Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-10T01:43:37.265723Z
Paper Citation Record · LEDGER
OpenCoF: Learning to Reason Through Video Generation
As of 16 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2607.08763.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
50 of 50 outbound references displayed
- verified exact31
- verified fuzzy18
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 9023a7b8-c75c-4c9e-a37d-4b6b650524a3 · outbound
This paper cites Lumiere: A space-time diffusion model for video generation.
OpenCoF: Learning to Reason Through Video Generation Lumiere: A space-time diffusion model for video generation
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.710227Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b0ff4bdc-f080-49a9-bb31-5b9db8fb612d · outbound
This paper cites Mmgr: Multi-modal generative reasoning.
OpenCoF: Learning to Reason Through Video Generation Mmgr: Multi-modal generative reasoning
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.951462Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6891cb1f-3420-475d-9ca0-96b142251f54 · outbound
This paper cites arXiv preprint arXiv:2511.13704 , year=.
OpenCoF: Learning to Reason Through Video Generation arXiv preprint arXiv:2511.13704 , year=
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-10T01:46:40.962721Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation af841a16-d433-4220-9a54-c8c40f4ca6d0 · outbound
This paper cites MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning.
OpenCoF: Learning to Reason Through Video Generation MINT-CoT: Enabling Interleaved Visual Tokens in Mathematical Chain-of-Thought Reasoning
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.976230Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 188fa137-da5c-4ef5-8765-2935a5d615e1 · outbound
This paper cites UniMax: Fairer and more Effective Language Sampling for Large-Scale Multilingual Pretraining.
OpenCoF: Learning to Reason Through Video Generation UniMax: Fairer and more Effective Language Sampling for Large-Scale Multilingual Pretraining
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.957102Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b6fb3e8c-3d45-4037-9f75-6ff610ad38fd · outbound
This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.
OpenCoF: Learning to Reason Through Video Generation Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.941636Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 9c5d7403-a04f-43d1-b567-b3c9a1805600 · outbound
This paper cites G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model.
OpenCoF: Learning to Reason Through Video Generation G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.940154Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation f0a263af-4767-4c36-b6eb-9cd479634827 · outbound
This paper cites Seedance 1.0: Exploring the Boundaries of Video Generation Models.
OpenCoF: Learning to Reason Through Video Generation Seedance 1.0: Exploring the Boundaries of Video Generation Models
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.934444Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b2a5a924-b357-4e98-8ab7-379e66038bf5 · outbound
This paper cites Veo-3 technical report.
OpenCoF: Learning to Reason Through Video Generation Veo-3 technical report
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.708214Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 6463ea4a-889b-4a75-ad3f-e0f17b8412e2 · outbound
This paper cites Are video models ready as zero-shot reasoners? an empirical study with the mme-cof benchmark.
OpenCoF: Learning to Reason Through Video Generation Are video models ready as zero-shot reasoners? an empirical study with the mme-cof benchmark
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.959738Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation cd97e1ec-a4f5-4930-a23c-4cc791835aca · outbound
This paper cites ATLAS: Agentic or Latent Visual Reasoning? One Word is Enough for Both.
OpenCoF: Learning to Reason Through Video Generation ATLAS: Agentic or Latent Visual Reasoning? One Word is Enough for Both
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.964934Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1a65e0b6-ca78-4ed1-a16d-6e96e54fe19b · outbound
This paper cites Ruler-bench: Probing rule-based reasoning abilities of next-level video generation models for vision foundation intelligence.
OpenCoF: Learning to Reason Through Video Generation Ruler-bench: Probing rule-based reasoning abilities of next-level video generation models for vision foundation intelligence
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.957301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation e9e10b7e-e588-4610-9a61-d22cbc2a186f · outbound
This paper cites DeepEyesV2: Toward Agentic Multimodal Model.
OpenCoF: Learning to Reason Through Video Generation DeepEyesV2: Toward Agentic Multimodal Model
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.983972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 11df88a7-3bc2-483d-9b0d-f1daedfc5519 · outbound
This paper cites Lora: Low-rank adaptation of large language models.Iclr, 1(2):3.
OpenCoF: Learning to Reason Through Video Generation Lora: Low-rank adaptation of large language models.Iclr, 1(2):3
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.700940Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5d7a631a-470a-42c3-aee0-a34a45a791fe · outbound
This paper cites Visual sketchpad: Sketching as a visual chain of thought for multimodal language models.Advances in Neural Information Processing Systems, 37:139348–139379.
OpenCoF: Learning to Reason Through Video Generation Visual sketchpad: Sketching as a visual chain of thought for multimodal language models.Advances in Neural Information Processing Systems, 37:139348–139379
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.697171Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 7a8a1784-94f6-4d85-9bb5-47133c928073 · outbound
This paper cites MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency.
