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Paper Citation Record · LEDGER

Reinforcing Video Reasoning with Focused Thinking

As of 21 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 8 inbound Pith citation observations for arXiv:2505.24718.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.24718 v3

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:22:14.226407Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:21:12.278852Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T17:27:15.553972Z

Reference resolution

41 of 41 outbound references displayed

  • verified exact0
  • verified fuzzy6
  • unresolved35
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c9badecf-09ff-4624-b35a-5e04c047cb19 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Reinforcing Video Reasoning with Focused Thinking DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 1

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source=pdf_text observed=2026-08-07T12:22:10.960839Z digest=sha256:4817d4798477f995744b4947400292002a0605bc650557873d9e2de73db3572c

Observation d4ce1a9a-d3b4-49aa-9a09-05aed9e84c1f · outbound

This paper cites R1-v: Reinforcing super generalization ability in vision-language models with less than $3,.

Reinforcing Video Reasoning with Focused Thinking R1-v: Reinforcing super generalization ability in vision-language models with less than $3,

Reference 2

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source=pdf_text observed=2026-08-07T12:22:11.084671Z digest=sha256:ffd62a81b833891e9c95ace0a0eeace628dd65e0418c96e62227a3ddcbdb8432

Observation a8d80d51-c2f5-47cb-a6a5-1ac8e721ad9f · outbound

This paper cites Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.

Reinforcing Video Reasoning with Focused Thinking Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 3

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Observation def96e6b-1f53-4bcc-84cc-98fe0f272012 · outbound

This paper cites MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning.

Reinforcing Video Reasoning with Focused Thinking MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning

Reference 4

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source=pdf_text observed=2026-08-07T12:22:11.241111Z digest=sha256:82dfdfdbce7d3070e5dc1e44f3405e1c254ba8479ccc6e6be8967e9eda57d6c0

Observation 9cef48be-5148-48ee-8727-049a8ab0dbc7 · outbound

This paper cites R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model.

Reinforcing Video Reasoning with Focused Thinking R1-Zero's "Aha Moment" in Visual Reasoning on a 2B Non-SFT Model

Reference 5

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source=pdf_text observed=2026-08-07T12:22:11.311509Z digest=sha256:eb1d133870dec62f64e31a5fc51175717982f2a7ce6e386547f8ea341b0e2e6a

Observation 77cdd7ca-ef91-47f0-b384-caf56fe79085 · outbound

This paper cites LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL.

Reinforcing Video Reasoning with Focused Thinking LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL

Reference 6

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source=pdf_text observed=2026-08-07T12:22:11.359058Z digest=sha256:70052d198c4f817f4e9079d2a9ae14af8b290800c91b63eeb2fa1224bfa4f2d5

Observation 11a643dc-ec93-43fe-ac47-f4c49d1f0933 · outbound

This paper cites Video-R1: Reinforcing Video Reasoning in MLLMs.

Reinforcing Video Reasoning with Focused Thinking Video-R1: Reinforcing Video Reasoning in MLLMs

Reference 7

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source=pdf_text observed=2026-08-07T12:22:11.399735Z digest=sha256:1837a6a7667c43acbe360fb0b292dab3cb5798e9f8628bfe0e128a4c2e57cd86

Observation 7c4361f0-b713-4b46-a04a-8ee3ac1a028f · outbound

This paper cites VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning.

Reinforcing Video Reasoning with Focused Thinking VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning

Reference 8

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Observation 9a269062-f33e-4c8c-8661-ef6baf68d974 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Reinforcing Video Reasoning with Focused Thinking DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 9

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source=pdf_text observed=2026-08-07T12:22:11.489252Z digest=sha256:b206c035085f674dc46e53444efb71578116a43af07f6d0223d781233cc79311

Observation 9f385f3f-9ae7-46d2-8098-d70880665cf6 · outbound

This paper cites MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency.

Reinforcing Video Reasoning with Focused Thinking MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency

Reference 10

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Observation 3c644961-f39d-4b35-85d2-385fb0255c0c · outbound

This paper cites R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization.

Reinforcing Video Reasoning with Focused Thinking R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization

Reference 11

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Observation 39800715-77d3-4a6b-8dcb-9616d86a5364 · outbound

This paper cites CLEVRER: CoLlision Events for Video REpresentation and Reasoning.

