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Paper Citation Record · LEDGER

TimeRefine: Temporal Grounding with Time Refining Video LLM

As of 12 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 4 inbound Pith citation observations for arXiv:2412.09601.

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

pith.paper-citation-record.v1
2412.09601 v2

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:57:35.860530Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:32:17.973013Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T00:35:10.177115Z

Reference resolution

25 of 25 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation df98f553-306c-4467-afb2-788d9e1aae73 · outbound

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

TimeRefine: Temporal Grounding with Time Refining Video LLM VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding

Reference 8

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:57:35.770247Z digest=sha256:e89c5c3079e80370a2f25ae99d84d58f99e1f482938e8575c2f5836a1618f2cc

Observation b17ce03f-2bce-40b8-b126-65b0d23266d8 · outbound

This paper cites LITA: Language Instructed Temporal-Localization Assistant.

TimeRefine: Temporal Grounding with Time Refining Video LLM LITA: Language Instructed Temporal-Localization Assistant

Reference 9

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source=pdf_text observed=2026-08-11T16:57:35.775493Z digest=sha256:bcf77ddeb42ee9e57dd2c3e3dc413e2c33455bf27a3783a689c119f397a1fdb1

Observation 7196a738-8449-467c-9ea5-e1a851bcd4ac · outbound

This paper cites TVQA+: Spatio-Temporal Grounding for Video Question Answering.

TimeRefine: Temporal Grounding with Time Refining Video LLM TVQA+: Spatio-Temporal Grounding for Video Question Answering

Reference 10

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source=pdf_text observed=2026-08-11T16:57:35.780791Z digest=sha256:cb6e3f7e07f9d3c675f532f1a277b0c452cd1fc9ff03ddf6d9c4f87e635aa681

Observation e25ae273-b957-48ed-afc9-2dfb0c72b653 · outbound

This paper cites Correlation-Guided Query-Dependency Calibration for Video Temporal Grounding.

TimeRefine: Temporal Grounding with Time Refining Video LLM Correlation-Guided Query-Dependency Calibration for Video Temporal Grounding

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:57:35.795752Z digest=sha256:fb6affdacde945afaa099a19dac6bbd4f6b17009b6376883ea45f2fe148292ba

Observation f76efc7b-8cc1-4d3b-85c2-035cd7590ecc · outbound

This paper cites Momentor: Advancing Video Large Language Model with Fine-Grained Temporal Reasoning.

TimeRefine: Temporal Grounding with Time Refining Video LLM Momentor: Advancing Video Large Language Model with Fine-Grained Temporal Reasoning

Reference 14

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source=pdf_text observed=2026-08-11T16:57:35.801324Z digest=sha256:009ae8d4a759149320a605d9c0ec9dbd106b591b03b7b4a8ee2cdcb2c2ac8b82

Observation 8998de24-92f8-4c51-aa20-de6d5926d243 · outbound

This paper cites ChatVTG: Video Temporal Grounding via Chat with Video Dialogue Large Language Models.

TimeRefine: Temporal Grounding with Time Refining Video LLM ChatVTG: Video Temporal Grounding via Chat with Video Dialogue Large Language Models

Reference 15

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local_arxiv, observed 2026-08-11T16:57:36.074996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T16:57:35.807184Z digest=sha256:a33c23e409ee1d18dc3c07b73c36d823f5df88926df23bb4ff75d171e65f4701

Observation 065f674e-98af-40fe-97fb-9eae4e944938 · outbound

This paper cites YOLOv3: An Incremental Improvement.

TimeRefine: Temporal Grounding with Time Refining Video LLM YOLOv3: An Incremental Improvement

Reference 16

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source=pdf_text observed=2026-08-11T16:57:35.813089Z digest=sha256:58b0754be953f241e92b6139bc2d6f783fbc0274b8cd4485a368b2fd51f2e9b3

Observation ea0a74f8-4d5a-44a4-901b-8df6eb668c35 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

TimeRefine: Temporal Grounding with Time Refining Video LLM LLaMA: Open and Efficient Foundation Language Models

Reference 17

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source=pdf_text observed=2026-08-11T16:57:35.818699Z digest=sha256:7dbc05693bd6fe2b709cf5d31bc812b0679accc42759d029e186b91bb1a9737f

Observation 74709ae5-d8b7-44ef-b5d4-879875b5159b · outbound

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

TimeRefine: Temporal Grounding with Time Refining Video LLM STAR: A Benchmark for Situated Reasoning in Real-World Videos

Reference 20

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:57:35.833457Z digest=sha256:f1946cadab0a3de6d5a4914abb5c2e1f05c8f06ced6812c544e6ba55dae21d03

Observation 5d3fa0c7-8f6a-4bcc-9baa-11bb3ec0edc0 · outbound

This paper cites When, Where, and What? A New Dataset for Anomaly Detection in Driving Videos.

