Paper Citation Record · LEDGER

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning

As of 19 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2507.18100.

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

pith.paper-citation-record.v1
2507.18100 v1

Coverage vector

measured 46 of 46 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:44:28.083815Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:01:25.879182Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T22:01:26.565617Z

Reference resolution

46 of 46 outbound references displayed

verified exact3
verified fuzzy19
unresolved22
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a90309b3-e264-462c-9cde-41863c5bff52 · outbound

This paper cites Localizing moments in video with natural language.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Localizing moments in video with natural language

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:30.043465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3bd7d84c-35fb-4ddb-9e32-8624023e4357 · outbound

This paper cites Qwen2.5-VL Technical Report.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Qwen2.5-VL Technical Report

Reference 2

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Source-reported events for the cited work

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Observation da08a2d8-c692-46bc-a24a-b359d99bede6 · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 3

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Source-reported events for the cited work

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Observation 148fcb4a-00be-484d-a39d-29b75c0e907d · outbound

This paper cites Fast model debias with machine unlearning.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Fast model debias with machine unlearning

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:30.012237Z

Source-reported events for the cited work

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Observation 2aca0a36-c680-4385-a576-0d18e231c8e0 · outbound

This paper cites Learnable Privacy Neurons Localization in Language Models.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Learnable Privacy Neurons Localization in Language Models

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:44:29.418897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3be719ce-3e73-480f-a0ae-0e7213b8bcaf · outbound

This paper cites Identifying and Mitigating Social Bias Knowledge in Language Models.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Identifying and Mitigating Social Bias Knowledge in Language Models

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:44:29.377369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 84381722-7cc9-4141-988f-97f1899a7d88 · outbound

This paper cites PAD: Personalized Alignment of LLMs at Decoding-Time.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning PAD: Personalized Alignment of LLMs at Decoding-Time

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T14:44:26.722417Z

Source-reported events for the cited work

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Observation 76363f27-e8ef-480b-bd4e-b6012903a9d0 · outbound

This paper cites DiffPO: Diffusion-styled Preference Optimization for Efficient Inference-Time Alignment of Large Language Models.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning DiffPO: Diffusion-styled Preference Optimization for Efficient Inference-Time Alignment of Large Language Models

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:44:29.311823Z

Source-reported events for the cited work

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Observation 6a5632fe-effa-4903-8afa-684e809d0e6f · outbound

This paper cites InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T14:44:26.743203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae0c8376-9632-42d3-9fb5-412f5f57bee3 · outbound

This paper cites FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMs.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMs

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c06c886-8b10-413a-b0cf-01bce557f20a · outbound

This paper cites BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMs.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMs

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65275dc1-f737-4d4b-8f4b-bbe8f3853023 · outbound

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

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Video-R1: Reinforcing Video Reasoning in MLLMs

Reference 12

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Source-reported events for the cited work

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Observation a8a4ed51-9823-426e-998a-af213afef551 · outbound

This paper cites MT-R1-Zero: Advancing LLM-based Machine Translation via R1-Zero-like Reinforcement Learning.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning MT-R1-Zero: Advancing LLM-based Machine Translation via R1-Zero-like Reinforcement Learning

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6ad3123d-5c1b-49ac-933b-58cfde2664d5 · outbound

This paper cites Temporal sen- tence grounding in streaming videos.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Temporal sen- tence grounding in streaming videos

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.988883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation eefa1a95-311c-4e2a-8fb3-21a30bf86986 · outbound

This paper cites Tall: Temporal activity localization via language query.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Tall: Temporal activity localization via language query

Reference 15

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Source-reported events for the cited work

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Observation daeabac4-3b10-414c-99aa-9e9c899c4629 · outbound

This paper cites Ego4D: Around the world in 3,000 hours of egocentric video.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Ego4D: Around the world in 3,000 hours of egocentric video

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.952714Z

Source-reported events for the cited work

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Observation 2575a69a-4235-47a0-b3a9-027d079ba953 · outbound

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

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 17

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Source-reported events for the cited work

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Observation 4ef51bf0-35fb-4327-8a37-2bc633ce22c2 · outbound

This paper cites VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding

Reference 18

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Source-reported events for the cited work

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Observation b2622ada-27f3-4294-8f4f-4bab9e8b8181 · outbound

This paper cites Rus- sell.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Rus- sell

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.933168Z

Source-reported events for the cited work

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Observation 7e2e8a22-2f40-454f-b1a7-f0e3f2219e3d · outbound

This paper cites Rus- sell.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Rus- sell

Reference 21

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Source-reported events for the cited work

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Observation efb29eae-dfc8-4dd3-85bc-a04cf87e4d04 · outbound

This paper cites Rextime: Temporal grounding benchmark for reasoning-intensive videos.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Rextime: Temporal grounding benchmark for reasoning-intensive videos

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.865538Z

Source-reported events for the cited work

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Observation b9c4a670-72c5-4a0f-ade4-c244a179ef6f · outbound

This paper cites Vtimellm: Empower llm to grasp video moments.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Vtimellm: Empower llm to grasp video moments

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.840730Z

Source-reported events for the cited work

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Observation dfaa9457-94d9-46a2-b4b1-dbc93195beb4 · outbound

This paper cites Lita: Language instructed temporal-localization assistant.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Lita: Language instructed temporal-localization assistant

