Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 35 inbound Pith citation observations for arXiv:2410.03290.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:35:47.027169Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T15:09:55.249321Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation dcaf2cd8-1f50-401c-83f5-de3f9366e583 · inbound
InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling cites this paper.
InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T02:52:20.775068Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 921a662e-7183-44a5-b656-983f70e2ff53 · inbound
Reinforcement Learning Tuning for VideoLLMs: Reward Design and Data Efficiency cites this paper.
Reinforcement Learning Tuning for VideoLLMs: Reward Design and Data Efficiency Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:35:47.027169Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 67ca3aea-21d9-42f0-82e8-0d874e7f886f · inbound
Scene-R1: Video-Grounded Large Language Models for 3D Scene Reasoning without 3D Annotations cites this paper.
Scene-R1: Video-Grounded Large Language Models for 3D Scene Reasoning without 3D Annotations Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:34:53.529692Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 874431d9-8e44-4c9c-b80f-5fc8a6dcd538 · 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 Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:29:24.133365Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 255843c6-4a7e-4c5c-892f-b71afcacd37b · inbound
IPFormer-VideoLLM: Enhancing Multi-modal Video Understanding for Multi-shot Scenes cites this paper.
IPFormer-VideoLLM: Enhancing Multi-modal Video Understanding for Multi-shot Scenes Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:37:38.924039Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e660d4f9-82e0-4d07-941d-532b62ab2a88 · inbound
Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning cites this paper.
Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:44:28.022951Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cb8d8afd-6d9a-4832-a6ef-ffdc5fd7d998 · inbound
TimeExpert: An Expert-Guided Video LLM for Video Temporal Grounding cites this paper.
TimeExpert: An Expert-Guided Video LLM for Video Temporal Grounding Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:30:36.525254Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cccf61d6-12aa-4df8-8839-8fd1fec4e665 · inbound
"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth cites this paper.
"Harmless to You, Hurtful to Me!": Investigating the Detection of Toxic Languages Grounded in the Perspective of Youth Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 78
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:15:43.184734Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 13f125b0-b270-4d4e-b194-a727aecc27fb · inbound
VLM4D: Towards Spatiotemporal Awareness in Vision Language Models cites this paper.
VLM4D: Towards Spatiotemporal Awareness in Vision Language Models Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 79
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:12:38.429768Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ee27c7d-fb51-4241-8eaf-ef831dfba3f3 · 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 Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T23:32:17.609232Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a9a7e9ff-10cd-4e27-b89f-d12e6896098a · inbound
When and What: Diffusion-Grounded VideoLLM with Entity Aware Segmentation for Long Video Understanding cites this paper.
When and What: Diffusion-Grounded VideoLLM with Entity Aware Segmentation for Long Video Understanding Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T17:50:49.044330Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 41ca1c2b-a3bf-4f21-bef5-9b4434fbc12a · inbound
Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data cites this paper.
Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T10:58:17.747639Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 551d36da-da25-4119-847e-9767d9931db7 · inbound
OneThinker: All-in-one Reasoning Model for Image and Video cites this paper.
OneThinker: All-in-one Reasoning Model for Image and Video Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 79
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T02:11:26.607886Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 19a5d37e-6486-4a8a-b153-7e6e0d905da5 · inbound
Detector-Empowered Video Large Language Model for Efficient Spatio-Temporal Grounding cites this paper.
Detector-Empowered Video Large Language Model for Efficient Spatio-Temporal Grounding Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 61
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:58:46.609124Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 70b78f38-3efd-4918-83b6-718938457278 · 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 Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T08:40:46.375077Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation d164cb4b-ad36-47f8-b0d4-75525aeb73c1 · 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 Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T05:14:23.944562Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a410e7bc-9a09-4f8b-8f2a-e680c85963b4 · inbound
A Multimodal Foundation Model of Spatial Transcriptomics and Histology for Biological Discovery and Clinical Prediction cites this paper.
A Multimodal Foundation Model of Spatial Transcriptomics and Histology for Biological Discovery and Clinical Prediction Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T12:44:39.273341Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d668af7f-8286-4138-881e-afcc6626edbf · inbound
Single-agent vs. Multi-agents for Automated Video Analysis of On-Screen Collaborative Learning Behaviors cites this paper.
Single-agent vs. Multi-agents for Automated Video Analysis of On-Screen Collaborative Learning Behaviors Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 28
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T17:33:02.311291Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 241d4e5e-d9e2-4581-9e32-7c01ee248be4 · inbound
How Should Video LLMs Output Time? An Analysis of Efficient Temporal Grounding Paradigms cites this paper.
