Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:52:06.520392Z
Paper Citation Record · LEDGER
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
As of 18 August 2026, this Paper Citation Record lists 76 of 76 outbound references and 16 inbound Pith citation observations for arXiv:2506.01300.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T12:32:59.130504Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T16:39:57.778113Z
Reference resolution
76 of 76 outbound references displayed
- verified exact1
- verified fuzzy17
- unresolved58
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 1be81308-c01c-4042-be40-b5813409f28b · outbound
This paper cites Flamingo: a visual language model for few-shot learning.Advances in neural information processing systems, 35:23716–23736, 2022.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Flamingo: a visual language model for few-shot learning.Advances in neural information processing systems, 35:23716–23736, 2022
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:51:57.632772Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a0f71f7c-9b15-4464-a25f-8382a351b257 · outbound
This paper cites Qwen2.5-VL Technical Report.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Qwen2.5-VL Technical Report
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:51:58.310770Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 102253c2-96a0-417c-b972-7db43a0eb69c · outbound
This paper cites LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:51:59.026187Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fb54b947-ccfe-448b-aab7-7f1a68fcba3c · outbound
This paper cites Sharegpt4video: Improving video understanding and generation with better captions.Advances in Neural Information Processing Systems, 37:19472– 19495, 2024.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Sharegpt4video: Improving video understanding and generation with better captions.Advances in Neural Information Processing Systems, 37:19472– 19495, 2024
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:51:59.236952Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b65b9093-4a76-49dc-8d33-1b46a11cc01e · outbound
This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:51:59.500410Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4b433ea6-da38-41d7-b39f-4361c179682e · outbound
This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:51:59.788980Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 39ca27fe-336c-4bf1-9fee-22ced1e2a5ba · outbound
This paper cites Supervised learning.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Supervised learning
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:09.878162Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation df18337e-b269-4427-8dc4-c5eb2a5fbe45 · outbound
This paper cites A long video caption generation algorithm for big video data retrieval.Future Generation Computer Systems, 93:583–595, 2019.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding A long video caption generation algorithm for big video data retrieval.Future Generation Computer Systems, 93:583–595, 2019
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:09.791899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6a1f81c9-dcca-470c-b5b3-8940cb5b5fc6 · outbound
This paper cites Videoagent: A memory-augmented multimodal agent for video understanding.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Videoagent: A memory-augmented multimodal agent for video understanding
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:01.205243Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c72fa3eb-90b6-481b-a9bb-877c4d8f6149 · outbound
This paper cites Video-R1: Reinforcing Video Reasoning in MLLMs.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Video-R1: Reinforcing Video Reasoning in MLLMs
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:01.830424Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3c70e8a3-ab42-4577-8f51-b5a8019f0ec3 · outbound
This paper cites Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:01.912701Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 87f08290-4877-431a-9c5c-8291479b2dd4 · outbound
This paper cites Visbench: A framework for remote data visualization and analysis.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Visbench: A framework for remote data visualization and analysis
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:09.687894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 69b421ce-8c08-4917-abe0-bdfc3944b2de · outbound
This paper cites Video-MMMU: Evaluating Knowledge Acquisition from Multi-Discipline Professional Videos.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Video-MMMU: Evaluating Knowledge Acquisition from Multi-Discipline Professional Videos
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:02.095752Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 81e2ba49-0023-467d-b944-61d8f8bb5ca1 · outbound
This paper cites GPT-4o System Card.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding GPT-4o System Card
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:02.191523Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eaa67c7e-0c46-4022-aae0-986774e0a664 · outbound
This paper cites BIMBA: Selective-Scan Compression for Long-Range Video Question Answering.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding BIMBA: Selective-Scan Compression for Long-Range Video Question Answering
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:02.288427Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d46fa311-2b27-4b04-a6ab-e182a8e94d36 · outbound
This paper cites VideoRAG: Retrieval-Augmented Generation over Video Corpus.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding VideoRAG: Retrieval-Augmented Generation over Video Corpus
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:02.359068Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36d9ab6b-be07-4308-a478-66bfb3688a3a · outbound
This paper cites New generation deep learning for video object detection: A survey.IEEE Transactions on Neural Networks and Learning Systems, 33(8):3195–3215, 2021.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding New generation deep learning for video object detection: A survey.IEEE Transactions on Neural Networks and Learning Systems, 33(8):3195–3215, 2021
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:09.593435Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a3e5b1a5-cb95-48c0-a050-f451effb1163 · outbound
This paper cites A survey of frontiers in llm reasoning: Inference scaling, learning to reason, and agentic systems.arXiv preprint arXiv:2504.09037, 2025.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding A survey of frontiers in llm reasoning: Inference scaling, learning to reason, and agentic systems.arXiv preprint arXiv:2504.09037, 2025
