Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T19:47:52.748814Z
Paper Citation Record · LEDGER
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning
As of 19 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 4 inbound Pith citation observations for arXiv:2507.04702.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T05:14:24.504509Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T07:14:42.403751Z
Reference resolution
22 of 22 outbound references displayed
- verified exact0
- verified fuzzy8
- unresolved14
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation eba1589a-8b44-45fe-9ff7-1d5f5ffd5a23 · outbound
This paper cites BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset
Reference 3
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1fab5044-b5c9-4c31-91dc-8a0b8170da03 · outbound
This paper cites anthropic.com/news/claude-4.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning anthropic.com/news/claude-4
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:47:53.515466Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ede67f04-834c-4392-9d4d-c9ce9ab07642 · outbound
This paper cites In 2025 IEEE/CVF Winter Conference on Appli- cations of Computer Vision (WACV), 5336–5345.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning In 2025 IEEE/CVF Winter Conference on Appli- cations of Computer Vision (WACV), 5336–5345
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:47:53.476188Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7b018bd8-c39c-406d-854e-8a41c7f3bcc5 · outbound
This paper cites BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models
Reference 11
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c4bc7e62-d089-4692-9099-0801bb3d77e5 · outbound
This paper cites VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:47:52.705443Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5159f353-fda2-4803-b433-6074900cf988 · outbound
This paper cites Improved Baselines with Visual Instruction Tuning.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning Improved Baselines with Visual Instruction Tuning
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:47:52.710694Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8620a1bd-48dd-4d95-9e07-4f8550afea60 · outbound
This paper cites arXiv:2406.18113.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning arXiv:2406.18113
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:47:52.715148Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5898f856-278c-4b78-91c9-7da815dcea0f · outbound
This paper cites https://openai.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning https://openai
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:47:53.399352Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3b7b90da-929e-46a5-a61f-834092662d14 · outbound
This paper cites https:// openai.com/index/introducing-o3-and-o4-mini/.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning https:// openai.com/index/introducing-o3-and-o4-mini/
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:47:53.382284Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 86ca351d-cbe5-4839-afb7-8bd851929189 · outbound
This paper cites arXiv:2505.06589.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning arXiv:2505.06589
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:47:52.728260Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b9429fee-09fc-47cf-8c99-f2f74abd21c6 · outbound
This paper cites InternVideo: General Video Foundation Models via Generative and Discriminative Learning.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning InternVideo: General Video Foundation Models via Generative and Discriminative Learning
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:47:52.732569Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 181b8286-f0e3-43cf-8069-371c4827b030 · outbound
This paper cites Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:47:52.737642Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 16df795f-a496-4bb5-9ed5-9898f8717b98 · outbound
This paper cites arXiv:2408.08872.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning arXiv:2408.08872
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:47:52.742385Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5b099f7e-35c1-4349-a697-ba25452e77cf · outbound
This paper cites Self-Chained Image-Language Model for Video Localization and Question Answering.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning Self-Chained Image-Language Model for Video Localization and Question Answering
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:47:52.748814Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e1fa4dda-2b45-458c-8b61-a3abf578c5a7 · outbound
This paper cites In 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 961–.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning In 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 961–
Reference 2015
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:47:53.432884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e1be29e6-c6fa-4b14-af0d-07368329e29f · outbound
This paper cites In 2017 IEEE International Conference on Computer Vision (ICCV), 5277–5285.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning In 2017 IEEE International Conference on Computer Vision (ICCV), 5277–5285
Reference 2017
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:47:53.450894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1b709416-f6b2-4100-af1b-4e2fbfa7e9fe · outbound
This paper cites In 2019 IEEE/CVF International Conference on Computer Vision (ICCV).
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning In 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
Reference 2019
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:47:53.495153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 277290e8-e626-4bc7-96ec-cd21110b8e3a · outbound
This paper cites QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning QVHighlights: Detecting Moments and Highlights in Videos via Natural Language Queries
Reference 2021
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8f1ccedf-c89b-40bd-a1e3-657f41d1ce3c · outbound
This paper cites BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
Reference 2022
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 633f6e99-21fe-4327-a3f2-03eeae7426be · outbound
This paper cites In 2023 IEEE/CVF International Con- ference on Computer Vision (ICCV), 13800–13810.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning In 2023 IEEE/CVF International Con- ference on Computer Vision (ICCV), 13800–13810
Reference 2023
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T19:47:53.415409Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 3652956f-490d-44b1-9977-cf8b15827807 · outbound
This paper cites arXiv:2410.01615.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning arXiv:2410.01615
Reference 2024
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b944b9fa-d160-4d52-9b7f-a1f5506ad70f · outbound
This paper cites Qwen2.5-VL Technical Report.
Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning Qwen2.5-VL Technical Report
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T19:47:52.231531Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation 68b17250-07ab-4506-9e4d-1cf7e010fee7 · inbound
Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation cites this paper.
Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T08:40:46.399907Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 71b43087-18c0-48a3-b06b-466589877ba1 · inbound
Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation cites this paper.
Video-OPD: Efficient Post-Training of Multimodal Large Language Models for Temporal Video Grounding via On-Policy Distillation Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T05:14:24.504509Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 982094ee-764d-4c30-be45-9d4e1bb08bdc · inbound
MLLMs Know When Before Speaking: Revealing and Recovering Temporal Grounding via Attention Cues cites this paper.
MLLMs Know When Before Speaking: Revealing and Recovering Temporal Grounding via Attention Cues Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T07:14:42.407010Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 261fc88e-489c-437d-9045-bdbcd2663435 · inbound
TimePLE: Rethinking Temporal Representation for Video Temporal Grounding cites this paper.
TimePLE: Rethinking Temporal Representation for Video Temporal Grounding Tempo-R0: A Video-MLLM for Temporal Video Grounding through Efficient Temporal Sensing Reinforcement Learning
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T23:32:54.657297Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.