83 citations · 242 across the 62 of their papers we have counts for
64 papers
UA-Bench: Benchmarking Large Audio-Language Models on Underwater Acoustic Recognition
Zhe Sun, Liang An, Jiayu Yao +9
Large audio-language models (LALMs) are fast becoming a general interface to sound, yet how far their broad pretraining carries into specialized domains remains largely open. Vesse…
Thinking with Anchors: Grounded and Efficient Document Reasoning
Sichen Zhu, Yuchen Zhu, Wenzhuo Xu +13
Existing document understanding benchmarks have largely focused on locating page elements, yet real-world document intelligence requires models to reason jointly about region seman…
Lost in a Single Vector: Improving Long-Document Retrieval with Chunk Evidence Aggregation
Shanshan Lyu, Yiwei Wang, Yujun Cai +2
Dense retrieval ranks one query vector against one document vector. On long documents, this interface can fail when a short but decisive span is weakened during document encoding b…
Dynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models
Boyan Han, Yiwei Wang, Yi Song +2
Diffusion large language models (dLLMs) offer bidirectional attention and parallel generation, enabling them to exploit global context and naturally support format-constrained task…
Semantic-Aware Adaptive Visual Memory for Streaming Video Understanding
Hang Wu, Sherin Mary Mathews, Yujun Cai +2
Online streaming video understanding requires models to process continuous visual inputs and respond to user queries in real time, where the unbounded stream and unpredictable quer…
VideoStir: Understanding Long Videos via Spatio-Temporally Structured and Intent-Aware RAG
Honghao Fu, Miao Xu, Yiwei Wang +3
Scaling multimodal large language models (MLLMs) to long videos is constrained by limited context windows. While retrieval-augmented generation (RAG) is a promising remedy by organ…
Hierarchical, Interpretable, Label-Free Concept Bottleneck Model
Haodong Xie, Yujun Cai, Rahul Singh Maharjan +3
Concept Bottleneck Models (CBMs) introduce interpretability to black-box deep learning models by predicting labels through human-understandable concepts. However, unlike humans, wh…
Finding Distributed Object-Centric Properties in Self-Supervised Transformers
Samyak Rawlekar, Amitabh Swain, Yujun Cai +3
Self-supervised Vision Transformers (ViTs) like DINO show an emergent ability to discover objects, typically observed in [CLS] token attention maps of the final layer. However, the…
HighlightBench: Benchmarking Markup-Driven Table Reasoning in Scientific Documents
Lexin Wang, Shenghua Liu, Yiwei Wang +5
Visual markups such as highlights, underlines, and bold text are common in table-centric documents. Although multimodal large language models (MLLMs) have made substantial progress…
CamReasoner: Reinforcing Camera Movement Understanding via Structured Spatial Reasoning
Hang Wu, Yujun Cai, Zehao Li +4
Understanding camera dynamics is a fundamental pillar of video spatial intelligence. However, existing multimodal models predominantly treat this task as a black-box classification…
Self-Manager: Parallel Agent Loop for Long-form Deep Research
Yilong Xu, Zhi Zheng, Xiang Long +2
Long-form deep research requires multi-faceted investigations over extended horizons to get a comprehensive report. When handling such complex tasks, existing agents manage context…
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…