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.806570Z

Source-reported events for the cited work

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Observation 9e3f692e-df7d-4f2b-9fa9-27d95914012e · outbound

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

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 25

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Observation ff6fa5f9-6258-430f-a590-0594ae6f6a44 · outbound

This paper cites Vision-based abnormal event detection in industrial manufacturing processes: A review.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Vision-based abnormal event detection in industrial manufacturing processes: A review

Reference 26

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Observation ee76819b-041a-4516-acef-d66ac2c934d2 · outbound

This paper cites VideoChat: Chat-Centric Video Understanding.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning VideoChat: Chat-Centric Video Understanding

Reference 28

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Source-reported events for the cited work

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Observation 2922b5aa-a159-4c90-9d4c-df27fd5d8a42 · outbound

This paper cites Videomind: A chain-of- lora agent for long video reasoning.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Videomind: A chain-of- lora agent for long video reasoning

Reference 29

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Observation 472e7546-6d6e-4825-bea1-1c087b4cddc9 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Understanding R1-Zero-Like Training: A Critical Perspective

Reference 30

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Observation bae4e109-7ec1-44ba-bb17-9a67a895d85d · outbound

This paper cites Mm-eureka: Exploring visual aha moment with rule-based large-scale reinforcement learning.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Mm-eureka: Exploring visual aha moment with rule-based large-scale reinforcement learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.781046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 6dd05566-7f72-46d3-9fd3-6532bf57abe1 · outbound

This paper cites Queryd: A video dataset with high-quality text and audio narrations.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Queryd: A video dataset with high-quality text and audio narrations

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.757043Z

Source-reported events for the cited work

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Observation 42a335cb-5509-4a9f-9df9-b6756a7ba707 · outbound

This paper cites Training language models to follow instructions with human feedback.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Training language models to follow instructions with human feedback

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.727645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a2754122-ec39-4095-acd2-ee992cf205ec · outbound

This paper cites Momentor: Advancing video large language model with fine-grained temporal reasoning.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Momentor: Advancing video large language model with fine-grained temporal reasoning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.693256Z

Source-reported events for the cited work

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Observation 9effb798-71c0-4ee0-8958-0e039d2cffd0 · outbound

This paper cites Timechat: A time-sensitive multimodal large language model for long video understanding.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Timechat: A time-sensitive multimodal large language model for long video understanding

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.668576Z

Source-reported events for the cited work

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Observation c29b70e7-09f3-4b13-9a59-427efecd68d8 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 36

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Observation a6d2cb88-9574-461b-b008-88b118aaabae · outbound

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

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 37

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Observation d1a79803-5d28-4527-a7c3-8f5b0c6ccf69 · outbound

This paper cites Learning to summarize with human feedback.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Learning to summarize with human feedback

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.642526Z

Source-reported events for the cited work

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Observation b5290e83-3aaa-4961-ac50-c2a0c652807a · outbound

This paper cites Real-world anomaly detection in surveillance videos.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Real-world anomaly detection in surveillance videos

Reference 39

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Observation 81b51efb-d814-4f25-9b49-ef5fa4e68074 · outbound

This paper cites Endonet: A deep architecture for recognition tasks on laparoscopic videos.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Endonet: A deep architecture for recognition tasks on laparoscopic videos

Reference 40

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Source-reported events for the cited work

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Observation e660d4f9-82e0-4d07-941d-532b62ab2a88 · outbound

This paper cites Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models

Reference 41

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Source-reported events for the cited work

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Observation 67e962c9-f402-42cc-accd-73d4f0f5d21b · outbound

This paper cites Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Time-R1: Post-Training Large Vision Language Model for Temporal Video Grounding

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T14:44:28.039862Z

Source-reported events for the cited work

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Observation 59763ee7-6e67-4e6d-b335-f5a1fe341371 · outbound

This paper cites InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation

Reference 43

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Source-reported events for the cited work

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Observation 0ac855aa-bf5d-4241-b934-ad217b4760e0 · outbound

This paper cites Negative sample matters: A renaissance of metric learning for temporal grounding.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Negative sample matters: A renaissance of metric learning for temporal grounding

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.601397Z

Source-reported events for the cited work

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Observation 2624e562-586c-4510-9021-4a9a718ab2a2 · outbound

This paper cites Task preference optimization: Improving multimodal large language models with vision task alignment.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Task preference optimization: Improving multimodal large language models with vision task alignment

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.560717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 73eb49b6-1c4c-4ef8-9b1b-76db014ee429 · outbound

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

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 46

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Source-reported events for the cited work

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Observation fda3be5d-d14e-4c9f-beee-1afb22b586bc · outbound

This paper cites Hierarchical video-moment retrieval and step-captioning.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Hierarchical video-moment retrieval and step-captioning

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.533067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a994773e-d3cc-4a18-8195-f8a332cf21d6 · outbound

This paper cites Easyr1: An efficient, scalable, multi-modality rl training framework.

Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Easyr1: An efficient, scalable, multi-modality rl training framework

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:44:29.504803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

Observation 3f11bd45-d97f-45cc-9b31-38158dba81d2 · inbound

TAR: Temporal Anchor-Constrained Reasoning for Video Temporal Grounding cites this paper.

TAR: Temporal Anchor-Constrained Reasoning for Video Temporal Grounding Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T22:01:26.572230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.