16 citations · 29 across the 26 of their papers we have counts for
26 papers
OmniEcho: Audio-Visual Spatial Understanding for Omni-Modal Embodied Agents
Ruixun Liu, Yuxuan Wang, Jiacheng Xie +10
Humans can effortlessly localize the direction of a sound source and integrate it with visual cues for reasoning, yet this remains challenging for embodied agents. In particular, i…
Native Active Perception as Reasoning for Omni-Modal Understanding
Zhenghao Xing, Ruiyang Xu, Yuxuan Wang +8
Passive models for long video understanding typically rely on a "watch-it-all" paradigm, processing frames uniformly regardless of query difficulty, causing computational cost to g…
Qwen3-VL Technical Report
Shuai Bai, Yuxuan Cai, Ruizhe Chen +61
We introduce Qwen3-VL, the most capable vision-language model in the Qwen series to date, achieving superior performance across a broad range of multimodal benchmarks. It natively…
Omni-Captioner: Data Pipeline, Models, and Benchmark for Omni Detailed Perception
Ziyang Ma, Ruiyang Xu, Zhenghao Xing +9
Fine-grained perception of multimodal information is critical for advancing human-AI interaction. With recent progress in audio-visual technologies, Omni Language Models (OLMs), ca…
OmniVideoBench: Towards Audio-Visual Understanding Evaluation for Omni MLLMs
Caorui Li, Yu Chen, Yiyan Ji +40
Recent advances in multimodal large language models (MLLMs) have demonstrated substantial potential in video understanding. However, existing benchmarks fail to comprehensively eva…
Beyond Isolated Facts: Synthesizing Narrative and Grounded Supervision for VideoQA
Jianxin Liang, Tan Yue, Yuxuan Wang +4
The performance of Video Question Answering (VideoQA) models is fundamentally constrained by the nature of their supervision, which typically consists of isolated, factual question…
Qwen3-Omni Technical Report
Jin Xu, Zhifang Guo, Hangrui Hu +35
We present Qwen3-Omni, a single multimodal model that, for the first time, maintains state-of-the-art performance across text, image, audio, and video without any degradation relat…
SurgVLM: A Large Vision-Language Model and Systematic Evaluation Benchmark for Surgical Intelligence
Zhitao Zeng, Zhu Zhuo, Xiaojun Jia +12
Foundation models have achieved transformative success across biomedical domains by enabling holistic understanding of multimodal data. However, their application in surgery remain…
Seek in the Dark: Reasoning via Test-Time Instance-Level Policy Gradient in Latent Space
Hengli Li, Chenxi Li, Tong Wu +8
Reasoning ability, a core component of human intelligence, continues to pose a significant challenge for Large Language Models (LLMs) in the pursuit of AGI. Although model performa…
Probing and Inducing Combinational Creativity in Vision-Language Models
Yongqian Peng, Yuxi Ma, Mengmeng Wang +5
The ability to combine existing concepts into novel ideas stands as a fundamental hallmark of human intelligence. Recent advances in Vision-Language Models (VLMs) like GPT-4V and D…
OmniMMI: A Comprehensive Multi-modal Interaction Benchmark in Streaming Video Contexts
Yuxuan Wang, Yueqian Wang, Bo Chen +3
The rapid advancement of multi-modal language models (MLLMs) like GPT-4o has propelled the development of Omni language models, designed to process and proactively respond to conti…
TokenSwift: Lossless Acceleration of Ultra Long Sequence Generation
Tong Wu, Junzhe Shen, Zixia Jia +2
Generating ultra-long sequences with large language models (LLMs) has become increasingly crucial but remains a highly time-intensive task, particularly for sequences up to 100K to…
LongViTU: Instruction Tuning for Long-Form Video Understanding
Rujie Wu, Xiaojian Ma, Hai Ci +5
This paper introduces LongViTU, a large-scale (~121k QA pairs, ~900h videos), automatically generated dataset for long-form video understanding. We propose a systematic approach th…
Friends-MMC: A Dataset for Multi-modal Multi-party Conversation Understanding
Yueqian Wang, Xiaojun Meng, Yuxuan Wang +3
Multi-modal multi-party conversation (MMC) is a less studied yet important topic of research due to that it well fits real-world scenarios and thus potentially has more widely-used…
VideoLLM Knows When to Speak: Enhancing Time-Sensitive Video Comprehension with Video-Text Duet Interaction Format
Yueqian Wang, Xiaojun Meng, Yuxuan Wang +4
Recent researches on video large language models (VideoLLM) predominantly focus on model architectures and training datasets, leaving the interaction format between the user and th…
Understanding Multimodal Hallucination with Parameter-Free Representation Alignment
Yueqian Wang, Jianxin Liang, Yuxuan Wang +2
Hallucination is a common issue in Multimodal Large Language Models (MLLMs), yet the underlying principles remain poorly understood. In this paper, we investigate which components…
ExoViP: Step-by-step Verification and Exploration with Exoskeleton Modules for Compositional Visual Reasoning
Yuxuan Wang, Alan Yuille, Zhuowan Li +1
Compositional visual reasoning methods, which translate a complex query into a structured composition of feasible visual tasks, have exhibited a strong potential in complicated mul…
VideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Models
Yuxuan Wang, Yueqian Wang, Dongyan Zhao +2
Recent advancements in Multimodal Large Language Models (MLLMs) have extended their capabilities to video understanding. Yet, these models are often plagued by "hallucinations", wh…
HawkEye: Training Video-Text LLMs for Grounding Text in Videos
Yueqian Wang, Xiaojun Meng, Jianxin Liang +3
Video-text Large Language Models (video-text LLMs) have shown remarkable performance in answering questions and holding conversations on simple videos. However, they perform almost…
Efficient Temporal Extrapolation of Multimodal Large Language Models with Temporal Grounding Bridge
Yuxuan Wang, Yueqian Wang, Pengfei Wu +4
Despite progress in multimodal large language models (MLLMs), the challenge of interpreting long-form videos in response to linguistic queries persists, largely due to the ineffici…
STAIR: Spatial-Temporal Reasoning with Auditable Intermediate Results for Video Question Answering
Yueqian Wang, Yuxuan Wang, Kai Chen +1
Recently we have witnessed the rapid development of video question answering models. However, most models can only handle simple videos in terms of temporal reasoning, and their pe…
Teaching Text-to-Image Models to Communicate in Dialog
Xiaowen Sun, Jiazhan Feng, Yuxuan Wang +3
A picture is worth a thousand words, thus, it is crucial for conversational agents to understand, perceive, and effectively respond with pictures. However, we find that directly em…
MoviePuzzle: Visual Narrative Reasoning through Multimodal Order Learning
Jianghui Wang, Yuxuan Wang, Dongyan Zhao +1
We introduce MoviePuzzle, a novel challenge that targets visual narrative reasoning and holistic movie understanding. Despite the notable progress that has been witnessed in the re…
Shuo Wen Jie Zi: Rethinking Dictionaries and Glyphs for Chinese Language Pre-training
Yuxuan Wang, Jianghui Wang, Dongyan Zhao +1
We introduce CDBERT, a new learning paradigm that enhances the semantics understanding ability of the Chinese PLMs with dictionary knowledge and structure of Chinese characters. We…