ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos | Paper Citation Record

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This paper cites needle in a haystack.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos needle in a haystack

Reference 1

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Observation 14f8428d-d7b1-4c95-9845-40a18e4758a1 · outbound

This paper cites needle in a haystack.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos needle in a haystack

Reference 2

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This paper cites https://sharegpt.com/.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos https://sharegpt.com/

Reference 3

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This paper cites https://github.com/gkamradt/LLMTest_ NeedleInAHaystack.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos https://github.com/gkamradt/LLMTest_ NeedleInAHaystack

Reference 4

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This paper cites Lo- calizing moments in long video via multimodal guidance.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Lo- calizing moments in long video via multimodal guidance

Reference 5

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Observation 70c6f739-fbc3-4dfb-9a5b-18bf90ef7e20 · outbound

This paper cites Functional brain organization of preparatory attentional control in visual search.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Functional brain organization of preparatory attentional control in visual search

Reference 6

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Observation c3a58dae-6d8d-4df8-9152-0553858fa38f · outbound

This paper cites End-to- end object detection with transformers.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos End-to- end object detection with transformers

Reference 7

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Observation f6a37a7e-6852-4567-ba07-10d991286069 · outbound

This paper cites VideoLLM: Modeling Video Sequence with Large Language Models.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos VideoLLM: Modeling Video Sequence with Large Language Models

Reference 8

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Observation b8ee4b52-d852-41af-b32a-ee00329f0aad · outbound

This paper cites Gonzalez, Ion Stoica, and Eric P.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Gonzalez, Ion Stoica, and Eric P

Reference 9

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Observation 8425f23a-9f25-42db-b812-904a74ca0259 · outbound

This paper cites Bert: Pre-training of deep bidirectional trans- formers for language understanding, 2019.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Bert: Pre-training of deep bidirectional trans- formers for language understanding, 2019

Reference 10

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Observation 7bfc6ce1-d9db-4510-b89a-3b9e40b894c4 · outbound

This paper cites Uatvr: Uncertainty-adaptive text-video retrieval,.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Uatvr: Uncertainty-adaptive text-video retrieval,

Reference 11

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Observation b54cee9a-901a-4e69-b862-fad754abe3e1 · outbound

This paper cites Multi-modal transformer for video retrieval.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Multi-modal transformer for video retrieval

Reference 12

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Observation d59df371-f9dc-4faf-9877-95bd9c219341 · outbound

This paper cites AssistGPT: A General Multi-modal Assistant that can Plan, Execute, Inspect, and Learn.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos AssistGPT: A General Multi-modal Assistant that can Plan, Execute, Inspect, and Learn

Reference 13

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Observation c23fb26c-f5c4-464b-8e35-9534ba353132 · outbound

This paper cites X-pool: Cross-modal language-video attention for text- video retrieval, 2022.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos X-pool: Cross-modal language-video attention for text- video retrieval, 2022

Reference 14

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Observation bc23c703-d543-4919-8f23-5065e7fcfed0 · outbound

This paper cites RGNet: A Unified Clip Retrieval and Grounding Network for Long Videos.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos RGNet: A Unified Clip Retrieval and Grounding Network for Long Videos

Reference 15

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Observation 255d90f0-9d27-4813-ad21-2f1b032353c9 · outbound

This paper cites CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos CONE: An Efficient COarse-to-fiNE Alignment Framework for Long Video Temporal Grounding

Reference 16

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Observation 4395324c-3dd4-4766-adfa-b8ea1ccf4037 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos LoRA: Low-Rank Adaptation of Large Language Models

Reference 17

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Observation 857ffaaa-1626-4923-8342-37e56075e9d4 · outbound

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

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Vtimellm: Empower llm to grasp video moments

Reference 18

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Observation 5760acec-746b-45f6-bfbc-d5a67ef8412f · outbound

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

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos LITA: Language Instructed Temporal-Localization Assistant

Reference 19

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Observation 6e092eaf-b30b-4139-ac67-d61fcb73725d · outbound

This paper cites Audio- enhanced text-to-video retrieval using text-conditioned fea- ture alignment, 2023.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Audio- enhanced text-to-video retrieval using text-conditioned fea- ture alignment, 2023

Reference 20

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This paper cites Efficient long- text understanding with short-text models.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Efficient long- text understanding with short-text models

Reference 21

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Observation 859ddc87-c4f6-4c55-a492-ae3650642b4b · outbound

This paper cites Diffusionret: Generative text-video retrieval with diffusion model, 2023.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Diffusionret: Generative text-video retrieval with diffusion model, 2023