TimeRefine: Temporal Grounding with Time Refining Video LLM When, Where, and What? A New Dataset for Anomaly Detection in Driving Videos

Reference 21

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source=pdf_text observed=2026-08-11T16:57:35.839149Z digest=sha256:9e04f0d40dd66bb0a23e5720f8622fddbdad28463d6a6ae9ca613da9bdb9a189

Observation bc418ab9-203b-4948-a194-3c8b11d3d805 · outbound

This paper cites TimeSuite: Improving MLLMs for Long Video Understanding via Grounded Tuning.

TimeRefine: Temporal Grounding with Time Refining Video LLM TimeSuite: Improving MLLMs for Long Video Understanding via Grounded Tuning

Reference 23

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source=pdf_text observed=2026-08-11T16:57:35.850058Z digest=sha256:100711f7c0fec4993195d7b82537945226e1b8b3bd77fde9c579196ad7ffc8ce

Observation 75aa75ca-243a-4f94-b085-ce7444ec8143 · outbound

This paper cites Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding.

TimeRefine: Temporal Grounding with Time Refining Video LLM Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 24

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source=pdf_text observed=2026-08-11T16:57:35.855457Z digest=sha256:349ddf09078ec6475bf69a07d52e7153bea0f65eafcec60d3fce95fcf2293e2f

Observation b379be4c-bea7-475c-8644-ec978f813055 · outbound

This paper cites Deformable DETR: Deformable Transformers for End-to-End Object Detection.

TimeRefine: Temporal Grounding with Time Refining Video LLM Deformable DETR: Deformable Transformers for End-to-End Object Detection

Reference 25

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no resolver link, observed 2026-08-11T16:57:35.860530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:57:35.860530Z digest=sha256:54d7692bde9a2e8c932be87455b3abb1ca0d5f5911dfbff6af7a14ead96281cd

Observation a7d2c266-bdfc-4b03-a12d-0aaaa7d2ba51 · outbound

This paper cites YOLOv4: Optimal Speed and Accuracy of Object Detection.

TimeRefine: Temporal Grounding with Time Refining Video LLM YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 2005

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:57:35.732267Z digest=sha256:d6c1ee821ba077d0652c74adafbdcc248e8428c1df88be6b3e516267e0e589e7

Observation 8b4c1ca4-fb2c-4738-9353-060cafc9a695 · outbound

This paper cites Soda: Story oriented dense video captioning evaluation framework.

TimeRefine: Temporal Grounding with Time Refining Video LLM Soda: Story oriented dense video captioning evaluation framework

Reference 2010

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verified fuzzy
raw_fallback, observed 2026-08-11T16:57:36.289062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T16:57:35.759301Z digest=sha256:252009b97c28fcd98d0fd27fe39a5d2cc45fb8dbb166e0d0d1ebc251fabe5683

Observation 87372a76-ae68-488f-8336-5c7927f086d5 · outbound

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

TimeRefine: Temporal Grounding with Time Refining Video LLM Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models

Reference 2015

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source=pdf_text observed=2026-08-11T16:57:35.823573Z digest=sha256:713df6255bd7df152285c80a71c3947e3336f0365f19a601311caf2b8160501e

Observation 9e977eae-89dd-403a-a8f7-75fb247a20b7 · outbound

This paper cites Temporally grounding natural sentence in video.

TimeRefine: Temporal Grounding with Time Refining Video LLM Temporally grounding natural sentence in video

Reference 2016

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raw_fallback, observed 2026-08-11T16:57:36.305547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T16:57:35.743208Z digest=sha256:4bbd109543728165342e69a90732bc5837b66f49e4340619608e3a8a9fa2558e

Observation acf6436e-d560-4cda-9f38-85db88791486 · outbound

This paper cites ExCL: Extractive Clip Localization Using Natural Language Descriptions.

TimeRefine: Temporal Grounding with Time Refining Video LLM ExCL: Extractive Clip Localization Using Natural Language Descriptions

Reference 2017

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source=pdf_text observed=2026-08-11T16:57:35.764464Z digest=sha256:d3d471b377bcedfb3d80d393f404e1ac73bdc2652054660a0be8e0ce95b73531

Observation fd22d433-36fd-4676-9c06-eae22651bc0c · outbound

This paper cites ShareGPT4Video: Improving Video Understanding and Generation with Better Captions.

TimeRefine: Temporal Grounding with Time Refining Video LLM ShareGPT4Video: Improving Video Understanding and Generation with Better Captions

Reference 2018

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source=pdf_text observed=2026-08-11T16:57:35.748209Z digest=sha256:9de8fe0f1a4bff8fc1ce63d8431964b012c91c6ce44ae95bcf59fa4228051a1f

Observation cf6b4bd1-f856-4f7d-898c-c5c16a159bb4 · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

TimeRefine: Temporal Grounding with Time Refining Video LLM LLaVA-OneVision: Easy Visual Task Transfer

Reference 2019

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source=pdf_text observed=2026-08-11T16:57:35.785625Z digest=sha256:30333d2a61b288cac0897327da78e02a1262b8e825975f192b0f13d0d9e336d3

Observation 417913bc-8f3e-4386-9cdc-1436180fa458 · outbound

This paper cites Language Models are Few-Shot Learners.

