Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T16:49:54.185917Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 100 of 104 outbound references and 0 inbound Pith citation observations for arXiv:2507.12463.
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 2026-08-06T16:49:54.185917Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
100 of 104 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 71839772-d37c-4bb6-8090-7cbf3de9a016 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Auxiliary tasks benefit 3d skeleton-based human motion prediction
Reference 1
Source-reported events for the cited work
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Observation a96daa7f-fbc2-4f4a-880c-6c94bc60c808 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Tamformer: Multi-modal transformer with learned attention mask for early intent prediction
Reference 2
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Unavailable: canonical work link unavailable.
Observation c47b113e-39f4-4286-8073-9c025b0ab892 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding GTransPDM: A Graph-embedded Transformer with Positional Decoupling for Pedestrian Crossing Intention Prediction
Reference 3
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Observation 27815572-f287-4085-a7ad-e23add9bdce2 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Predicting pedestrian crossing intention with feature fusion and spatio-temporal attention
Reference 4
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e65c5890-52c5-41db-8aec-26f07361ddfc · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Incorporating physics principles for precise human motion prediction
Reference 5
Source-reported events for the cited work
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Observation f19f81f0-32c3-4616-976b-4e360e651e53 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Behavioral intention prediction in driving scenes: A survey
Reference 6
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Observation 668c5fa7-85d0-4f6d-a0aa-a5a34ede1a94 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Scalability in perception for autonomous driving: Waymo open dataset
Reference 7
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Observation 8f10b2ba-4ba7-4d84-bdfa-d7cb13c856f6 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding nuscenes: A multimodal dataset for autonomous driving
Reference 8
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Observation 6b0d5c9a-88d9-44fe-b3ba-60febd80c9e9 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Vision meets robotics: The kitti dataset
Reference 9
Source-reported events for the cited work
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Observation 6a6153d1-418d-4584-bf64-aab75b599cfb · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Pie: A large-scale dataset and models for pedestrian intention estimation and trajectory prediction
Reference 10
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Observation b50f0152-fb57-4c86-824d-22574cc8200a · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Euro-pvi: Pedestrian vehicle interactions in dense urban centers
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 75c4dd4a-6aa8-4f10-b74c-b9cbea0c36f2 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Are they going to cross? a benchmark dataset and baseline for pedestrian crosswalk behavior
Reference 12
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Observation 2c03a62f-90fb-4846-abd9-0525de31d5b6 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Recovering accurate 3d human pose in the wild using imus and a moving camera
Reference 13
Source-reported events for the cited work
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Observation de699b7c-0835-46f1-9b34-031d2a002a56 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Pedestrian motion reconstruction: A large-scale benchmark via mixed reality rendering with multiple perspectives and modalities
Reference 14
Source-reported events for the cited work
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Observation 35a10f2d-3953-4c15-83fd-a9fd04b6a633 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Text to blind motion
Reference 15
Source-reported events for the cited work
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Observation 522147a0-1c2e-4da7-b5dc-f7fc850ea232 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Learning to generate diverse pedestrian move- ments from web videos with noisy labels
Reference 16
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Observation 5f264ace-4e2b-475a-8332-4e25d805e24b · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding LLaMA: Open and Efficient Foundation Language Models
Reference 17
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Observation c37d2d69-251c-4188-a3a1-f199219b0a40 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Vila: On pre-training for visual language models, 2023
Reference 18
Source-reported events for the cited work
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Observation 7ba56018-4ad9-4ac4-91cf-f28fe1dadac0 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Longvila: Scaling long-context visual language models for long videos, 2024
Reference 19
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Unavailable: canonical work link unavailable.
Observation 693cdbeb-5477-427d-9c0c-ccac7a52ccb5 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Nvila: Efficient frontier visual language models, 2024
Reference 20
Source-reported events for the cited work
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Observation 297c659b-7536-4a3d-ad99-c81590c0b5f8 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Visual instruction tuning, 2023
Reference 21
Source-reported events for the cited work
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Observation a63ec538-4950-44c5-b9a0-10b1c4594b7f · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Llava-next: Improved reasoning, ocr, and world knowledge, January 2024
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1453a2f1-8bde-4cfd-9337-264e70df223f · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Improved baselines with visual instruction tuning, 2023
Reference 23
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Unavailable: canonical work link unavailable.