OpenCoF: Learning to Reason Through Video Generation MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.945808Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 062dbfca-809a-4311-a779-d6b9b3c251ce · outbound
This paper cites Large language models are zero-shot reasoners.Advancesin neural information processing systems, 35:22199–22213, 2022.
OpenCoF: Learning to Reason Through Video Generation Large language models are zero-shot reasoners.Advancesin neural information processing systems, 35:22199–22213, 2022
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.695293Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c3b4b50d-260e-4c33-8979-ba81089ceac8 · outbound
This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.
OpenCoF: Learning to Reason Through Video Generation HunyuanVideo: A Systematic Framework For Large Video Generative Models
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.978808Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 39325a9b-6503-4a4c-bd97-ab03340701e3 · outbound
This paper cites Kling ai: Next-generation ai creative studio.https://klingai.com/, June 2024.
OpenCoF: Learning to Reason Through Video Generation Kling ai: Next-generation ai creative studio.https://klingai.com/, June 2024
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.702717Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d877ac51-8731-44a6-80f7-fdadc40eac68 · outbound
This paper cites Imagine while Reasoning in Space: Multimodal Visualization-of-Thought.
OpenCoF: Learning to Reason Through Video Generation Imagine while Reasoning in Space: Multimodal Visualization-of-Thought
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.925629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c45ac3be-9ebc-4caf-8d91-1f5861551ca8 · outbound
This paper cites Thinking in frames: How visual context and test-time scaling empower video reasoning.
OpenCoF: Learning to Reason Through Video Generation Thinking in frames: How visual context and test-time scaling empower video reasoning
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.989376Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c86affcc-5c45-4d49-9652-8851960cbdd9 · outbound
This paper cites Beyond the last frame: Process-aware evaluation for generative video reasoning.
OpenCoF: Learning to Reason Through Video Generation Beyond the last frame: Process-aware evaluation for generative video reasoning
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.946670Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a2378171-af96-4dfb-a16e-4a3455e26c58 · outbound
This paper cites Can world simulators reason? Gen-ViRe: A generative visual reasoning benchmark.
OpenCoF: Learning to Reason Through Video Generation Can world simulators reason? Gen-ViRe: A generative visual reasoning benchmark
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.966106Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5ae965ed-4668-48cd-8f50-42c07938ef76 · outbound
This paper cites MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts.
OpenCoF: Learning to Reason Through Video Generation MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.922981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 1c5f7a11-3783-4f99-b1e5-8d4ff7594325 · outbound
This paper cites V-reasonbench: Toward unified reasoning benchmark suite for video generation models.
OpenCoF: Learning to Reason Through Video Generation V-reasonbench: Toward unified reasoning benchmark suite for video generation models
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.954809Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5f7cfce7-c762-4002-8a03-3de86e4b2680 · outbound
This paper cites Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers.
OpenCoF: Learning to Reason Through Video Generation Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.693365Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation b600dee4-f4a6-4258-9d8c-f2576be339ce · outbound
This paper cites MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning.
OpenCoF: Learning to Reason Through Video Generation MM-Eureka: Exploring the Frontiers of Multimodal Reasoning with Rule-based Reinforcement Learning
Reference 27
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.973659Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d97fcd91-3b88-481a-81b3-23eac9c1fee7 · outbound
This paper cites Sora 2 system card.
OpenCoF: Learning to Reason Through Video Generation Sora 2 system card
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.689671Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 3080deb3-be58-474c-8580-5bc03a4d6a93 · outbound
This paper cites Scalable diffusion models with transformers.
OpenCoF: Learning to Reason Through Video Generation Scalable diffusion models with transformers
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.691493Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c8f7bd50-224c-4bc8-9a57-79e870edfdf0 · outbound
This paper cites Mme-cof-pro: Evaluating reasoning coherence in video generative models with text and visual hints.arXiv preprint arXiv:2603.20194, 2026.
OpenCoF: Learning to Reason Through Video Generation Mme-cof-pro: Evaluating reasoning coherence in video generative models with text and visual hints.arXiv preprint arXiv:2603.20194, 2026
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.981614Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c554f99c-a9a5-499b-8b9d-93629e585ffe · outbound
This paper cites U-net: Convolutional networks for biomedical image segmentation.
OpenCoF: Learning to Reason Through Video Generation U-net: Convolutional networks for biomedical image segmentation
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.706478Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 414590e5-777f-4818-ab82-213f3920114d · outbound
This paper cites Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model.
OpenCoF: Learning to Reason Through Video Generation Seedance 1.5 pro: A Native Audio-Visual Joint Generation Foundation Model
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.968677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 5dd83c35-a621-42e2-991b-2ddf1ddccd6e · outbound
This paper cites Seedance 2.0: Advancing Video Generation for World Complexity.
