Paper Citation Record · LEDGER

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No

As of 14 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2608.08315.

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

pith.paper-citation-record.v1
2608.08315 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:13:21.347468Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

verified exact1
verified fuzzy25
unresolved7
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f4370455-d3a7-44e6-8ffb-555f24acd836 · outbound

This paper cites Qwen2.5- vl technical report, 2025.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Qwen2.5- vl technical report, 2025

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.589225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 146a1edd-ebc8-47b1-a4ea-c5942015e36f · outbound

This paper cites TimeMarker: A Versatile Video-LLM for Long and Short Video Understanding with Superior Temporal Localization Ability.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No TimeMarker: A Versatile Video-LLM for Long and Short Video Understanding with Superior Temporal Localization Ability

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T00:13:21.258076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a9cfc4a-82d4-496a-98c0-3b559f30bb01 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-12T00:13:21.261525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c4f7b43-953f-41cb-b3d1-2fd87e90130e · outbound

This paper cites Internvl: Scal- ing up vision foundation models and aligning for generic visual-linguistic tasks.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Internvl: Scal- ing up vision foundation models and aligning for generic visual-linguistic tasks

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.581225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8c9ad2b7-a9c9-4fa9-8386-d75a6fd866a8 · outbound

This paper cites Boundary-aware temporal dy- namic pseudo-supervision pairs generation for zero- shot natural language video localization.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Boundary-aware temporal dy- namic pseudo-supervision pairs generation for zero- shot natural language video localization

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.574994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 25ff8519-019a-4240-b7d4-79f9b0359976 · outbound

This paper cites LLM4VG: Large Language Models Evaluation for Video Grounding.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No LLM4VG: Large Language Models Evaluation for Video Grounding

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-12T00:13:21.393747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 3d808a60-3431-49c2-96cd-e5e1dc81cd1d · outbound

This paper cites Tall: Temporal activity localization via lan- guage query.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Tall: Temporal activity localization via lan- guage query

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.568316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 0f191f38-52b1-4434-b46c-e62bf6de952e · outbound

This paper cites TRACE: Temporal Grounding Video LLM via Causal Event Modeling.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No TRACE: Temporal Grounding Video LLM via Causal Event Modeling

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T00:13:21.276988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5422887-5c32-4b3b-8138-2da02352894b · outbound

This paper cites Vtg-llm: Integrating timestamp knowledge into video llms for enhanced video tempo- ral grounding.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Vtg-llm: Integrating timestamp knowledge into video llms for enhanced video tempo- ral grounding

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.559870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b8136e6d-ccd2-421c-9180-22b306431425 · outbound

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

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Vtimellm: Empower llm to grasp video moments

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.552649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e05c93c2-24b4-493e-a89a-b9ec01d698c6 · outbound

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

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Lita: Language instructed temporal- localization assistant

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.545557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b9058860-27a5-40de-84f5-1693d13c0303 · outbound

This paper cites Granalign: Granularity-aware alignment framework for zero-shot video moment retrieval.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Granalign: Granularity-aware alignment framework for zero-shot video moment retrieval

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.539170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c1368278-c94c-4acb-91a6-878ca53e7f30 · outbound

This paper cites Dense-captioning events in videos.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Dense-captioning events in videos

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.531984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 174a74fd-7cd0-4e71-b284-ec27f283b44b · outbound

This paper cites Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T00:13:21.291693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c462f85-4c67-4865-8d8a-f8b8a7f655ab · outbound

This paper cites Detecting moments and highlights in videos via natural language queries.Advances in Neural Information Processing Systems, 34:11846–11858, 2021.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Detecting moments and highlights in videos via natural language queries.Advances in Neural Information Processing Systems, 34:11846–11858, 2021

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.525896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b8e0bcb6-93c9-40c2-8b3f-4bfb5f079b1c · outbound

This paper cites VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-12T00:13:21.297865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ec53043a-a89c-4557-88d9-a23810dec103 · outbound

This paper cites Evaluating object hallucina- tion in large vision-language models.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Evaluating object hallucina- tion in large vision-language models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.519760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c13c99db-45be-439b-9235-2d83cba45546 · outbound