Reinforcing Video Reasoning with Focused Thinking CLEVRER: CoLlision Events for Video REpresentation and Reasoning

Reference 12

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source=pdf_text observed=2026-08-07T12:22:11.671883Z digest=sha256:19d006459632a70832079c400d2266b5446e650fc29c76776ad189b6d0bfcd3b

Observation 63dc5c0e-fd1e-4515-8820-7df1a7617a02 · outbound

This paper cites Can i trust your answer? visually grounded video ques- tion answering,.

Reinforcing Video Reasoning with Focused Thinking Can i trust your answer? visually grounded video ques- tion answering,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T12:22:11.761989Z digest=sha256:a39f9acec149e5d295f53648a454547995aec8fd99af6c3feae8be244ba80d3b

Observation b10404a4-85df-4172-9be5-4bc22869d712 · outbound

This paper cites MMVU: Measuring Expert-Level Multi-Discipline Video Understanding.

Reinforcing Video Reasoning with Focused Thinking MMVU: Measuring Expert-Level Multi-Discipline Video Understanding

Reference 14

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Observation 76b2b73f-acf5-4bf4-b0e6-2208a7941102 · outbound

This paper cites OpenAI o1 System Card.

Reinforcing Video Reasoning with Focused Thinking OpenAI o1 System Card

Reference 15

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source=pdf_text observed=2026-08-07T12:22:11.951541Z digest=sha256:cf1a6f99d8cbee4eab5a46f1634cb3e5c2f770e020db417e99d657679ee80311

Observation 8070ccbe-b763-47b6-b467-3b9d0d7c8850 · outbound

This paper cites Secrets of RLHF in Large Language Models Part I: PPO.

Reinforcing Video Reasoning with Focused Thinking Secrets of RLHF in Large Language Models Part I: PPO

Reference 16

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source=pdf_text observed=2026-08-07T12:22:12.045876Z digest=sha256:5739db2c9dffdb98efc00526dbb15b003cbac22fae2b5a9f546bbce31fef6c9d

Observation 0613e258-0573-4692-ae18-f61740a8bef4 · outbound

This paper cites Vision-R1: Evolving Human-Free Alignment in Large Vision-Language Models via Vision-Guided Reinforcement Learning.

Reinforcing Video Reasoning with Focused Thinking Vision-R1: Evolving Human-Free Alignment in Large Vision-Language Models via Vision-Guided Reinforcement Learning

Reference 17

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source=pdf_text observed=2026-08-07T12:22:12.120909Z digest=sha256:c963ed0f5a4b85e1c971a093a4a02e28b62f1a0731e00371c7ab5629a36e2e45

Observation 7b4aba80-d73a-4225-914e-cd2b8ce53e20 · outbound

This paper cites SEED-GRPO: Semantic Entropy Enhanced GRPO for Uncertainty-Aware Policy Optimization.

Reinforcing Video Reasoning with Focused Thinking SEED-GRPO: Semantic Entropy Enhanced GRPO for Uncertainty-Aware Policy Optimization

Reference 18

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Observation 8a5119cd-5d9d-4291-8035-90a5405ecd91 · outbound

This paper cites VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs.

Reinforcing Video Reasoning with Focused Thinking VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

Reference 19

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Observation 868cd186-217e-47e2-9345-540ad555343e · outbound

This paper cites Audio-Visual LLM for Video Understanding.

Reinforcing Video Reasoning with Focused Thinking Audio-Visual LLM for Video Understanding

Reference 20

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source=pdf_text observed=2026-08-07T12:22:12.360528Z digest=sha256:26a6b57751790d7c5e0ce00373424b05f791d5ebf4ffa17f3b9836fabe7a0892

Observation 1be92ba5-8340-4a3b-9337-dce1fb7f4931 · outbound

This paper cites Visa: Reasoning video object segmentation via large language models,.

Reinforcing Video Reasoning with Focused Thinking Visa: Reasoning video object segmentation via large language models,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T12:22:12.453345Z digest=sha256:eb94c2af7341a4cdd441259362112db6005af569ba9f604a9078e7217d6836c5

Observation 87bdd1af-243d-4b5e-b13e-7a70c8daa3c9 · outbound

This paper cites Will Pre-Training Ever End? A First Step Toward Next-Generation Foundation MLLMs via Self-Improving Systematic Cognition.

