Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:40:57.860880Z
Paper Citation Record · LEDGER
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
As of 23 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 11 inbound Pith citation observations for arXiv:2506.01725.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T16:58:52.971482Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T17:40:00.934274Z
Reference resolution
52 of 52 outbound references displayed
- verified exact0
- verified fuzzy8
- unresolved44
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation a15c7f71-a533-4b6f-90c3-a2dca39bc095 · outbound
This paper cites GPT-4 Technical Report.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking GPT-4 Technical Report
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:39:54.001986Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation be9052c9-8e93-4861-a699-4f87d8bb6797 · outbound
This paper cites Activitynet: A large-scale video benchmark for human activity understanding.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Activitynet: A large-scale video benchmark for human activity understanding
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:08.019749Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b9c0c257-e40d-4a50-9b57-4793d2ddcc92 · outbound
This paper cites Auroracap: Efficient, performant video detailed captioning and a new benchmark.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Auroracap: Efficient, performant video detailed captioning and a new benchmark
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:40:59.563025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 87d10cb7-bbce-4570-894c-48ea936d37e7 · outbound
This paper cites M3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge dis- tillation.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking M3-embedding: Multi-linguality, multi-functionality, multi-granularity text embeddings through self-knowledge dis- tillation
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:09.643118Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ef9d158-91d2-4043-b920-430cefab504d · outbound
This paper cites ShareGPT4Video: Improving Video Understanding and Generation with Better Captions.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking ShareGPT4Video: Improving Video Understanding and Generation with Better Captions
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:09.778162Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 03135c81-6c8b-4354-b373-5950dd5531e4 · outbound
This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:09.868692Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eb22eed1-3201-432c-9962-4d3ab340b08f · outbound
This paper cites Video-R1: Reinforcing Video Reasoning in MLLMs.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Video-R1: Reinforcing Video Reasoning in MLLMs
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:09.908851Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41784efd-54cd-4147-bb3a-2519b8b8319b · outbound
This paper cites Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:09.939333Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 83d9c79d-4ff8-4bf6-a9f4-4936233864b4 · outbound
This paper cites Tall: Temporal activity localization via language query.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Tall: Temporal activity localization via language query
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:40:59.301041Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 02ca2843-d1a7-4209-ba52-dea0399d67e4 · outbound
This paper cites Scaling laws for reward model overoptimization.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Scaling laws for reward model overoptimization
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:40:59.223294Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7c245ae2-6d72-4855-8bec-7c8f7ad09bc5 · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:11.701653Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5eead944-f033-4430-97d5-61140c8c3ef9 · outbound
This paper cites Shot2Story: A New Benchmark for Comprehensive Understanding of Multi-shot Videos.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Shot2Story: A New Benchmark for Comprehensive Understanding of Multi-shot Videos
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:11.807797Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 68037354-34b0-40c7-954e-572ffe521b97 · outbound
This paper cites OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:11.883387Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5a3b0e9d-49b5-48eb-889e-a442eaca222c · outbound
This paper cites Video-MMMU: Evaluating Knowledge Acquisition from Multi-Discipline Professional Videos.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Video-MMMU: Evaluating Knowledge Acquisition from Multi-Discipline Professional Videos
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:11.956199Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 903b84b7-4c7b-4e9a-ba12-15ed97a07435 · outbound
This paper cites GPT-4o System Card.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking GPT-4o System Card
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:11.978948Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9b7bb67e-93e3-4e1f-9da3-d259de55f54a · outbound
This paper cites OpenAI o1 System Card.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking OpenAI o1 System Card
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:11.995527Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8c2b9347-9f47-422d-8df5-d5a7eaa3ad00 · outbound
This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:12.012820Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ff83fa10-ffe1-48b6-9b70-6a8e139e6a8c · outbound
This paper cites A shortest augmenting path algorithm for dense and sparse linear assignment problems.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking A shortest augmenting path algorithm for dense and sparse linear assignment problems
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:40:59.184267Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 3210f0e7-20a3-4d2f-9319-37e1bc1b2cad · outbound
This paper cites LLaVA-OneVision: Easy Visual Task Transfer.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking LLaVA-OneVision: Easy Visual Task Transfer
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:12.061896Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 64cd84fb-ff43-4cac-9c69-120eafb54e01 · outbound
This paper cites Mvbench: A comprehensive multi-modal video understanding benchmark.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Mvbench: A comprehensive multi-modal video understanding benchmark
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:40:59.084921Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 00491f7a-f816-44ec-89d2-873dd68e7f75 · outbound
This paper cites VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:12.120821Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e54b9f27-0590-4e6d-b7d4-57ac29bbd53b · outbound
This paper cites Let’s verify step by step.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Let’s verify step by step
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:12.167318Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e962be59-6051-4662-b6ca-b4f3a45d3b9e · outbound
This paper cites Visual-RFT: Visual Reinforcement Fine-Tuning.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Visual-RFT: Visual Reinforcement Fine-Tuning
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:12.227193Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 929c53b7-30e9-4924-bd77-7fa1adf09ad0 · outbound