Observation 2eb5d404-b758-49a9-b3a4-66d32a56798c · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Video instruction tuning with synthetic data, 2024
Reference 24
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Observation aea0b38f-be94-4ce3-8094-dbf9f85e5196 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Qwen Technical Report
Reference 25
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Observation a666b112-4d18-43ab-b4ba-28345d4a0e29 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding 2d human pose estimation calibration and keypoint visibility classification
Reference 26
Source-reported events for the cited work
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Observation c57d3b76-d08b-4d33-b7f5-c64d243f7602 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Recurrent human pose estimation
Reference 27
Source-reported events for the cited work
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Observation fa480358-192c-4714-9253-d3f1016384a7 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Rethinking the heatmap regression for bottom-up human pose estimation
Reference 28
Source-reported events for the cited work
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Observation 892c2586-5580-411a-8265-3ab02a313167 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Tokenpose: Learning keypoint tokens for human pose estimation
Reference 29
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Observation 8a758109-a470-4bd3-a647-71bfc7302460 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Whole- body human pose estimation in the wild
Reference 30
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Observation 94e049d9-f517-4a89-a27f-b739d48817cb · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Unresolved cited work
Reference 31
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Observation 9b883b61-44b7-437b-bcc5-0cd0cc3b1c58 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Unresolved cited work
Reference 32
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Observation 59899439-f75b-4e85-a161-55b8cac73f39 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Unresolved cited work
Reference 33
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Observation 1c010a3d-66b7-4b03-9a71-7c68846f1581 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Unresolved cited work
Reference 34
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Observation 0a50da58-49dc-4d31-8ab4-40816ba7ab2e · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding MotionBank: A Large-scale Video Motion Benchmark with Disentangled Rule-based Annotations
Reference 35
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Observation 27b6e82b-430e-42c8-9144-895cccf7a313 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Amass: Archive of motion capture as surface shapes
Reference 36
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Observation f4e72f73-3dac-49b6-a2cc-7bbff6b27495 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Motion- x: A large-scale 3d expressive whole-body human motion dataset
Reference 37
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Observation d30fa8f4-654e-4a01-9c9a-f20182624064 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Dynamic multi-person mesh recovery from uncalibrated multi-view cameras
Reference 38
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Observation 867a74ba-8797-4300-a5cb-9d6c5274a6f9 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Motion capture from internet videos
Reference 39
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Observation 8d9a3d61-079c-4639-a8bb-838233d8e2f8 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Scene-aware 3d multi-human motion capture from a single camera
Reference 40
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Observation 2291b9e1-8e3d-4ee4-afc5-36e6e2ef7029 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding D &d: Learning human dynamics from dynamic camera
Reference 41
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Observation c096dc11-32ef-427e-8d4b-02f99abb36f5 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Decoupling human and camera motion from videos in the wild
Reference 42
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Observation 6aefdd6d-1981-4a44-a1f1-0dddfaf1523e · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Glamr: Global occlusion-aware human mesh recovery with dynamic cameras
Reference 43
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Observation 9820c467-ba5a-4440-aa1b-2bf2e57f7dc5 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Implicit neural representations for variable length human motion generation
Reference 44
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Observation 376615c3-cc43-41f0-9c2c-c1b895599a2c · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Human Motion Diffusion Model
Reference 45
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Observation 03f7e6d3-2a41-4896-8caa-e2297dc1c84a · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Motiondiffuse: Text-driven human motion generation with diffusion model
Reference 46
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Observation 9ea47c99-d57c-4a00-904f-4631a1ac504c · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Home action genome: Cooperative compositional action understanding
Reference 47
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Observation b4758825-c618-4953-bb34-bb8a00c56d74 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Babel: Bodies, action and behavior with english labels
Reference 48
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Observation be6c8ef9-7a1f-4292-a862-7d67243e69d2 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Mining actionlet ensemble for action recognition with depth cameras
Reference 49
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Observation 92a5830b-19b3-47c5-a2b6-c13a1da481bb · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Action recognition based on a bag of 3d points
Reference 50
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Observation 6a2104d7-8a74-41c3-be0e-22d7490af9a9 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild
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Observation d4bca55f-f114-4a84-8c6b-b03b8097020a · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Modeling temporal structure of decomposable motion segments for activity classification
Reference 52
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Observation c58ba53b-e930-46e4-8461-78f9e80d71dd · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding The Kinetics Human Action Video Dataset
Reference 53
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Observation 92b440a4-e734-4821-a45c-8212ea0819ed · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Actions in context
Reference 54
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Observation 164e9ab0-c904-4bf8-8d68-3c8a9b41626b · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Auxformer: Robust approach to audiovisual emotion recognition
Reference 55
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Context-based inter- pretable spatio-temporal graph convolutional network for human motion forecasting
Reference 56
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Gcnext: Towards the unity of graph convo- lutions for human motion prediction
Reference 57
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Back to mlp: A simple baseline for human motion prediction
Reference 58
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Reference 59
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Reference 60
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Benchmark for evaluating pedestrian action prediction
Reference 62
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Agreeing to cross: How drivers and pedestrians communicate
Reference 63
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Pedestrian intention prediction based on dynamic fuzzy automata for vehicle driving at nighttime
Reference 64
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Pedestrian intention and pose prediction through dynamical models and behaviour classification
Reference 65
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Reference 66
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Dolphins: Multimodal language model for driving
Reference 67
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Drivelm: Driving with graph visual question answering
Reference 68
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Tem-adapter: Adapting image-text pretraining for video question answer
Reference 69
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Lmdrive: Closed-loop end-to-end driving with large language models
Reference 70
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning
Reference 71
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Rag-driver: Generalisable driving explanations with retrieval-augmented in-context learning in multi- modal large language model
Reference 72
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Driving with llms: Fusing object-level vector modality for explainable autonomous driving
Reference 73
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Lingoqa: Visual question answering for autonomous driving
Reference 74
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Observation fd6b48ab-d441-4973-8c40-d5b1556c37ac · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Covla: Comprehensive vision-language-action dataset for autonomous driving
Reference 75
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Rea- son2drive: Towards interpretable and chain-based reasoning for autonomous driving
Reference 76
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Observation 607d30e9-3a00-4aaf-9820-30d0b87c37e2 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Nuscenes-mqa: Integrated evaluation of captions and qa for autonomous driving datasets using markup annotations
Reference 77
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MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding NuScenes-QA: A Multi-modal Visual Question Answering Benchmark for Autonomous Driving Scenario
Reference 78
Source-reported events for the cited work
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Observation a79d6fa2-8fd4-4d0e-bd84-197aed7768f3 · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding 1 year, 1000 km: The oxford robotcar dataset
Reference 79
Source-reported events for the cited work
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Observation 9bb8aba5-a4b5-4106-9d54-f1f3eba09c6d · outbound
MMHU: A Massive-Scale Multimodal Benchmark for Human Behavior Understanding Dada: Driver attention prediction in driving accident scenarios
Reference 80
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