TimeRefine: Temporal Grounding with Time Refining Video LLM Language Models are Few-Shot Learners

Reference 2020

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T16:57:35.738253Z digest=sha256:b82c09999d72a94f164f9701e8d89c872f3ca8b4f7a7bf44f6658a7d534b4e25

Observation 4be33d49-31d4-4359-9df3-28abc5c6f49b · outbound

This paper cites InternVideo2: Scaling Foundation Models for Multimodal Video Understanding.

TimeRefine: Temporal Grounding with Time Refining Video LLM InternVideo2: Scaling Foundation Models for Multimodal Video Understanding

Reference 2021

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source=pdf_text observed=2026-08-11T16:57:35.828529Z digest=sha256:36ab5869a0b0f1ba958a88ddc47d1afded0533837b26978add29ef90802d7b74

Observation 6fc31aaf-9c8e-428e-95d7-2680895b1328 · outbound

This paper cites Llava-next: Improved reasoning, ocr, and world knowledge, January 2024a.

TimeRefine: Temporal Grounding with Time Refining Video LLM Llava-next: Improved reasoning, ocr, and world knowledge, January 2024a

Reference 2022

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verified fuzzy
raw_fallback, observed 2026-08-11T16:57:36.272715Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-11T16:57:35.790869Z digest=sha256:c4321e2f0d23ed14dd7b3c6d58a67cbd08006559ab1581eaf5f54706fe0dc1cf

Observation 4fca2ed9-b2bd-41d8-bda3-ea1ca970c6b5 · outbound

This paper cites Hierarchical Video-Moment Retrieval and Step-Captioning.

TimeRefine: Temporal Grounding with Time Refining Video LLM Hierarchical Video-Moment Retrieval and Step-Captioning

Reference 2023

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source=pdf_text observed=2026-08-11T16:57:35.844726Z digest=sha256:b934fe6d786b8f8578b26e9122d20b5202155074bcb36f864550880bd179b7bc

Observation 12af4f38-b7a9-4177-9dc4-bcafcd9eeecc · outbound

This paper cites Look Closer to Ground Better: Weakly-Supervised Temporal Grounding of Sentence in Video.

TimeRefine: Temporal Grounding with Time Refining Video LLM Look Closer to Ground Better: Weakly-Supervised Temporal Grounding of Sentence in Video

Reference 2024

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source=pdf_text observed=2026-08-11T16:57:35.753985Z digest=sha256:e49e207747b7e8ac939e39d3d2278823c5593cc4c52076e90fc5aba317e64fc5

Pith citing papers

Observation b47ecbd2-5b82-478c-a41b-8c3703a461d1 · inbound

A Survey on Video Temporal Grounding with Multimodal Large Language Model cites this paper.

A Survey on Video Temporal Grounding with Multimodal Large Language Model TimeRefine: Temporal Grounding with Time Refining Video LLM

Reference 113

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source=arxiv_source observed=2026-08-05T23:32:17.973013Z digest=sha256:e516e7e8d711c6d17da5196b9630ed9f2b0ce97c216be7f2694f2fffe5ba974a

Observation 4713ba86-b9c9-472b-bcdb-4835d36892fe · inbound

TemPose-TF-ASF: Two-Stage Bidirectional Stroke Context Fusion for Badminton Stroke Classification cites this paper.

TemPose-TF-ASF: Two-Stage Bidirectional Stroke Context Fusion for Badminton Stroke Classification TimeRefine: Temporal Grounding with Time Refining Video LLM

Reference 29

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verified exact
arxiv_id, observed 2026-05-09T06:35:39.666857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-08T18:17:39.756415Z digest=sha256:12048af5277160fbca83dfb78c5742bd046e2e199382ef91be427757731cce46

Observation 16a8fbe0-5c54-4cf3-9996-6b8a3f463b9c · inbound

TemPose-TF-ASF: Two-Stage Bidirectional Stroke Context Fusion for Badminton Stroke Classification cites this paper.

TemPose-TF-ASF: Two-Stage Bidirectional Stroke Context Fusion for Badminton Stroke Classification TimeRefine: Temporal Grounding with Time Refining Video LLM

Reference 29

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arxiv_id, observed 2026-07-01T00:35:10.178749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T00:32:38.605388Z digest=sha256:7986ac39ee7e953c86b1841c1a87b35b7ef659630c2056ca0324987f06197e5d

Observation a536b478-5223-45eb-a82e-13d608823555 · inbound

TimePLE: Rethinking Temporal Representation for Video Temporal Grounding cites this paper.

TimePLE: Rethinking Temporal Representation for Video Temporal Grounding TimeRefine: Temporal Grounding with Time Refining Video LLM

Reference 32

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source=pdf_text observed=2026-07-31T23:32:54.051270Z digest=sha256:148a4353942c817724c6ce18d66153aab44a09753566f7dc3a4d8c0d99539aac