Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T09:30:05.747416Z
Paper Citation Record · LEDGER
As of 6 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 2 inbound Pith citation observations for arXiv:2601.13836.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T09:30:05.747416Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-11T01:53:01.939765Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T09:46:26.384867Z
71 of 71 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 5342e9b2-2050-4423-834a-b4495beb432b · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Flamingo: a visual language model for few-shot learning
Reference 1
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Observation 117b96c1-1289-4c89-8fa5-b8541330e63b · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Claude haiku 4.5.https://www.anthropic.com/news/claude-haiku-4-5, 2025
Reference 2
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Observation b9b5dc81-54ec-4d9e-8b4a-050b10c77247 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Qwen3-VL Technical Report
Reference 3
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Observation f93242b4-56c5-4950-9ebf-df4fbbcb86f4 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Qwen2.5-VL Technical Report
Reference 4
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Observation 74decc1f-576f-4c53-bbbb-0510b7fcf13f · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs JointAVBench: A Benchmark for Joint Audio-Visual Reasoning Evaluation
Reference 5
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Observation 291f06fe-e5cc-4f5a-a1a3-08be9955d49e · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Avocado: An audiovisual video captioner driven by temporal orchestration, 2025
Reference 6
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Observation bdd9e760-8893-4b3a-9ab1-63ee9fc832ea · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs
Reference 7
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Observation f94943c4-2e0a-4714-975b-c1967b14ffec · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs AVTrustBench: Assessing and Enhancing Reliability and Robustness in Audio-Visual LLMs
Reference 8
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Observation 6b74ba86-77ec-4db6-8b20-4449c4c74f80 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Qwen2-Audio Technical Report
Reference 9
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Observation e4c8fac1-5cb4-430e-a2a6-bb14c36720b0 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
Reference 10
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Observation 01b70bed-b4a6-4b00-888e-fbc0c43ce51b · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs An image is worth 16x16 words: Transformers for image recognition at scale
Reference 11
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Observation 6dbf7de3-6058-46c9-952b-695a5ec7021a · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis
Reference 12
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Observation c5d976f3-30e0-4bad-a67f-a22ea71eed09 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Longvale: Vision-audio- language-event benchmark towards time-aware omni-modal perception of long videos
Reference 13
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Observation ee42a785-38e9-4c48-a9ca-1219c9646491 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Gemini 3 flash: frontier intelligence built for speed
Reference 14
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Observation 28da8c2f-0656-4530-b6f4-c4838e7d2a79 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Reference 15
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Observation 10659347-8211-4457-b856-c13cc9598dfe · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs
Reference 16
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Observation 204b01f8-c23c-47b3-97fe-badefa6dd0d6 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs LoRA: Low-rank adaptation of large language models
Reference 17
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Observation 815da43e-6d71-47a3-ad10-250e9834563a · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs WavLLM: Towards robust and adaptive speech large language model
Reference 18
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Observation 8d12d096-ae67-436b-95c2-c3d37645874d · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Forecastbench: A dynamic benchmark of AI forecasting capabilities
Reference 19
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Observation 0145f447-cc1b-4b41-8253-502b0bac7606 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Efficient Memory Management for Large Language Model Serving with PagedAttention
Reference 20
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Observation 94a1e897-872f-4722-a3df-18de237e3985 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs What is more likely to happen next? video-and-language future event prediction
Reference 21
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Observation e8dd5021-4dad-490f-9f84-a3c0e8855eb2 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Omnivideobench: Towards audio-visual understanding evaluation for omni mllms, 2025
Reference 22
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Observation 34a15548-1bc1-49be-aa18-ddf1432f0031 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Learning to answer questions in dynamic audio-visual scenarios
Reference 23
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Observation 6431bbed-44f9-4d53-8491-82ed7ec2121d · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Unresolved cited work
Reference 24
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Observation 563cf7eb-5382-4076-b190-ef4b60f00b4a · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Intentqa: Context-aware video intent reasoning
Reference 25
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Observation 182110fe-57b5-48cc-9470-3a8e95219cd5 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs BLIP-2: Bootstrapping language-image pre-training with frozenimageencodersandlargelanguagemodels
Reference 26
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Observation a77102ca-79f2-4f92-b77d-b882fcbe62b3 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Llama-vid: An image is worth 2 tokens in large language models
Reference 27
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Observation a06cdbbc-e55d-41a5-a969-58a42594810e · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Video-llava: Learning united visual representation by alignment before projection
Reference 28
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Observation 8ed4ff97-65b9-4479-a7f4-d5dfaf9d1941 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Visual instruction tuning
Reference 29
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Observation 52c170a9-6577-4502-9730-ac4b1ecd25c6 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Ola: Pushing the Frontiers of Omni-Modal Language Model
Reference 30
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Observation 5fe89d08-cb9d-45d4-8a54-1ef956aff6a6 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs See, Hear, and Understand: Benchmarking Audiovisual Human Speech Understanding in Multimodal Large Language Models
Reference 31
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Observation f4e04727-99ce-481b-8967-68008123f0ba · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs GPT-4o System Card
Reference 32
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Observation 0d22d709-2fed-4727-b621-921d21e4624d · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Learning transferable visual models from natural language supervision
Reference 33
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Observation 456f5fc6-ad34-43ed-ad58-4a866a3fe9eb · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Robust speech recognition via large-scale weak supervision
Reference 34
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Observation be511dd8-3e82-4048-a917-08c72cf835c7 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Timechat: A time-sensitive multimodal large language model for long video understanding
Reference 35
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Observation db963ebe-3076-45e8-9ccc-49841ec3cbb7 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs SALMONN: Towards generic hearing abilities for large language models
Reference 36