This paper cites MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:12.317088Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 463aad97-165e-47ee-95e4-5c492569d533 · outbound
This paper cites MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:23.084340Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c097e315-49c3-4fed-a816-21edd16b6721 · outbound
This paper cites Introducing gemini 2.0: our new ai model for the agentic era, 2024.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Introducing gemini 2.0: our new ai model for the agentic era, 2024
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:40:58.900706Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 69971c8d-693e-4318-ba6c-b3316bc9db5f · outbound
This paper cites Proximal Policy Optimization Algorithms.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Proximal Policy Optimization Algorithms
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:23.659852Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f77a72e1-7acc-4f7a-a6fb-89a92ca927ce · outbound
This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:24.131641Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9e13b280-d600-4202-a8e2-37e22e721598 · outbound
This paper cites VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:31.437137Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ecbc943e-6897-4c25-9e4d-093006c3b49f · outbound
This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:32.880469Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 077385f6-de87-4489-81d0-4e9c4156c2e3 · outbound
This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Kimi k1.5: Scaling Reinforcement Learning with LLMs
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:34.931386Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ce95458a-a9b4-41d5-8105-9a804e398998 · outbound
This paper cites LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:35.727219Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c314e2d9-ad47-490c-a7b0-549e292d25e3 · outbound
This paper cites Tarsier: Recipes for Training and Evaluating Large Video Description Models.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Tarsier: Recipes for Training and Evaluating Large Video Description Models
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:35.885400Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 835dc834-d0d0-4557-bfba-38afbae77af2 · outbound
This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:35.947370Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c1befbf9-e216-4ae7-bb19-6a771e49d146 · outbound
This paper cites Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:36.023507Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7be61c09-24ad-45a7-95ff-96a0817528a3 · outbound
This paper cites LLaVA-CoT: Let Vision Language Models Reason Step-by-Step.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking LLaVA-CoT: Let Vision Language Models Reason Step-by-Step
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:36.060722Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c42b6749-3580-4a62-b6eb-d81860a6ce66 · outbound
This paper cites CaReBench: A Fine-Grained Benchmark for Video Captioning and Retrieval.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking CaReBench: A Fine-Grained Benchmark for Video Captioning and Retrieval
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:45.357734Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84cb20a6-1314-4606-881c-7b4d6619932a · outbound
This paper cites Qwen2.5 Technical Report.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Qwen2.5 Technical Report
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:53.234744Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e19a02cd-8847-4a5b-b60b-5160165c8c7f · outbound
This paper cites Vript: A video is worth thousands of words.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Vript: A video is worth thousands of words
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:40:58.725983Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation cfe4d595-bfd2-4502-834d-9b58e82f605a · outbound
This paper cites Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:55.543904Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11382a79-e212-483d-acee-0e4633d8e18a · outbound
This paper cites Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:55.873734Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b38cb08a-7b3d-4787-9fca-3455a433d275 · outbound
This paper cites Modeling context in referring expressions.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Modeling context in referring expressions
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:55.915232Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 71e9c9c5-ee26-4ec7-af1a-7aa1e7509853 · outbound
This paper cites Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Tarsier2: Advancing Large Vision-Language Models from Detailed Video Description to Comprehensive Video Understanding
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:55.923555Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 02b25c7c-7ad1-44a4-891f-fc297f035177 · outbound
This paper cites 7b model and 8k examples: Emerging reasoning with reinforcement learning is both effective and efficient.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking 7b model and 8k examples: Emerging reasoning with reinforcement learning is both effective and efficient
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T11:40:58.644904Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation b58ff38f-0a06-422c-942e-7381f7305b9d · outbound
This paper cites Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems? In European Conference on Computer Vision, pages 169–186.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems? In European Conference on Computer Vision, pages 169–186
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:56.019147Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f26bff47-1afe-46bf-aed8-1efb8589414e · outbound
This paper cites Improve Vision Language Model Chain-of-thought Reasoning.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Improve Vision Language Model Chain-of-thought Reasoning
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:57.064569Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 19ab9372-e3a4-457d-8ffd-1ef64bb7114f · outbound
This paper cites LLaVA-Video: Video Instruction Tuning With Synthetic Data.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking LLaVA-Video: Video Instruction Tuning With Synthetic Data
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:57.687621Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bfc7a347-b255-43b6-97df-b3e9738fef0d · outbound
This paper cites R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:57.733558Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 568a8494-8f7a-48f4-b86c-3834ef178039 · outbound
This paper cites MMVU: Measuring Expert-Level Multi-Discipline Video Understanding.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking MMVU: Measuring Expert-Level Multi-Discipline Video Understanding
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:57.775507Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c016390e-52e4-4925-aa35-151145ec6a97 · outbound
This paper cites SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuning.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuning
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:57.810477Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 48094e61-f3c6-4174-be5d-b770a4d99ebe · outbound
This paper cites R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:40:57.860880Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eb5ca7e3-48c9-404b-97c0-cf111daead75 · outbound
This paper cites an unresolved cited work.
VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking Unresolved cited work
Reference 2025
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T11:40:59.416096Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Pith citing papers
Observation e5b183dd-b5a6-4e41-9796-1db3ffebe5ec · inbound
Empowering Multimodal LLMs with External Tools: A Comprehensive Survey cites this paper.
Empowering Multimodal LLMs with External Tools: A Comprehensive Survey VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 292
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T20:29:11.589395Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2c65558d-f0b6-46a8-9c1d-539e9579eef0 · inbound
OwlCap: Harmonizing Motion-Detail for Video Captioning via HMD-270K and Caption Set Equivalence Reward cites this paper.
OwlCap: Harmonizing Motion-Detail for Video Captioning via HMD-270K and Caption Set Equivalence Reward VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T16:58:52.971482Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ff98ddf-19d9-4d22-a939-46b89e999320 · inbound
VIDEOP2R: Video Understanding from Perception to Reasoning cites this paper.
VIDEOP2R: Video Understanding from Perception to Reasoning VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T22:25:22.561845Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 36e73833-b17f-49e4-9a20-48e792f14e45 · inbound
Building a Precise Video Language with Human-AI Oversight cites this paper.
Building a Precise Video Language with Human-AI Oversight VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 44
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:46:04.484250Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation ef22b1aa-0882-4abb-b11b-72a052fbcb76 · inbound
VCap: Hypergeometric Rewards for Weak-to-Strong Visual Captioning cites this paper.
VCap: Hypergeometric Rewards for Weak-to-Strong Visual Captioning VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T13:23:28.493845Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c8439cfd-3612-4e2a-a1f4-fcd335241947 · inbound
Watch, Remember, Reason: Human-View Video Understanding with MLLMs cites this paper.
Watch, Remember, Reason: Human-View Video Understanding with MLLMs VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 94
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T17:27:15.755390Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation b6a4f68f-becd-49ee-a3bc-6334f5766267 · inbound
CineCap: Structured Reasoning with Spatio-Temporal Anchors for Cinematographic Video Captioning cites this paper.
CineCap: Structured Reasoning with Spatio-Temporal Anchors for Cinematographic Video Captioning VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T17:40:00.935800Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 9066af67-d826-4a5c-b0d1-5ef885e470a5 · inbound
From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models cites this paper.
From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 194
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T15:09:54.942635Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation b32ac67e-4cd7-421b-a1e9-b83d10d18411 · inbound
ReBind: Multi-Reference Video Editing via Structured Instructions with Explicit Reference Relationships cites this paper.
ReBind: Multi-Reference Video Editing via Structured Instructions with Explicit Reference Relationships VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T01:27:22.196718Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 32461e25-5782-49b6-a010-1cc41b265953 · inbound
PercepCap: Video Captioner with Structured Spatio-Temporal Perception cites this paper.
PercepCap: Video Captioner with Structured Spatio-Temporal Perception VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T10:02:03.207694Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53fcffc3-aa5f-49b5-ac92-20dd6ee28176 · inbound
AVCap: Reinforcing Audio-Video Joint Caption with Detail-Aware Reward cites this paper.
AVCap: Reinforcing Audio-Video Joint Caption with Detail-Aware Reward VideoCap-R1: Enhancing MLLMs for Video Captioning via Structured Thinking
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T18:13:44.235558Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.