition, audio captioning, and auditory question answering. Yet, whether these models can…
PAS: A Training-Free Stabilizer for Temporal Encoding in Video LLMs
Bowen Sun, Yujun Cai, Ming-Hsuan Yang +2
Video LLMs suffer from temporal inconsistency: small shifts in frame timing can flip attention and suppress relevant frames. We trace this instability to the common extension of Ro…
Vision Language Models Map Logos to Text via Semantic Entanglement in the Visual Projector
Sifan Li, Hongkai Chen, Yujun Cai +4
Vision Language Models (VLMs) have achieved impressive progress in multimodal reasoning; yet, they remain vulnerable to hallucinations, where outputs are not grounded in visual evi…
FrameMind: Frame-Interleaved Video Reasoning via Reinforcement Learning
Haonan Ge, Yiwei Wang, Kai-Wei Chang +2
Current video understanding models rely on fixed frame sampling strategies, processing predetermined visual inputs regardless of the specific reasoning requirements of each questio…
RefineShot: Rethinking Cinematography Understanding with Foundational Skill Evaluation
Hang Wu, Yujun Cai, Haonan Ge +3
Cinematography understanding refers to the ability to recognize not only the visual content of a scene but also the cinematic techniques that shape narrative meaning. This capabili…
A Survey of Vibe Coding with Large Language Models
Yuyao Ge, Lingrui Mei, Zenghao Duan +12
The advancement of large language models (LLMs) has catalyzed a paradigm shift from code generation assistance to autonomous coding agents, enabling a novel development methodology…
ChainMPQ: Interleaved Text-Image Reasoning Chains for Mitigating Relation Hallucinations
Yike Wu, Yiwei Wang, Yujun Cai
While Large Vision-Language Models (LVLMs) achieve strong performance in multimodal tasks, hallucinations continue to hinder their reliability. Among the three categories of halluc…
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…
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…
Cure or Poison? Embedding Instructions Visually Alters Hallucination in Vision-Language Models
Zhaochen Wang, Yiwei Wang, Yujun Cai
Vision-Language Models (VLMs) often suffer from hallucination, partly due to challenges in aligning multimodal information. We propose Prompt-in-Image, a simple method that embeds…
Blockwise SFT for Diffusion Language Models: Reconciling Bidirectional Attention and Autoregressive Decoding
Bowen Sun, Yujun Cai, Ming-Hsuan Yang +1
Discrete diffusion language models have shown strong potential for text generation, yet standard supervised fine-tuning (SFT) misaligns with their semi-autoregressive inference: tr…
MRFD: Multi-Region Fusion Decoding with Self-Consistency for Mitigating Hallucinations in LVLMs
Haonan Ge, Yiwei Wang, Ming-Hsuan Yang +1
Large Vision-Language Models (LVLMs) have shown strong performance across multimodal tasks. However, they often produce hallucinations -- text that is inconsistent with visual inpu…
A Survey of Context Engineering for Large Language Models
Lingrui Mei, Jiayu Yao, Yuyao Ge +12
The performance of Large Language Models (LLMs) is fundamentally determined by the contextual information provided during inference. This survey introduces Context Engineering, a f…
Symbolic or Numerical? Understanding Physics Problem Solving in Reasoning LLMs
Nifu Dan, Yujun Cai, Yiwei Wang
Navigating the complexities of physics reasoning has long been a difficult task for Large Language Models (LLMs), requiring a synthesis of profound conceptual understanding and ade…
: 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…
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…
DiMo-GUI: Advancing Test-time Scaling in GUI Grounding via Modality-Aware Visual Reasoning
Hang Wu, Hongkai Chen, Yujun Cai +4
Grounding natural language queries in graphical user interfaces (GUIs) poses unique challenges due to the diversity of visual elements, spatial clutter, and the ambiguity of langua…
Answer-Centric or Reasoning-Driven? Uncovering the Latent Memory Anchor in LLMs
Yang Wu, Yifan Zhang, Yiwei Wang +5
While Large Language Models (LLMs) demonstrate impressive reasoning capabilities, growing evidence suggests much of their success stems from memorized answer-reasoning patterns rat…
BRIGHT+: Upgrading the BRIGHT Benchmark with MARCUS, a Multi-Agent RAG Clean-Up Suite
Liyang Chen, Yujun Cai, Jieqiong Dong +1
Retrieval-Augmented Generation (RAG) systems require corpora that are both structurally clean and semantically coherent. BRIGHT is a recent and influential benchmark designed to ev…
SemVink: Advancing VLMs' Semantic Understanding of Optical Illusions via Visual Global Thinking
Sifan Li, Yujun Cai, Yiwei Wang
Vision-language models (VLMs) excel in semantic tasks but falter at a core human capability: detecting hidden content in optical illusions or AI-generated images through perceptual…
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…
Token-Efficient Prompt Injection Attack: Provoking Cessation in LLM Reasoning via Adaptive Token Compression
Yu Cui, Yujun Cai, Yiwei Wang
While reasoning large language models (LLMs) demonstrate remarkable performance across various tasks, they also contain notable security vulnerabilities. Recent research has uncove…
Do "New Snow Tablets" Contain Snow? Large Language Models Over-Rely on Names to Identify Ingredients of Chinese Drugs
Sifan Li, Yujun Cai, Bryan Hooi +2
Traditional Chinese Medicine (TCM) has seen increasing adoption in healthcare, with specialized Large Language Models (LLMs) emerging to support clinical applications. A fundamenta…