This paper cites Univer- sal video temporal grounding with generative multi- modal large language models.Advances in Neu- ral Information Processing Systems, 38:64426–64455,.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Univer- sal video temporal grounding with generative multi- modal large language models.Advances in Neu- ral Information Processing Systems, 38:64426–64455,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.512260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation cceff855-71e5-4e6f-ba9a-1e0a21bb342e · outbound

This paper cites Univtg: Towards unified video-language temporal grounding.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Univtg: Towards unified video-language temporal grounding

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.505691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c5d0fda9-42bf-4b91-8434-d9b5c817af67 · outbound

This paper cites Enrich and detect: Video temporal ground- ing with multimodal llms.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Enrich and detect: Video temporal ground- ing with multimodal llms

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.499354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1b6e6aad-a810-4233-808d-653eef6b5a3e · outbound

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

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Momentor: Advancing Video Large Language Model with Fine-Grained Temporal Reasoning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-12T00:13:21.312072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54dbf097-00f9-4d99-931e-a7969e1afc02 · outbound

This paper cites Chatvtg: Video temporal grounding via chat with video dialogue large language models.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Chatvtg: Video temporal grounding via chat with video dialogue large language models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.492610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8887fdb5-cfa2-4fda-a68d-ecd742e93200 · outbound

This paper cites Grounding action descriptions in videos.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Grounding action descriptions in videos

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.486131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1f43cfb5-22ef-4a9d-b78e-a86fdb398536 · outbound

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

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Timechat: A time-sensitive multimodal large language model for long video understanding

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.478275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2f283da1-a739-4f44-bc42-ef5ab8393b3d · outbound

This paper cites HawkEye: Training Video-Text LLMs for Grounding Text in Videos.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No HawkEye: Training Video-Text LLMs for Grounding Text in Videos

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-12T00:13:21.323847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4db2ec45-81ae-4ab3-8a3e-da7b3f6d7a18 · outbound

This paper cites Time-r1: Post- training large vision language model for temporal video grounding.Advances in Neural Information Processing Systems, 38:83330–83364, 2026.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Time-r1: Post- training large vision language model for temporal video grounding.Advances in Neural Information Processing Systems, 38:83330–83364, 2026

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.471445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 424deaef-f576-41d1-a14b-3f8be6894ee3 · outbound

This paper cites Negative sample matters: A renais- sance of metric learning for temporal grounding.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Negative sample matters: A renais- sance of metric learning for temporal grounding

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.461997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 459ba1b0-6648-4086-b995-81b0cb4d3965 · outbound

This paper cites Zero-shot video moment retrieval via off-the-shelf multimodal large language models.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Zero-shot video moment retrieval via off-the-shelf multimodal large language models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.455408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d00a842c-ee51-438b-bfdf-71fdd08c529f · outbound

This paper cites mplug-owl3: Towards long image-sequence under- standing in multi-modal large language models.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No mplug-owl3: Towards long image-sequence under- standing in multi-modal large language models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.446819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f34c7a9e-e391-49f7-8284-507e939154c6 · outbound

This paper cites Time- suite: Improving mllms for long video understanding via grounded tuning.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Time- suite: Improving mllms for long video understanding via grounded tuning

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.439383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1b962534-b04a-4556-9197-c589b18447ef · outbound

This paper cites Learning 2d temporal adjacent networks for moment localization with natural language.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Learning 2d temporal adjacent networks for moment localization with natural language

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.431453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2a6ce923-819b-48ab-8fa0-aec4c9694cec · outbound

This paper cites Llava-next: A strong zero-shot video under- standing model, 2024.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Llava-next: A strong zero-shot video under- standing model, 2024

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.423606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e3804e84-edea-41ef-8d6e-478db517e334 · outbound

This paper cites Omnivtg: A large-scale dataset and training paradigm for open-world video tempo- ral grounding.

Your VLM Already Knows When: Training-Free Temporal Grounding by Asking Yes or No Omnivtg: A large-scale dataset and training paradigm for open-world video tempo- ral grounding

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T00:13:21.413332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.