OpenCoF: Learning to Reason Through Video Generation Seedance 2.0: Advancing Video Generation for World Complexity
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.986572Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 754f53a1-1095-4b26-9443-797670817931 · outbound
This paper cites Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning.
OpenCoF: Learning to Reason Through Video Generation Visual cot: Advancing multi-modal language models with a comprehensive dataset and benchmark for chain-of-thought reasoning
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.687949Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 7a687809-ffa1-465a-a467-5f64c2433ae0 · outbound
This paper cites Image editing in gemini just got a major upgrade.
OpenCoF: Learning to Reason Through Video Generation Image editing in gemini just got a major upgrade
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.686062Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 7a5f0106-3f86-4f6b-bd99-dac096f1d38f · outbound
This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.
OpenCoF: Learning to Reason Through Video Generation Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.944092Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation bb2c96df-62fb-4a1f-9510-3665177844d3 · outbound
This paper cites Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063.
OpenCoF: Learning to Reason Through Video Generation Roformer: Enhanced transformer with rotary position embedding.Neurocomputing, 568:127063
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.718006Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation d93dd5b9-05b3-40a7-b701-81dc87bb4625 · outbound
This paper cites Thinking with Video: Video Generation as a Promising Multimodal Reasoning Paradigm.
OpenCoF: Learning to Reason Through Video Generation Thinking with Video: Video Generation as a Promising Multimodal Reasoning Paradigm
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.977806Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4320165e-6448-49aa-b662-beb1d6a27e8e · outbound
This paper cites Attention is all you need.Advancesin neural information processing systems, 30.
OpenCoF: Learning to Reason Through Video Generation Attention is all you need.Advancesin neural information processing systems, 30
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.712067Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 15fceebf-d8b6-4570-8021-90f0cf75f9c5 · outbound
This paper cites Bridgedata v2: A dataset for robot learning at scale.
OpenCoF: Learning to Reason Through Video Generation Bridgedata v2: A dataset for robot learning at scale
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.713777Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 9e5b6d57-8719-429f-8121-96e685de7bcd · outbound
This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.
OpenCoF: Learning to Reason Through Video Generation Wan: Open and Advanced Large-Scale Video Generative Models
Reference 41
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.980174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation dc76d491-4e59-4cb6-baca-d3a1fae1a3e1 · outbound
This paper cites A very big video reasoning suite.
OpenCoF: Learning to Reason Through Video Generation A very big video reasoning suite
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.919795Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 2b3fc277-3f0b-4234-93cf-8483a272a386 · outbound
This paper cites Chain-of-thought prompting elicits reasoning in large language models.Advancesin neural information processing systems, 35:24824–24837.
OpenCoF: Learning to Reason Through Video Generation Chain-of-thought prompting elicits reasoning in large language models.Advancesin neural information processing systems, 35:24824–24837
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.715805Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 8657b9ef-67e8-4500-a5f8-38582f8953d2 · outbound
This paper cites Video models are zero-shot learners and reasoners.
OpenCoF: Learning to Reason Through Video Generation Video models are zero-shot learners and reasoners
Reference 44
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.972750Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c0047a30-0832-4b0f-8df6-e7a5a46116af · outbound
This paper cites HunyuanVideo 1.5 Technical Report.
OpenCoF: Learning to Reason Through Video Generation HunyuanVideo 1.5 Technical Report
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.933515Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 885deb5a-6120-4ae8-906b-f0a07f982aaa · outbound
This paper cites Visual planning: Let’s think only with images.
OpenCoF: Learning to Reason Through Video Generation Visual planning: Let’s think only with images
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.960034Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation cba367d6-33e6-403f-9bf3-ca666b0c4672 · outbound
This paper cites Reasoning via video: The first evaluation of video models’ reasoning abilities through maze-solving tasks.
OpenCoF: Learning to Reason Through Video Generation Reasoning via video: The first evaluation of video models’ reasoning abilities through maze-solving tasks
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-07-10T01:46:40.949249Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation fe13e993-bead-430a-8d8a-d06b6f3d0e08 · outbound
This paper cites R1-onevision: Advancing generalized multimodal reasoning through cross-modal formalization.
OpenCoF: Learning to Reason Through Video Generation R1-onevision: Advancing generalized multimodal reasoning through cross-modal formalization
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.699135Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 4627b822-39cc-4b87-984d-7413f66e04e2 · outbound
This paper cites Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems? ECCV 2024, 2024.
OpenCoF: Learning to Reason Through Video Generation Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems? ECCV 2024, 2024
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-10T01:46:41.704599Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation a231b1ce-35ce-4484-963e-8c973cf20d25 · outbound
This paper cites DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning.
OpenCoF: Learning to Reason Through Video Generation DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning
Reference 50
- Resolution
- verified exact
- local_arxiv, observed 2026-07-10T01:46:40.971205Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Pith citing papers
No inbound Pith citation observations are available.