OmniMMI: A Comprehensive Multi-modal Interaction Benchmark in Streaming Video Contexts
On the map: Multimodal LLMs / vision-language models → Video understanding with MLLMs
Abstract (arXiv)
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 continuous streams of multi-modal data. Despite their potential, evaluating their real-world interactive capabilities in streaming video contexts remains a formidable challenge. In this work, we introduce OmniMMI, a comprehensive multi-modal interaction benchmark tailored for OmniLLMs in streaming video contexts. OmniMMI encompasses over 1,121 videos and 2,290 questions, addressing two critical yet underexplored challenges in existing video benchmarks: streaming video understanding and proactive reasoning, across six distinct subtasks. Moreover, we propose a novel framework, Multi-modal Multiplexing Modeling (M4), designed to enable an inference-efficient streaming model that can see, listen while generating.
Key facts. Cited by 48 papers in the map (data through 7 Oct 2026). Placed in Video understanding with MLLMs, one of 16 directions in Multimodal LLMs / vision-language models. Builds on 49 of its 61 references that are in the map. First posted on arXiv 29 Mar 2025.
Builds on
49 of 61 references.
Closest ancestors · 13
Same direction, newest first
- 2024StreamingBench: Assessing the Gap for MLLMs to Achieve Streaming Video Understanding6 Nov
- 2024Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding22 Sep
- 2024LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via a Hybrid Architecture4 Sep
- 2024LongVILA: Scaling Long-Context Visual Language Models for Long Videos19 Aug
- 2024LongVideoBench: A Benchmark for Long-context Interleaved Video-Language Understanding22 Jul
- 2024Long Context Transfer from Language to Vision24 Jun
- 2024Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis31 May
- 2024PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning25 Apr
- 2024MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding8 Apr
- 2024MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens4 Apr
- 2023LLaMA-VID: An Image is Worth 2 Tokens in Large Language Models28 Nov
- 2023MVBench: A Comprehensive Multi-modal Video Understanding Benchmark28 Nov
Other references · 36
- 2024GPT-4o System Cardcited by 4,467
- 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,151
- 2021Ego4D: Around the World in 3,000 Hours of Egocentric Videocited by 1,530
- 2023Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Modelscited by 1,047
- 2024Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Headscited by 821
- 2024VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMscited by 749
- 2021NExT-QA:Next Phase of Question-Answering to Explaining Temporal Actionscited by 735
- 2023EgoSchema: A Diagnostic Benchmark for Very Long-form Video Language Understandingcited by 666
- 2024LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Modelscited by 571
- 2019ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answeringcited by 559
- 2024Qwen2-Audio Technical Reportcited by 543
- 2024Moshi: a speech-text foundation model for real-time dialoguecited by 536
24 more
- 2024ShareGPT4Video: Improving Video Understanding and Generation with Better Captionscited by 386
- 2017TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answeringcited by 378
- 2019COIN: A Large-scale Dataset for Comprehensive Instructional Video Analysiscited by 316
- 2024Break the Sequential Dependency of LLM Inference Using Lookahead Decodingcited by 295
- 2024VideoLLM-online: Online Video Large Language Model for Streaming Videocited by 216
- 2024STAR: A Benchmark for Situated Reasoning in Real-World Videoscited by 213
- 2024MANTIS: Interleaved Multi-Image Instruction Tuningcited by 212
- 2024Mini-Omni: Language Models Can Hear, Talk While Thinking in Streamingcited by 204
- 2024VITA: Towards Open-Source Interactive Omni Multimodal LLMcited by 172
- 2024Streaming Long Video Understanding with Large Language Modelscited by 164
- 2025OVO-Bench: How Far is Your Video-LLMs from Real-World Online Video Understanding?cited by 134
- 2023Video-Bench: A Comprehensive Benchmark and Toolkit for Evaluating Video-based Large Language Modelscited by 107
- 2024OmniBench: Towards The Future of Universal Omni-Language Modelscited by 100
- 2024VideoHallucer: Evaluating Intrinsic and Extrinsic Hallucinations in Large Video-Language Modelscited by 88
- 2024Streaming Dense Video Captioningcited by 82
- 2024Language Model Can Listen While Speakingcited by 62
- 2023Shot2Story: A New Benchmark for Comprehensive Understanding of Multi-shot Videoscited by 54
- 2024Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Modelscited by 53
- 2024Grounded Multi-Hop VideoQA in Long-Form Egocentric Videoscited by 43
- 2024Beyond the Turn-Based Game: Enabling Real-Time Conversations with Duplex Modelscited by 26
- 2024Ouroboros: Generating Longer Drafts Phrase by Phrase for Faster Speculative Decodingcited by 25
- 2022DataMUX: Data Multiplexing for Neural Networkscited by 18
- 2023Streaming Video Modelcited by 10
- 2024Enabling Real-Time Conversations with Minimal Training Costscited by 6
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Citing papers per year: 2025: 7; 2026: 41.
