Paper Citation Record · LEDGER

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition

As of 8 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2506.16701.

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

pith.paper-citation-record.v1
2506.16701 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:42:21.811848Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

43 of 43 outbound references displayed

verified exact0
verified fuzzy34
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b72c9351-9ef0-465e-b48e-f1ce3130d5c8 · outbound

This paper cites Action genome: Actions as compositions of spatio- temporal scene graphs.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Action genome: Actions as compositions of spatio- temporal scene graphs

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.520530Z

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Observation 33a8dfb9-c426-4331-85c2-628f14f2c224 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition OPT: Open Pre-trained Transformer Language Models

Reference 2

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Observation f8c50662-bf37-4081-9d4d-80586bc74098 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 3

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Observation 78e5ac41-9a02-42fd-9a94-117b65d18d08 · outbound

This paper cites Chatgpt-4o, 2024.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Chatgpt-4o, 2024

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.508520Z

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Observation 20c30f0a-6199-46e8-b882-0cbeac9c7b31 · outbound

This paper cites Gemini 2.0 flash, 2024.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Gemini 2.0 flash, 2024

Reference 5

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Observation a01dcf5b-733c-4f47-ad8c-b86ba066d818 · outbound

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

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Qwen2.5- vl technical report, 2025

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.484668Z

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Observation 373aa4ee-a0f3-4b4f-af5b-ad4fc7eb3c53 · outbound

This paper cites Prompting visual-language models for efficient video understanding.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Prompting visual-language models for efficient video understanding

Reference 7

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Observation 239205f9-1874-448e-a453-9ab9238b2366 · outbound

This paper cites Llms are good action recognizers.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Llms are good action recognizers

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.451449Z

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Observation 04db58d5-6d67-424b-bbdd-7b8eff7218e1 · outbound

This paper cites Video-chatgpt: Towards detailed video understanding via large vision and language models.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Video-chatgpt: Towards detailed video understanding via large vision and language models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.430934Z

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Observation d9c25835-2ced-4e4d-8a4c-7fafab3cb869 · outbound

This paper cites M-llm based video frame selec- tion for efficient video understanding.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition M-llm based video frame selec- tion for efficient video understanding

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.418534Z

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Observation 0db42020-bc5d-4b84-bfe1-195443b6a256 · outbound

This paper cites HierarQ: Task-Aware Hierarchical Q-Former for Enhanced Video Understanding.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition HierarQ: Task-Aware Hierarchical Q-Former for Enhanced Video Understanding

Reference 11

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Observation cb149e37-2dad-424f-9e59-0b8fafce6447 · outbound

This paper cites Two-stream con- volutional networks for action recognition in videos.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Two-stream con- volutional networks for action recognition in videos

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.385943Z

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Observation 259051f0-9365-45ca-b031-1b99d5ba3968 · outbound

This paper cites Temporal segment networks for action recognition in videos.IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(11):2740– 2755, 2019.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Temporal segment networks for action recognition in videos.IEEE Transactions on Pattern Analysis and Machine Intelligence, 41(11):2740– 2755, 2019

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.374140Z

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Observation 284c16f2-3140-4f03-9820-0cd072e8dd07 · outbound

This paper cites Learning spatiotemporal features with 3d convolutional networks.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Learning spatiotemporal features with 3d convolutional networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.360639Z

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Observation b1b3f256-2266-4cea-bdc4-10175834fbc6 · outbound

This paper cites Quo vadis, action recognition? A new model and the kinetics dataset.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Quo vadis, action recognition? A new model and the kinetics dataset

Reference 15

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Observation 786b4f0b-98ff-44c7-b9f0-b03b7d76232e · outbound

This paper cites Smeulders.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Smeulders

Reference 16

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Observation 53831e79-1ec1-4d5f-b53d-b1ce24f67bbb · outbound

This paper cites Slowfast networks for video recognition.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Slowfast networks for video recognition

Reference 17

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Observation 64d244a2-55d8-420c-8cd6-4fdb5da3b246 · outbound

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Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Unresolved cited work

Reference 18

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Observation 44aab4ff-dcef-4ac7-9517-6380c2b044cc · outbound

This paper cites Tokenlearner: Adaptive space- time tokenization for videos.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Tokenlearner: Adaptive space- time tokenization for videos

Reference 19

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Observation c3ec7672-fe3d-4eb1-97aa-ee2ba973dbd7 · outbound

This paper cites ConceptNet 5.5: An Open Multilingual Graph of General Knowledge.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition ConceptNet 5.5: An Open Multilingual Graph of General Knowledge

Reference 20

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Observation 0a4e7caf-2a1f-4f04-87ff-69fc0c041152 · outbound

This paper cites ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning

Reference 21

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Observation 6e20bce3-48c2-4f9a-a53b-ae7be4ed1c08 · outbound