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:02.510242Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a34bbc0b-9c8c-4d91-afb5-192bdfcb2f23 · outbound
This paper cites MMCTAgent: Multi-modal Critical Thinking Agent Framework for Complex Visual Reasoning.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding MMCTAgent: Multi-modal Critical Thinking Agent Framework for Complex Visual Reasoning
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:02.616703Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bb3419ea-c525-44aa-a585-17c074f8fe92 · outbound
This paper cites Video-VoT-R1: An efficient video inference model integrating image packing and AoE architecture.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Video-VoT-R1: An efficient video inference model integrating image packing and AoE architecture
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T11:52:07.114887Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 096c6815-5245-45ce-baca-b8e6e4d6cf63 · outbound
This paper cites VideoChat: Chat-Centric Video Understanding.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding VideoChat: Chat-Centric Video Understanding
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:02.781775Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 55ee274d-81e6-4e95-a5d6-69c51ded5163 · outbound
This paper cites Mvbench: A comprehensive multi-modal video understanding benchmark.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Mvbench: A comprehensive multi-modal video understanding benchmark
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:02.885116Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd6432c5-199f-41a0-9fae-5001b5a82a24 · outbound
This paper cites Evaluating real-world robot manipulation policies in simulation.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Evaluating real-world robot manipulation policies in simulation
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:09.515158Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 5250ca97-04eb-43ec-904f-4ead60e8f0b5 · outbound
This paper cites Video-LLaVA: Learning United Visual Representation by Alignment Before Projection.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:03.037638Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 82c0dd4b-7efa-417e-8b24-09987e4f0f69 · outbound
This paper cites Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:03.120334Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f1ce3282-74b9-42a5-b4c9-2734a3a1c058 · outbound
This paper cites Grounding dino: Marrying dino with grounded pre-training for open-set object detection.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Grounding dino: Marrying dino with grounded pre-training for open-set object detection
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:03.155199Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b29f277b-80b9-4b11-910f-aad6dfaa8894 · outbound
This paper cites TempCompass: Do Video LLMs Really Understand Videos?.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding TempCompass: Do Video LLMs Really Understand Videos?
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:03.280995Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4c20478-b9f1-41a2-ba72-350cd53df1a5 · outbound
This paper cites Inference-time scaling for generalist reward modeling.arXiv preprint arXiv:2504.02495, 2025.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Inference-time scaling for generalist reward modeling.arXiv preprint arXiv:2504.02495, 2025
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:03.403830Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3c1b2c95-f32a-47b8-95cd-374e42339c39 · outbound
This paper cites A real- time object detection algorithm for video.Computers & Electrical Engineering, 77:398–408, 2019.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding A real- time object detection algorithm for video.Computers & Electrical Engineering, 77:398–408, 2019
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:09.431241Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4cd63c2f-cde4-4503-afa9-3c2302e4b9e3 · outbound
This paper cites Video-rag: Visually-aligned retrieval-augmented long video comprehension.arXiv preprint arXiv:2411.13093, 2024.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Video-rag: Visually-aligned retrieval-augmented long video comprehension.arXiv preprint arXiv:2411.13093, 2024
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:03.589894Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 36ba2adb-1ec1-4c2a-9c3b-025e15b9efbb · outbound
This paper cites Egoschema: A diagnostic benchmark for very long-form video language understanding.Advances in Neural Information Processing Systems, 36:46212–46244, 2023.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Egoschema: A diagnostic benchmark for very long-form video language understanding.Advances in Neural Information Processing Systems, 36:46212–46244, 2023
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:03.678829Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f2f78580-1bad-4ff0-b88a-2871da22b966 · outbound
This paper cites Optical character recognition.International journal of recent technology and engineering (IJRTE), 2(1):72–75, 2013.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Optical character recognition.International journal of recent technology and engineering (IJRTE), 2(1):72–75, 2013
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:09.302660Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9589d168-a2a1-46b3-b59d-a0d5b52b5068 · outbound
This paper cites Direct preference optimization: Your language model is secretly a reward model.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Direct preference optimization: Your language model is secretly a reward model
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:03.906958Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2e517384-bf4b-4127-930a-623522809703 · outbound
This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.012050Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7d5c8bf3-a6c2-4477-8364-6639b3871b1a · outbound
This paper cites Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36:8634–8652, 2023.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Reflexion: Language agents with verbal reinforcement learning.Advances in Neural Information Processing Systems, 36:8634–8652, 2023
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.092255Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8a5c5170-2b8f-4c5f-ad9d-c6bff655e472 · outbound