How Should Video LLMs Output Time? An Analysis of Efficient Temporal Grounding Paradigms Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T08:05:58.925033Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 6dcc5857-4426-4d94-8fc3-e128035b778b · inbound
Towards Temporal Compositional Reasoning in Long-Form Sports Videos cites this paper.
Towards Temporal Compositional Reasoning in Long-Form Sports Videos Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T19:27:29.843866Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation da6f3052-00a2-46b6-8175-55d420989eb9 · inbound
EvoGround: Self-Evolving Video Agents for Video Temporal Grounding cites this paper.
EvoGround: Self-Evolving Video Agents for Video Temporal Grounding Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T19:32:52.391468Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation ed7acdf5-df22-44a5-a1a3-a99d5d8beb02 · inbound
Video-Zero: Self-Evolution Video Understanding cites this paper.
Video-Zero: Self-Evolution Video Understanding Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T21:35:04.426284Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 8751f1f0-6f57-4225-ae09-27e7d4237a56 · 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 Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T07:14:42.418973Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation e8e66c53-1aa6-462f-8eae-33e353ef4e39 · inbound
LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence cites this paper.
LLaVA-OneVision-2: Towards Next-Generation Perceptual Intelligence Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T22:13:59.520753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation ce3a092a-a93a-41bb-9264-0ca58af703fa · inbound
VidPrism: Heterogeneous Mixture of Experts for Image-to-Video Transfer cites this paper.
VidPrism: Heterogeneous Mixture of Experts for Image-to-Video Transfer Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T13:03:25.917929Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 43060d12-bce0-4242-89ee-08bd37db8ef6 · inbound
Watch, Remember, Reason: Human-View Video Understanding with MLLMs cites this paper.
Watch, Remember, Reason: Human-View Video Understanding with MLLMs Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 66
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T17:27:14.973292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 2f75dce3-b997-4a91-ab51-f7d37bfec2e4 · inbound
Counterfactual Reasoning for Fine-Grained Evidence Disentanglement in VideoQA cites this paper.
Counterfactual Reasoning for Fine-Grained Evidence Disentanglement in VideoQA Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T00:57:30.201488Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation b68500d7-1bc9-4b0c-be33-e5e2f117903b · inbound
InternVideo3: Agentify Foundation Models with Multimodal Contextual Reasoning cites this paper.
InternVideo3: Agentify Foundation Models with Multimodal Contextual Reasoning Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 135
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T10:48:03.119304Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 56cffcb1-b355-4a21-8d17-f5d2b404f5d5 · inbound
Training LLMs with Reinforcement Learning over Digital Twin Representations for Reasoning-Intensive Surgical VideoQA cites this paper.
Training LLMs with Reinforcement Learning over Digital Twin Representations for Reasoning-Intensive Surgical VideoQA Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T17:48:46.270090Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f266c6e2-8f7f-4787-a57c-2c67421b3810 · inbound
NEST: Narrative Event Structures in Time for Long Video Understanding cites this paper.
NEST: Narrative Event Structures in Time for Long Video Understanding Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 16
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T03:29:31.221922Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 069fe2d3-7ff4-4e73-b830-14eee3dafe06 · inbound
From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models cites this paper.
From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 117
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T15:09:55.251092Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation dca9bb31-a4d2-417c-8449-830109fe3267 · inbound
TimeThink: Reasoning with Time for Video LLMs cites this paper.
TimeThink: Reasoning with Time for Video LLMs Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T08:59:46.244502Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 76950a0e-92bb-46e7-a5cc-8355dec280c7 · inbound
VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding cites this paper.
VideoChat3: Fully Open Video MLLM for Efficient and Generalist Video Understanding Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 110
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T00:44:50.709854Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2c1b856a-8498-4fe4-aeb1-ca770c12920d · inbound
TimeLens2: Generalist Video Temporal Grounding with Multimodal LLMs cites this paper.
TimeLens2: Generalist Video Temporal Grounding with Multimodal LLMs Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T18:04:16.246667Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc0bda32-8dbd-402d-9fe7-50afc2fb0e4b · inbound
TimePLE: Rethinking Temporal Representation for Video Temporal Grounding cites this paper.
TimePLE: Rethinking Temporal Representation for Video Temporal Grounding Grounded-VideoLLM: Sharpening Fine-grained Temporal Grounding in Video Large Language Models
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T23:32:53.699768Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.