60 citations · 127 across the 20 of their papers we have counts for
11 papers · 1 filter
Beyond Watching and Searching: Benchmarking Agents for Video-centered Deep Research Reports
Jiahao Meng, Qize Yang, Yuxuan Wang +4
Deep research agents synthesize open-web evidence into long reports, but current benchmarks do not evaluate research centered on a source video. We introduce Video-Centered Deep Re…
VisionWeave: Weaving Elastic Visual Representations as a Native Capability of MLLMs
Yuan Feng, Qize Yang, Ruizhe Chen +9
Multimodal large language models have become the dominant paradigm for visual understanding, but incur substantial costs by encoding inputs into dense, fixed-size patch tokens. How…
MMPostTrainBench: Benchmarking Autonomous Research for Multimodal Post-Training
Yuxin Liu, Yuxuan Wang, Zhenxin Lei +9
Autonomous research seeks sustained model improvements through iterative experimentation and feedback. LLM agents show promise in automating machine learning and language-model pos…
OmniReasoning: Pushing the Limits of Audio-Visual Joint Reasoning
Junming Lin, Yuxuan Wang, Zhenxin Lei +11
Recent advances have enabled unified omni-modal models in understanding audio, vision, and language. However, existing benchmarks, training data, and learning methods largely treat…
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…
Omni2Web: Benchmarking Audiovisual Website Development
Minghao Han, Zhenghao Xing, Xize Cheng +7
Screen-recorded web editing requests contain weak deictic expressions such as ``this'' and ``there,'' whose referents depend on speech, cursor trajectories, page state, and edit hi…
OmniVChat: Synthesizing, Benchmarking, and Training for Native Audio-Visual Dialogue
Haolin He, Yunfei Chu, Qi Chen +15
We define OmniVChat (Omni Video Chat) as the task of native audio-visual dialogue between a user and an omni model. In OmniVChat, omni models directly and simultaneously receive au…
Omni Demand Understanding: A Benchmark for Contextual User-Intent Inference in Multimodal Interaction
Qi Chen, Yunfei Chu, Haolin He +15
Natural audio-visual interaction is emerging as an important interface for AI assistants, allowing users to communicate through speech and vision rather than carefully composed tex…
LongAudioSpan: Spanning the Duration and Depth of Audio Comprehension
Wen Huang, Yunfei Chu, Meng Gao +2
General audio comprehension now covers speech, sound, and music over durations from seconds to hours, driven by large audio-language models (LALMs) that are increasingly omni-modal…
Qwen-Music Technical Report
Jin Xu, Kangdi Wang, Ruibin Yuan +24
We introduce Qwen-Music, a music generation model that produces high-fidelity songs with complete vocals. It supports text-to-music generation from descriptions, lyrics, and musica…
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…