This paper cites Clip4caption: Clip for video caption.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Clip4caption: Clip for video caption
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:09.161153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b492a32e-b99c-42d9-b9d9-f75137683fc1 · outbound
This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.282750Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6c873815-9fe0-4a56-9899-af6e692d1f15 · outbound
This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.407610Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 694b2ea1-a581-4bfd-9043-d45c68d63642 · outbound
This paper cites LVBench: An Extreme Long Video Understanding Benchmark.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding LVBench: An Extreme Long Video Understanding Benchmark
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.486784Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f7ade44-8bbf-4824-abaa-b9180d64e2d9 · outbound
This paper cites Videoagent: Long-form video understanding with large language model as agent.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Videoagent: Long-form video understanding with large language model as agent
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.606785Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b0cfdf22-0f13-436f-a2cb-c0ff9ef1f06c · outbound
This paper cites Longllava: Scaling multi-modal llms to 1000 images efficiently via a hybrid architecture.arXiv preprint arXiv:2409.02889, 2024.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Longllava: Scaling multi-modal llms to 1000 images efficiently via a hybrid architecture.arXiv preprint arXiv:2409.02889, 2024
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.621903Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f9d85935-da37-4c4a-a56d-c37c6088d6a0 · outbound
This paper cites SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding SoTA with Less: MCTS-Guided Sample Selection for Data-Efficient Visual Reasoning Self-Improvement
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.646937Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b6da2d5e-de29-42e3-966d-b14c05c59e11 · outbound
This paper cites Reinforcement learning.Adaptation, learning, and optimization, 12(3):729, 2012.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Reinforcement learning.Adaptation, learning, and optimization, 12(3):729, 2012
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:09.069209Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation af4c72b2-bc22-40cc-85b2-9cb08932bbd9 · outbound
This paper cites Sailing by the Stars: A Survey on Reward Models and Learning Strategies for Learning from Rewards.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Sailing by the Stars: A Survey on Reward Models and Learning Strategies for Learning from Rewards
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.806540Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b4ec8324-c20b-496c-b5d9-2db4aa971f94 · outbound
This paper cites Next-qa: Next phase of question- answering to explaining temporal actions.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Next-qa: Next phase of question- answering to explaining temporal actions
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.896434Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a764790d-75e9-40b8-92e1-412508e6e4e9 · outbound
This paper cites Qwen2.5 Technical Report.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Qwen2.5 Technical Report
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:04.983800Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90e8c85e-ca08-4738-bf48-0c7e041833a7 · outbound
This paper cites Vid2seq: Large-scale pretraining of a visual language model for dense video captioning.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Vid2seq: Large-scale pretraining of a visual language model for dense video captioning
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:08.930996Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1e00a398-26eb-43cb-8fe3-3094f39cb71d · outbound
This paper cites VCA: Video Curious Agent for Long Video Understanding.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding VCA: Video Curious Agent for Long Video Understanding
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:05.146191Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4fec2d96-4ea0-4ee6-83dd-722aeaa204ae · outbound
This paper cites T*: Re-thinking Temporal Search for Long-Form Video Understanding.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding T*: Re-thinking Temporal Search for Long-Form Video Understanding
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:05.217519Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d2cc1b7-310b-4135-8c15-ef95429627c8 · outbound
This paper cites Springer, 2016.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Springer, 2016
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:08.810813Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation a656f6a0-36b8-455c-b943-f2498f93a962 · outbound
This paper cites Merlot: Multimodal neural script knowledge models.Advances in neural information processing systems, 34:23634–23651, 2021.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Merlot: Multimodal neural script knowledge models.Advances in neural information processing systems, 34:23634–23651, 2021
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:08.744429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9fb880f2-dc92-4e74-840c-74ba33e7b7f9 · outbound
This paper cites OmAgent: A Multi-modal Agent Framework for Complex Video Understanding with Task Divide-and-Conquer.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding OmAgent: A Multi-modal Agent Framework for Complex Video Understanding with Task Divide-and-Conquer
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:05.252358Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1037613c-34e7-4cf4-993a-c89ec1469acc · outbound
This paper cites Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:05.260604Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4afaad58-44d7-4e64-8e01-b8477d86472e · outbound
This paper cites TinyLLaVA-Video-R1: Towards Smaller LMMs for Video Reasoning.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding TinyLLaVA-Video-R1: Towards Smaller LMMs for Video Reasoning
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:05.300590Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 750e3829-9bd7-499d-a53f-33291ba92b22 · outbound
This paper cites Llava-next: A strong zero-shot video understanding model.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Llava-next: A strong zero-shot video understanding model