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- 2026TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videoscited by 1
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- 2026Omni Demand Understanding: A Benchmark for Contextual User-Intent Inference in Multimodal Interaction18 Sep 2026
- 2026LiveProBench: Can Streaming Video Models Really Interact Like Humans?11 Sep 2026
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- 2026OmniAssistBench: Assistant-style Interaction Benchmark for Omni-LLMs21 Aug 2026
- 2026Multi-turn Conversational AI from Text to Multimodal Interaction: Data, Models, Evaluation, and Open Challenges18 Aug 2026
- 2026MOSS-VL Technical Report15 Aug 2026
- 2026StreamTTT: Reconciling Real-Time Perception and Long-Term Memory in Streaming VLMs13 Aug 2026
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- 2026Agentic Active Omni-Modal Perception for Multi-Hop Audio-Visual Reasoning27 May 2026
- 2026IPIBench: Evaluating Interactive Proactive Intelligence of MLLMs under Continuous Streams26 May 2026
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- 2026Omni-DuplexEval: Evaluating Real-time Duplex Omni-modal Interaction17 May 2026
- 2026StreamPro: From Reactive Perception to Proactive Decision-Making in Streaming Video11 May 2026
- 2026TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos8 May 2026
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- 2026SiMing-Bench: Evaluating Procedural Correctness from Continuous Interactions in Clinical Skill Videos10 Apr 2026
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- 2026PhoStream: Benchmarking Real-World Streaming for Omnimodal Assistants in Mobile Scenarios30 Jan 2026
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- 2025Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Models6 Oct 2025
- 2025Chat with AI: The Surprising Turn of Real-time Video Communication from Human to AI14 Jul 2025
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- 2025StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant8 May 2025
- 2025Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models8 May 2025
- 2026PhoStream: Benchmarking Real-World Streaming for Omnimodal Assistants in Mobile Scenarioscited by 10
- 2026ROMA: Real-time Omni-Multimodal Assistant with Interactive Streaming Understandingcited by 5
- 2026MOSS-VL Technical Reportcited by 5
- 2026LifeEval: A Multimodal Benchmark for Assistive AI in Egocentric Daily Life Taskscited by 4
- 2026IPIBench: Evaluating Interactive Proactive Intelligence of MLLMs under Continuous Streamscited by 4
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- 2025Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance?cited by 2
- 2026EgoSAT: A Comprehensive Benchmark of Egocentric Streaming Interaction Understandingcited by 2
- 2026EgoPro-Bench: Benchmarking Personalized Proactive Interaction in Egocentric Video Streamscited by 1
- 2026GuideMe: Multi-Domain Task Guidance and Intervention in Streaming Videocited by 1
- 2025Temporally-Grounded Language Generation: Towards Real-Time Vision-Language Modelscited by 0
- 2026SiMing-Bench: Evaluating Procedural Correctness from Continuous Interactions in Clinical Skill Videoscited by 0
- 2026MOSS-VL Technical Report15 Aug 2026
- 2026GuideMe: Multi-Domain Task Guidance and Intervention in Streaming Video3 Jul 2026
- 2026EgoSAT: A Comprehensive Benchmark of Egocentric Streaming Interaction Understanding23 Jun 2026
- 2026Harnessing Streaming Video in the Wild7 Jun 2026
- 2026IPIBench: Evaluating Interactive Proactive Intelligence of MLLMs under Continuous Streams26 May 2026
- 2026EgoPro-Bench: Benchmarking Personalized Proactive Interaction in Egocentric Video Streams8 May 2026
- 2026SiMing-Bench: Evaluating Procedural Correctness from Continuous Interactions in Clinical Skill Videos10 Apr 2026
- 2026LifeEval: A Multimodal Benchmark for Assistive AI in Egocentric Daily Life Tasks28 Feb 2026
- 2026PhoStream: Benchmarking Real-World Streaming for Omnimodal Assistants in Mobile Scenarios30 Jan 2026
- 2026ROMA: Real-time Omni-Multimodal Assistant with Interactive Streaming Understanding15 Jan 2026
- 2025Can Multi-Modal LLMs Provide Live Step-by-Step Task Guidance?27 Nov 2025
- 2025Temporally-Grounded Language Generation: Towards Real-Time Vision-Language Models16 May 2025
- 2025Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Modelscited by 89
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- 2025Video-LMM Post-Training: A Deep Dive into Video Reasoning with Large Multimodal Models6 Oct 2025
- 2025Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models8 May 2025
- 2025StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistantcited by 56
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- 2026StreamReady: Learning What to Answer and When in Long Streaming Videoscited by 18
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- 2026SocialOmni: Benchmarking Audio-Visual Social Interactivity in Omni Modelscited by 12
- 2026What Should a Streaming Video Model Remember?cited by 7
- 2026StreamPro: From Reactive Perception to Proactive Decision-Making in Streaming Videocited by 3
- 2026OmniInteract: Benchmarking Real-World Streaming Interaction for Real-Time Omnimodal Assistantscited by 3
- 2026FOLIO: Focused Semantic Memory for Streaming Video Understandingcited by 3
- 2026StreamTTT: Reconciling Real-Time Perception and Long-Term Memory in Streaming VLMscited by 3
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- 2026Live Assistant: Learning Whether, When, and Whom to Assist in Real-World Live Social Streams23 Sep 2026
- 2026OmniVChat: Synthesizing, Benchmarking, and Training for Native Audio-Visual Dialogue18 Sep 2026
- 2026Omni Demand Understanding: A Benchmark for Contextual User-Intent Inference in Multimodal Interaction18 Sep 2026
- 2026LiveProBench: Can Streaming Video Models Really Interact Like Humans?11 Sep 2026
- 2026Modality Maturity Index: A benchmark for assessing multimodal capabilities of omni models26 Aug 2026
- 2026OmniAssistBench: Assistant-style Interaction Benchmark for Omni-LLMs21 Aug 2026
- 2026Multi-turn Conversational AI from Text to Multimodal Interaction: Data, Models, Evaluation, and Open Challenges18 Aug 2026
- 2026StreamTTT: Reconciling Real-Time Perception and Long-Term Memory in Streaming VLMs13 Aug 2026
- 2026FOLIO: Focused Semantic Memory for Streaming Video Understanding14 Jul 2026
- 2026What Should a Streaming Video Model Remember?15 Jun 2026
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