Reinforcing Video Reasoning with Focused Thinking Will Pre-Training Ever End? A First Step Toward Next-Generation Foundation MLLMs via Self-Improving Systematic Cognition

Reference 22

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source=pdf_text observed=2026-08-07T12:22:12.546086Z digest=sha256:51bc2fab4324115ffc65825950a1c968a6c5c122c1d91dd1756fb359b35451f2

Observation 7bd86063-dc8f-43ee-b910-3d8236c3ae10 · outbound

This paper cites LLaVA-UHD v2: an MLLM Integrating High-Resolution Semantic Pyramid via Hierarchical Window Transformer.

Reinforcing Video Reasoning with Focused Thinking LLaVA-UHD v2: an MLLM Integrating High-Resolution Semantic Pyramid via Hierarchical Window Transformer

Reference 23

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Observation a68fac34-d6bf-45f2-9f76-6ba773877cc4 · outbound

This paper cites Forking Paths in Neural Text Generation.

Reinforcing Video Reasoning with Focused Thinking Forking Paths in Neural Text Generation

Reference 24

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source=pdf_text observed=2026-08-07T12:22:12.716029Z digest=sha256:86539f41e364a566cc9008230369aa677d0d0f33d2c9c0dbebce4b4845f27724

Observation 570faee5-66db-4c4e-812c-0e3a9d8f6b1c · outbound

This paper cites Critical Tokens Matter: Token-Level Contrastive Estimation Enhances LLM's Reasoning Capability.

Reinforcing Video Reasoning with Focused Thinking Critical Tokens Matter: Token-Level Contrastive Estimation Enhances LLM's Reasoning Capability

Reference 25

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source=pdf_text observed=2026-08-07T12:22:12.794644Z digest=sha256:e7b15b39e71de5333653398745084b65961fc99684b55a34c3e5cc26433133d0

Observation 605d6a0f-b46e-45a6-b1fd-25588ab8c0ca · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

Reinforcing Video Reasoning with Focused Thinking DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 26

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Observation 0dc28f2d-2237-4f73-bb25-60c69b46ac44 · outbound

This paper cites Mvbench: A comprehensive multi-modal video understanding benchmark,.

Reinforcing Video Reasoning with Focused Thinking Mvbench: A comprehensive multi-modal video understanding benchmark,

Reference 27

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T12:22:12.956300Z digest=sha256:77b8bd2374b6f30896ca315f67a3d95330198a7d769f34d9032f441498e54ccd

Observation cf3020a1-1f48-4b8c-81aa-788731fa7a08 · outbound

This paper cites TempCompass: Do Video LLMs Really Understand Videos?.

Reinforcing Video Reasoning with Focused Thinking TempCompass: Do Video LLMs Really Understand Videos?

Reference 28

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source=pdf_text observed=2026-08-07T12:22:13.038077Z digest=sha256:ead33007e7235e4fae8f3a0a6de594ed05527edb3b71c357641ebf3b2075d640

Observation bed7a548-6ece-4d28-8108-5f014352f3ba · outbound

This paper cites Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis.

Reinforcing Video Reasoning with Focused Thinking Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis

Reference 29

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source=pdf_text observed=2026-08-07T12:22:13.162144Z digest=sha256:003075fa258a0062f19b67d89bfd79dfb43bf3c3aeb8b19768fb0e1050e8018b

Observation ff5b7fee-4772-452d-8a82-d0de440785c9 · outbound

This paper cites Llama-vid: An image is worth 2 tokens in large language models,.

Reinforcing Video Reasoning with Focused Thinking Llama-vid: An image is worth 2 tokens in large language models,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T12:22:13.236797Z digest=sha256:2307d9e702d19ac79255a718455f0e0266f36866ca6a86a6de7bcb1dcc5f7c9c

Observation 708677d5-b6a1-4e7b-88c6-5af249e4da12 · outbound

This paper cites Long Context Transfer from Language to Vision.