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:05.389434Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 759fd701-e7b1-4f1a-86f2-762e8626f470 · outbound
This paper cites LLaVA-Video: Video Instruction Tuning With Synthetic Data.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding LLaVA-Video: Video Instruction Tuning With Synthetic Data
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:05.475245Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7c6129e4-3d2e-4edd-b340-313df9e42b50 · outbound
This paper cites GRAPE: Generalizing robot policy via preference alignment.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding GRAPE: Generalizing robot policy via preference alignment
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:08.646448Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 3ec4580c-f95e-4276-833e-804df956f725 · outbound
This paper cites MMVU: Measuring Expert-Level Multi-Discipline Video Understanding.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:05.618855Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e7957743-e946-4247-b3f0-3d91b93f9cdd · outbound
This paper cites MLVU: Benchmarking Multi-task Long Video Understanding.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding MLVU: Benchmarking Multi-task Long Video Understanding
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:05.694478Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 27221795-aa84-426e-8810-dc44697e6c62 · outbound
This paper cites Fine-Tuning Language Models from Human Preferences.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Fine-Tuning Language Models from Human Preferences
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:52:05.786594Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 60af8306-df46-48fa-b256-7449baec38fa · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 61
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:08.575739Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cbf29bb9-eb39-41a8-8929-c98c1dc62353 · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 62
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:08.484882Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2526a2cf-926f-4e6f-91f2-4837c46a85c5 · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 63
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:08.415386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4fca7a39-865d-4986-a0e4-ea0c49908c0a · outbound
This paper cites final_answer.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding final_answer
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:08.336877Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e867ee9b-fdb4-4ed4-b918-dd808f59b5e0 · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 65
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:08.271741Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8ba41646-316e-41d8-9685-c1db615163a4 · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 66
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:08.208571Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 6f519e9a-0846-43cc-8fc4-5572ce1cd1bf · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 67
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:08.151703Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7e859022-84ce-4c5c-a1e8-b94fa7b6e6b4 · outbound
This paper cites final_answer.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding final_answer
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:08.067744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 20ad729e-21f9-4a82-b3a3-3256ece21e10 · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 69
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:07.975166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation da03baae-7c04-4766-9244-e4359eaf489c · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 70
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:07.894057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0f5f08f1-18c0-40c1-a535-d8c5f4ea15b1 · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 71
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:07.821986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 39ceaa36-4aa4-47b5-877e-7ea413dc8402 · outbound
This paper cites canine” = “dog.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding canine” = “dog
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:07.725231Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 33859cb0-8896-4928-ac80-402e402f787e · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 73
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:07.631729Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1d5a6fe0-6ccc-431e-b8cc-84d455415f74 · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 74
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:07.537346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 366c6bcd-9312-482f-9bf6-2dc94b70f5e1 · outbound
This paper cites an unresolved cited work.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding Unresolved cited work
Reference 75
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:52:07.445401Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 70d8f986-230c-46ed-8267-0690b04d910e · outbound
This paper cites What”, “Where.
ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding What”, “Where
Reference 76
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:52:07.382681Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
Observation ac573bae-4752-485c-883f-55a61fd97187 · inbound
ForgetMe: Evaluating Selective Forgetting in Generative Models cites this paper.
ForgetMe: Evaluating Selective Forgetting in Generative Models ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 72
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T12:32:59.130504Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3a4df78e-d045-4809-9b5e-907452d9e57a · inbound
4KAgent: Agentic Any Image to 4K Super-Resolution cites this paper.
4KAgent: Agentic Any Image to 4K Super-Resolution ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 268
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:52:39.441018Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea46245c-9613-4a23-86d7-d7331fac33fa · inbound
Low-Cost Test-Time Adaptation for Robust Video Editing cites this paper.
Low-Cost Test-Time Adaptation for Robust Video Editing ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T12:21:30.770642Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 495ed2be-70c7-4bb2-9c66-9c8f48b5db12 · inbound
Multi-Modal Machine Learning Framework for Predicting Early Recurrence of Brain Tumors Using MRI and Clinical Biomarkers cites this paper.
