mlsanityData to 14 Oct 2026

Omni2Web: Benchmarking Audiovisual Website Development

arXiv 2609.23417 ↗First posted 20 Sep 2026cs.SE cs.CVcited by 1

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Abstract (arXiv)

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 history. Such requests require intent recovery beyond the explicit specifications assumed by many existing web-editing benchmarks. We introduce Omni2Web, a bilingual benchmark of 918 instances spanning 13,907 edit steps. It defines three complementary tracks: Direct Editing evaluates webpage editing from recordings, Instruction Recovery measures explicit intent recovery, and Instruction Utility tests whether recovered instructions can drive a fixed code executor. We evaluate 17 open- and closed-source models. The best models attain 51.17 on the Edit Fidelity Score (EFS) for Direct Editing and 49.14 on the Instruction Recovery Score (IRS); under the fixed executor, the strongest recovered instructions reach 51.08 EFS, still far below the 89.69 EFS obtained with oracle instructions. Step-level analyses show that correct grounding does not guarantee successful edits, while some Omni models recover instructions that the fixed coding model executes substantially better than their direct edits. Controlled ablations further demonstrate the value of temporally aligned audiovisual evidence, while alternative judges preserve the leader and broad ordering. Together, these findings reveal substantial headroom in multimodal intent recovery and code execution and highlight the promise of pairing Omni rewriters with coding models.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 26 of its 42 references that are in the map. First posted on arXiv 20 Sep 2026.

Builds on

26 of 42 references.

References · 26

  1. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  2. 2023Mind2Web: Towards a Generalist Agent for the Webcited by 1,242
  3. 2024OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environmentscited by 1,195
  4. 2026DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligencecited by 1,040
  5. 2023CogAgent: A Visual Language Model for GUI Agentscited by 704
  6. 2024LLM Evaluators Recognize and Favor Their Own Generationscited by 686
  7. 2024SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agentscited by 567
  8. 2026Gemma 4 Technical Reportcited by 259
  9. 2023MeViS: A Large-scale Benchmark for Video Segmentation with Motion Expressionscited by 228
  10. 2024WebLINX: Real-World Website Navigation with Multi-Turn Dialoguecited by 180
  11. 2024Ferret-UI: Grounded Mobile UI Understanding with Multimodal LLMscited by 176
  12. 2026Qwen3.5-Omni Technical Reportcited by 174
14 more
  1. 2026Qwen3-ASR Technical Reportcited by 118
  2. 2025Daily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across Modalitiescited by 110
  3. 2024ScreenAI: A Vision-Language Model for UI and Infographics Understandingcited by 98
  4. 2024Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Modelscited by 91
  5. 2026MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interactioncited by 78
  6. 2024VideoGUI: A Benchmark for GUI Automation from Instructional Videoscited by 35
  7. 2026Nemotron 3 Nano Omni: Efficient and Open Multimodal Intelligencecited by 30
  8. 2026LVOmniBench: Pioneering Long Audio-Video Understanding Evaluation for Omnimodal LLMscited by 24
  9. 2025JointAVBench: A Benchmark for Joint Audio-Visual Reasoning Evaluationcited by 17
  10. 2025FronTalk: Benchmarking Front-End Development as Conversational Code Generation with Multi-Modal Feedbackcited by 14
  11. 2026MMOU: A Massive Multi-Task Omni Understanding and Reasoning Benchmark for Long and Complex Real-World Videoscited by 14
  12. 2023Spatial and Visual Perspective-Taking via View Rotation and Relation Reasoning for Embodied Reference Understandingcited by 11
  13. 2026WebVR: Benchmarking Multimodal LLMs for WebPage Recreation from Videos via Human-Aligned Visual Rubricscited by 8
  14. 2025Envisioning Future Interactive Web Development: Editing Webpage with Natural Languagecited by 4

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