Reinforcing Video Reasoning with Focused Thinking Long Context Transfer from Language to Vision

Reference 31

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source=pdf_text observed=2026-08-07T12:22:13.330350Z digest=sha256:46fc88932a55232218ae1de7a7e7f165ec33920bf4f5ebde96d48a2d6ae5fc8b

Observation 81d94e55-924f-4bef-8a01-09d71e5a273c · outbound

This paper cites Unhackable Temporal Rewarding for Scalable Video MLLMs.

Reinforcing Video Reasoning with Focused Thinking Unhackable Temporal Rewarding for Scalable Video MLLMs

Reference 32

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source=pdf_text observed=2026-08-07T12:22:13.428738Z digest=sha256:dd73f65c58fc3bd7464142c99139c5fde3e6c16c1d7b06b53ed503f2863a3fcb

Observation 6443ad05-adcd-41d2-b2e6-1dc1fa460b2e · outbound

This paper cites Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input.

Reinforcing Video Reasoning with Focused Thinking Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input

Reference 33

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source=pdf_text observed=2026-08-07T12:22:13.508706Z digest=sha256:5f8ea9de87a26a31ce0814201aaf83e7ffa3bd664a8c0fa03c791d25c2fbd97b

Observation ea08b928-4410-4cbe-9613-cb0320456b33 · outbound

This paper cites Qwen2.5-VL Technical Report.

Reinforcing Video Reasoning with Focused Thinking Qwen2.5-VL Technical Report

Reference 34

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source=pdf_text observed=2026-08-07T12:22:13.630605Z digest=sha256:94e25884912b22a973d9fd4e80ba56b8f405de797431e3ce898da5f1415f432a

Observation b23e32ea-f4c2-45bd-a21a-5b55d020807b · outbound

This paper cites STAR: A Benchmark for Situated Reasoning in Real-World Videos.

Reinforcing Video Reasoning with Focused Thinking STAR: A Benchmark for Situated Reasoning in Real-World Videos

Reference 35

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source=pdf_text observed=2026-08-07T12:22:13.702673Z digest=sha256:a90aea8654343160bc79947e6fdffcfa9b31d1a89458ba296efee0876520dcf7

Observation 04fb0489-b2e9-4f57-b528-5d163eb5e669 · outbound

This paper cites The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning.

Reinforcing Video Reasoning with Focused Thinking The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning

Reference 36

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source=pdf_text observed=2026-08-07T12:22:13.785924Z digest=sha256:00662aa5fc73557c4ffc946bda5d0261d42f15920fcb37689bb3494c8d8075a1

Observation faa37307-72ef-439b-9160-a7171164c542 · outbound

This paper cites Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization.

Reinforcing Video Reasoning with Focused Thinking Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization

Reference 37

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unresolved
no resolver link, observed 2026-08-07T12:22:13.915142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:22:13.915142Z digest=sha256:411bc083a354b94eb8bcba7c3401a0550372c6bc8acd4a096eba114cd58583a7

Observation 059a37cd-0a8a-4db3-8832-8abd7abb548e · outbound

This paper cites Learning to Reason without External Rewards.

Reinforcing Video Reasoning with Focused Thinking Learning to Reason without External Rewards

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T12:22:14.022769Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:22:14.022769Z digest=sha256:dbcfa58c80d52572138adcb8473e7eb88e19002ffb0f20937cc08545b81ccf08

Observation 9a939a17-bd5f-4ae7-8863-1005e0f9acf6 · outbound

This paper cites Scalable best-of-n selection for large language models via self-certainty,.

Reinforcing Video Reasoning with Focused Thinking Scalable best-of-n selection for large language models via self-certainty,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T12:22:14.098816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:22:14.098816Z digest=sha256:ccac19254742a87ae6fc8f7891fbb44e8a5c3b515fe1de448c2410efa5825d42

Observation cba31ede-d6d4-4a2b-884f-d19b251f9087 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Reinforcing Video Reasoning with Focused Thinking Proximal Policy Optimization Algorithms

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T12:22:14.151223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:22:14.151223Z digest=sha256:d4d0b04dfceb9b5ddeece002770edf17ce0a8c67b9fcc0e4e879ddfc002c2e41

Observation 9d76de55-bffc-4eba-982d-7a74f3e6c844 · outbound

This paper cites Trl: Transformer reinforcement learning,.