Multi-Modal Machine Learning Framework for Predicting Early Recurrence of Brain Tumors Using MRI and Clinical Biomarkers ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 76
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:53:04.377414Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7ff03557-9f3d-4582-b7f2-a9e28202df8a · inbound
A Multimodal Deep Learning Framework for Early Diagnosis of Liver Cancer via Optimized BiLSTM-AM-VMD Architecture cites this paper.
A Multimodal Deep Learning Framework for Early Diagnosis of Liver Cancer via Optimized BiLSTM-AM-VMD Architecture ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 76
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T12:53:15.065485Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e6b80ed8-feae-4fbf-bb1c-b69d507d9c7f · inbound
DAG: A Dual Correlation Network for Time Series Forecasting with Exogenous Variables cites this paper.
DAG: A Dual Correlation Network for Time Series Forecasting with Exogenous Variables ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 72
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T15:31:33.406292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 1771a2f9-43da-462e-bac9-3a53fa1657a0 · inbound
Hermes: A Multi-Scale Spatial-Temporal Hypergraph Network for Stock Time Series Forecasting cites this paper.
Hermes: A Multi-Scale Spatial-Temporal Hypergraph Network for Stock Time Series Forecasting ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 77
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T12:36:22.633218Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7bb90a75-89c5-41aa-874e-7cffd7629122 · inbound
GLANCE: A Global-Local Coordination Multi-Agent Framework for Music-Grounded Non-Linear Video Editing cites this paper.
GLANCE: A Global-Local Coordination Multi-Agent Framework for Music-Grounded Non-Linear Video Editing ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 56
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T23:20:51.103089Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b3921a8d-93da-49c9-9b9f-542e6e097ea7 · inbound
HiCrew: Hierarchical Reasoning for Long-Form Video Understanding via Question-Aware Multi-Agent Collaboration cites this paper.
HiCrew: Hierarchical Reasoning for Long-Form Video Understanding via Question-Aware Multi-Agent Collaboration ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:26:02.242836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 67121b98-4b0d-41c1-99b7-5b3181bee725 · inbound
Agentic Collaborative Cognition for Zero-Shot 3D Understanding cites this paper.
Agentic Collaborative Cognition for Zero-Shot 3D Understanding ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 63
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T16:39:57.779695Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 70a1566f-46d7-4825-b7de-c0e186576dab · inbound
Agentic Collaborative Cognition for Zero-Shot 3D Understanding cites this paper.
Agentic Collaborative Cognition for Zero-Shot 3D Understanding ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 63
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T12:59:52.640164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 73db7383-415f-4ca2-9be8-7d65c81c02a8 · inbound
EVLA: An Electro-Aware Multimodal Assistant for Physically-Grounded Driving Reasoning and Control cites this paper.
EVLA: An Electro-Aware Multimodal Assistant for Physically-Grounded Driving Reasoning and Control ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 89
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T10:04:36.295073Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 105f4180-394b-4e53-990c-2e7c1b0159e6 · inbound
A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions cites this paper.
A3M: Adaptive, Adversarial and Multi-Objective Learning for Strategic Bidding in Repeated Auctions ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T09:54:34.421694Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2bad20b2-32ca-4641-8968-6c61e4ae1166 · inbound
Beyond Skepticism: Evaluating LLMs Pedagogical Intent Reasoning with the Adaptive Pedagogical Vigilance Framework cites this paper.
Beyond Skepticism: Evaluating LLMs Pedagogical Intent Reasoning with the Adaptive Pedagogical Vigilance Framework ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T15:28:33.596585Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 98e38a82-915f-4527-a8f8-5882a6c71685 · inbound
FedCausal-Dyn: A Causal-Dynamic Paradigm for Federated Learning under Dynamic Feature Drift cites this paper.
FedCausal-Dyn: A Causal-Dynamic Paradigm for Federated Learning under Dynamic Feature Drift ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T17:36:18.728469Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 94a0d757-191e-49df-9044-6f0de5e6aec7 · inbound
Child-Oriented AIGC Video Risk Reviewing: A Benchmark and Knowledge-Supported Iterative Reasoning Framework cites this paper.
Child-Oriented AIGC Video Risk Reviewing: A Benchmark and Knowledge-Supported Iterative Reasoning Framework ReAgent-V: A Reward-Driven Multi-Agent Framework for Video Understanding
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T13:14:48.090658Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.