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Observation e2b5552f-7812-439e-a4ac-c51df590b3c9 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs video-salmonn 2: Caption-enhanced audio-visual large language models, 2025
Reference 37
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Observation 91eff93a-8fef-440f-88b3-520c1ba45c48 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Empoweringllmswithpseudo- untrimmed videos for audio-visual temporal understanding
Reference 38
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Observation 999cd9e9-7450-41b6-81d1-bffa35dbba45 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Fostering Video Reasoning via Next-Event Prediction
Reference 39
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Observation dd977d04-9f5f-4d6f-82bb-f33cbf209a1f · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs MiniLMv2: Multi-Head Self-Attention Relation Distillation for Compressing Pretrained Transformers
Reference 40
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Observation eca52e40-6877-4180-8d03-2d94c40d9d87 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Ugc-videocaptioner: An omni ugc video detail caption model and new benchmarks, 2025
Reference 41
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Observation 0bdd1548-18b8-44bd-aac7-5f0dfd162eb0 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Qwen2.5-Omni Technical Report
Reference 42
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Observation 2019e343-a879-4850-b5a1-02cdacced65f · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Qwen3-Omni Technical Report
Reference 43
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Observation 38782b91-8639-4079-acab-3b1d2adedec2 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Avqa: A dataset for audio-visual question answering on videos
Reference 44
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Observation 876e2cf3-fa49-41bb-b316-52fe10104723 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Audio-centric video understanding benchmark without text shortcut
Reference 45
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Observation 2ee5adee-8905-4378-8267-8fc9fe604b3b · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs MiniCPM-V: A GPT-4V Level MLLM on Your Phone
Reference 46
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Observation f751875c-2764-451f-8691-af037b973ef2 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs MIRAI: Evaluating LLM Agents for Event Forecasting
Reference 47
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Observation 9423e84a-2c86-49ad-8a40-bf144231d01e · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs FutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction
Reference 48
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Observation 8d1f9cab-1f93-4e66-859d-6073e64b8a0b · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Videollama 3: Frontier multimodal foundation models for image and video understanding, 2025
Reference 49
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Observation f3cb9f55-8729-4bff-ab24-21142c73b5af · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Video-LLaMA: An instruction-tuned audio-visual language model for video understanding
Reference 50
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Observation a7b9e03d-5771-4a71-8096-eb351e13d139 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Timelens: Rethinking video temporal grounding with multimodal llms, 2025
Reference 51
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Observation 973440a7-ee75-4f4c-8cf5-03b5e5a9206f · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Llava-next: A strong zero-shot video understanding model, April 2024
Reference 52
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Observation fe91e45c-5946-485a-b0a7-7b14d573777b · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Llamafactory: Unified efficient fine-tuning of 100+ language models, 2024
Reference 53
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Observation bac7dbdc-5309-4629-b6f8-72d54bc6a17a · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Mlvu: Benchmarkingmulti-tasklongvideounderstanding
Reference 54
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Observation 411ac1a0-8bad-4adb-baa0-c8db2c5edcc9 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs audio event
Reference 56
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Observation d6536786-ded1-44ac-b2ed-eaf005685b9c · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs John walks down the street
Reference 58
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Observation 47f4dab8-a9ee-4cfc-b335-d57bf47d48d8 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Given the premise event: ’[Description of Event A]’, which event is its most direct conclusion?
Reference 59
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Observation 97194122-7bbb-47b0-8e19-82ca4f0399aa · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs decisive
Reference 60
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Observation 94e7e43c-22c1-4f7c-a636-ce6f24ad63b6 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs motor jam
Reference 61
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Observation c83a88fa-3c1b-4262-9fb4-257c23e80f06 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Understand the sequence of actions, the characters involved, and the overall flow of the narrative
Reference 62
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Observation f24d402a-5741-431c-b21d-a165a6ef7e5d · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs A glass shatters
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Observation 6b1280f2-bee5-4c1a-9065-57c7b474c1c3 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Unresolved cited work
Reference 64
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Observation 374b1e23-db9e-4304-abd7-475dd096059c · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Unresolved cited work
Reference 65
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Observation 252dd4f4-8327-4892-99ab-1869e9f6dd30 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Unresolved cited work
Reference 66
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Observation 4ed0cc97-7cea-48bf-9c8e-1d34e1590372 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Unresolved cited work
Reference 67
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Observation 99c47ed7-c774-4274-b8eb-bd6c73c7f0cc · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs # Classification Criteria: You must classify the error into exactly one of the following four categories
Reference 68
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Observation 985fd226-c960-46c2-bf9b-ce2eb2964b74 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs ## Indicator: The visual context alone is insufficient or misleading, and the model failed because it missed the acoustic cue (e.g., a doorbell ringing off-screen)
Reference 69
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Observation f0b144f5-0f0e-4be2-a8cb-0c2c1884b761 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs ## Indicator: The model’s prediction contradicts clear visual evidence (e.g., predicting "driving" when the car is visually parked)
Reference 70
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Observation 8f7bd563-303b-4f74-b37f-b65a2ac44f91 · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs ## Indicator: Understanding the scene requires prior knowledge (e.g., knowing that mixing specific chemicals causes an explosion, or knowing the rules of Chess)
Reference 71
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Observation 69094d7c-2ee4-463a-853d-2df860ad8dfb · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs he is exercising
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Observation 1f515224-ed55-450d-a504-edbc430ba84e · outbound
FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs Unresolved cited work
Reference 2022
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Observation 075050cf-aab1-451b-8dc5-3b65d322515b · inbound
MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs
Reference 84
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Observation 9828d907-7b75-4569-a70c-691be18ed1f5 · inbound
TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos FutureOmni: Evaluating Future Forecasting from Omni-Modal Context for Multimodal LLMs
Reference 24
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