This paper cites We- bChild 2.0 : Fine-grained commonsense knowledge distilla- tion.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition We- bChild 2.0 : Fine-grained commonsense knowledge distilla- tion

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.271807Z

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Observation 990f1d3b-7972-4649-bcdb-6f1381f3ae86 · outbound

This paper cites COMET: Com- monsense transformers for automatic knowledge graph con- struction.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition COMET: Com- monsense transformers for automatic knowledge graph con- struction

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.233158Z

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This paper cites Hwang, Liwei Jiang, Ronan Le Bras, Ximing Lu, Sean Welleck, and Yejin Choi.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Hwang, Liwei Jiang, Ronan Le Bras, Ximing Lu, Sean Welleck, and Yejin Choi

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.213346Z

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Observation eb5cccf0-a671-4502-a497-e36f674092a3 · outbound

This paper cites Conditional prompt learning for vision-language models.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Conditional prompt learning for vision-language models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.194019Z

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Observation 6f5971ea-0443-4a1d-95db-f1e2e582866b · outbound

This paper cites Prompt distribution learning.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Prompt distribution learning

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.173041Z

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Observation 7b6802c2-d0dc-4f3b-a310-e6ab3adf4e31 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Learning transferable visual models from natural language supervision

Reference 27

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Observation b9fe3d8f-922b-4af2-a320-e0060a24cc92 · outbound

This paper cites Denseclip: Language-guided dense prediction with context- aware prompting.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Denseclip: Language-guided dense prediction with context- aware prompting

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.151063Z

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Observation 58ea54c6-2266-46b1-8fb9-d96decd84584 · outbound

This paper cites Expanding language-image pretrained models for general video recognition.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Expanding language-image pretrained models for general video recognition

Reference 29

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Observation e16178ab-908b-460c-8c71-61bebae55ae0 · outbound

This paper cites Learning to prompt for continual learning.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Learning to prompt for continual learning

Reference 30

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Observation e60e9bb0-1d7c-461e-a67e-361fec39616a · outbound

This paper cites Visual prompt tuning.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Visual prompt tuning

Reference 31

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Observation 626eb1b9-c04f-45cf-84c3-95f5616aca36 · outbound

This paper cites Videobert: A joint model for video and language representation learning.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Videobert: A joint model for video and language representation learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.096230Z

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Observation f7615d3c-ec66-474b-b69c-708751fcd5ac · outbound

This paper cites Language models are few- shot learners.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Language models are few- shot learners

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.075878Z

Source-reported events for the cited work

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Observation edc83934-8674-4252-8dd8-09a0bd6a8aa6 · outbound

This paper cites Le, and Christo- pher D.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Le, and Christo- pher D

Reference 34

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Observation ad77e2ab-4f84-44c4-9a81-51ecbd5c80a6 · outbound

This paper cites Multimodal few-shot learn- ing with frozen language models.Proc.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Multimodal few-shot learn- ing with frozen language models.Proc

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.042786Z

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Observation 79406379-5f3b-4823-aa3b-eb5e72351b8e · outbound

This paper cites UNIFIEDQA: Crossing format boundaries with a single QA system.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition UNIFIEDQA: Crossing format boundaries with a single QA system

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.019630Z

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Observation e08c08b5-1488-4201-afdf-32b8fcefbaaf · outbound

This paper cites Few-shot text generation with natural language instructions.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Few-shot text generation with natural language instructions

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:22.005297Z

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Observation 67d8d725-f251-4fa0-acce-d060c304a619 · outbound

This paper cites Generating action-conditioned prompts for open-vocabulary video action recognition.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Generating action-conditioned prompts for open-vocabulary video action recognition

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:21.987818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2e59d9d7-4bd7-43b6-9229-22b0bd086f9c · outbound

This paper cites Kronecker mask and interpretive prompts are language-action video learners.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Kronecker mask and interpretive prompts are language-action video learners

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:21.973922Z

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Observation ad2c47ed-e007-499d-bad7-4a94f141ceae · outbound

This paper cites Visual semantic role labeling for video understanding.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Visual semantic role labeling for video understanding

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:21.960619Z

Source-reported events for the cited work

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Observation 8d9974a3-f7ec-40c7-b23f-fb6a181a81b6 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Learning Transferable Visual Models From Natural Language Supervision

Reference 41

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Observation cb55a17d-2ff0-4de0-9d46-7fc584a684b9 · outbound

This paper cites Flava: A foundational language and vision alignment model.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Flava: A foundational language and vision alignment model

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:42:21.947281Z

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Observation 83e83f57-78f2-4534-b8fb-0af7dffdfdea · outbound

This paper cites Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding.

Language-driven Description Generation and Common Sense Reasoning for Video Action Recognition Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T23:42:21.811848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.