Reinforcing Video Reasoning with Focused Thinking Trl: Transformer reinforcement learning,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:22:14.955173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T12:22:14.226407Z digest=sha256:4bf54e94293dec860477a24f2c73e8ef22b4eecb301202b2db57dcd6aefa2f5a

Pith citing papers

Observation 11ef9459-0e33-44f8-b644-437f7bf2568f · inbound

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models cites this paper.

Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models Reinforcing Video Reasoning with Focused Thinking

Reference 152

Resolution
verified exact
arxiv_id, observed 2026-05-12T08:40:42.109496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-12T08:40:40.910461Z digest=sha256:dcd74bca78a418d01e7f16cca63d6ee08f9be2d39186c567bc6da2257e3de78b

Observation 20a21313-389b-424e-95f4-d4bf0c82cd26 · inbound

Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models cites this paper.

Perception, Reason, Think, and Plan: A Survey on Large Multimodal Reasoning Models Reinforcing Video Reasoning with Focused Thinking

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-15T23:21:12.278852Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T23:21:12.278852Z digest=sha256:a5d1e0a2eb5135db71ba0b0b85f514d6a4d507a18ea469ce2fc622a971b57317

Observation d580f246-b69a-4ce7-9e75-ff8a42927870 · inbound

MUSEG: Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment Grounding cites this paper.

MUSEG: Reinforcing Video Temporal Understanding via Timestamp-Aware Multi-Segment Grounding Reinforcing Video Reasoning with Focused Thinking

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-19T13:17:18.498226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-19T13:13:40.485342Z digest=sha256:40b743d8bafdf72278c9eb83a9faa8a02b0b57d78061061907eaa18d343e7c94

Observation f5846c80-5fad-47c0-a4f5-ee604d4987cf · inbound

MUPA: Towards Multi-Path Agentic Reasoning for Grounded Video Question Answering cites this paper.

MUPA: Towards Multi-Path Agentic Reasoning for Grounded Video Question Answering Reinforcing Video Reasoning with Focused Thinking

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-15T19:00:53.888143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:00:53.888143Z digest=sha256:86cefe0dcc7fe3ceb0a97f901c5dc52265ac8855dad9beceda60a432f7646f47

Observation 64b23fc0-7c1f-43fa-b7cd-ae758657a52e · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models Reinforcing Video Reasoning with Focused Thinking

Reference 101

Resolution
verified exact
arxiv_id, observed 2026-05-18T00:02:25.240758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-18T00:02:24.352947Z digest=sha256:433220927148f779e88d094117840a952183acc6d974dffdbca9b79f79281b98

Observation fa44740c-da3e-4761-9ada-d3c4e94c2d7c · inbound

Watch Before You Answer: Learning from Visually Grounded Post-Training cites this paper.

Watch Before You Answer: Learning from Visually Grounded Post-Training Reinforcing Video Reasoning with Focused Thinking

Reference 17

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T22:20:46.742418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T20:01:13.305374Z digest=sha256:92530f3aa524522c6a1b92c34384a1af4325fbcb7e1c3aff44e113918205852e

Observation 47928768-5cd9-4810-bb8b-6b6ceda6a724 · inbound

Beyond Perceptual Shortcuts: Causal-Inspired Debiasing Optimization for Generalizable Video Reasoning in Lightweight MLLMs cites this paper.

Beyond Perceptual Shortcuts: Causal-Inspired Debiasing Optimization for Generalizable Video Reasoning in Lightweight MLLMs Reinforcing Video Reasoning with Focused Thinking

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:56:06.417753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-09T14:30:56.297653Z digest=sha256:c06f1ca78446a9d8c699f868e66841aef36b338a1cdf407fe227dfc744fe8d38

Observation 836b67cd-9967-44af-b27b-fc1230f82719 · inbound

Watch, Remember, Reason: Human-View Video Understanding with MLLMs cites this paper.

Watch, Remember, Reason: Human-View Video Understanding with MLLMs Reinforcing Video Reasoning with Focused Thinking

Reference 184

Resolution
verified exact
arxiv_id, observed 2026-07-02T17:27:15.555931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T22:00:28.350003Z digest=sha256:064ac52dc9587bf2c0d4c9b53349afe4d0d08c7ecf9a823126a4810e187edd58