Reference 22

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Observation 7e84c5c3-f984-47f6-8364-31ec71538ba3 · outbound

This paper cites Chat-univi: Unified visual representation em- powers large language models with image and video un- derstanding.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Chat-univi: Unified visual representation em- powers large language models with image and video un- derstanding

Reference 23

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This paper cites Large Language Models Must Be Taught to Know What They Don't Know.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Large Language Models Must Be Taught to Know What They Don't Know

Reference 24

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This paper cites Uncertainty-Aware Evaluation for Vision-Language Models.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Uncertainty-Aware Evaluation for Vision-Language Models

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This paper cites Detecting mo- ments and highlights in videos via natural language queries.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Detecting mo- ments and highlights in videos via natural language queries

Reference 26

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This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 27

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This paper cites VideoChat: Chat-Centric Video Understanding.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos VideoChat: Chat-Centric Video Understanding

Reference 28

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This paper cites Ground- inggpt: Language enhanced multi-modal grounding model.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Ground- inggpt: Language enhanced multi-modal grounding model

Reference 29

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This paper cites Video-LLaVA: Learning United Visual Representation by Alignment Before Projection.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 30

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

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Univtg: Towards unified video- language temporal grounding

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This paper cites Visual Instruction Tuning.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Visual Instruction Tuning

Reference 32

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This paper cites ReLER@ZJU-Alibaba Submission to the Ego4D Natural Language Queries Challenge 2022.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos ReLER@ZJU-Alibaba Submission to the Ego4D Natural Language Queries Challenge 2022

Reference 33

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This paper cites Lost in the Middle: How Language Models Use Long Contexts.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Lost in the Middle: How Language Models Use Long Contexts

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This paper cites Umt: Unified multi-modal transformers for joint video moment retrieval and highlight detection.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Umt: Unified multi-modal transformers for joint video moment retrieval and highlight detection

Reference 35

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Observation ab253223-2440-4d2e-9dcf-5f41221f69d6 · outbound

This paper cites Decoupled weight decay regularization, 2019.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Decoupled weight decay regularization, 2019

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This paper cites Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

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This paper cites Query-dependent video representa- tion for moment retrieval and highlight detection.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Query-dependent video representa- tion for moment retrieval and highlight detection

Reference 38

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Observation ebb83402-3994-44ec-9a7b-18b8f6713bf9 · outbound

This paper cites Snag: Scalable and accurate video grounding.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Snag: Scalable and accurate video grounding

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This paper cites Towards Calibrated Robust Fine-Tuning of Vision-Language Models.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Towards Calibrated Robust Fine-Tuning of Vision-Language Models

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This paper cites Obtaining well calibrated probabilities using bayesian binning.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Obtaining well calibrated probabilities using bayesian binning

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Observation 8c9c6ddd-4e66-4dc0-bd29-dfb737e37993 · outbound

This paper cites Scanning Only Once: An End-to-end Framework for Fast Temporal Grounding in Long Videos.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Scanning Only Once: An End-to-end Framework for Fast Temporal Grounding in Long Videos

Reference 42

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This paper cites Momen- tor: Advancing video large language model with fine-grained temporal reasoning, 2024.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Momen- tor: Advancing video large language model with fine-grained temporal reasoning, 2024

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

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Chatvtg: Video temporal grounding via chat with video dialogue large language models

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Observation 369d7e0f-0aba-4b96-8864-7d0504029881 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Learn- ing transferable visual models from natural language super- vision

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

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Timechat: A time-sensitive multimodal large lan- guage model for long video understanding

Reference 46

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Observation fa1786fc-b54f-462c-9a64-d3e8d146a890 · outbound

This paper cites Vlg-net: Video-language graph matching network for video grounding.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Vlg-net: Video-language graph matching network for video grounding

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This paper cites Mad: A scalable dataset for language grounding in videos from movie audio descriptions.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Mad: A scalable dataset for language grounding in videos from movie audio descriptions

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This paper cites Moviechat: From dense token to sparse memory for long video understanding.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Moviechat: From dense token to sparse memory for long video understanding

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This paper cites Avicuna: Audio-visual llm with interleaver and context- boundary alignment for temporal referential dialogue.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Avicuna: Audio-visual llm with interleaver and context- boundary alignment for temporal referential dialogue

Reference 50

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

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos LLaMA: Open and Efficient Foundation Language Models

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This paper cites ChatVideo: A Tracklet-centric Multimodal and Versatile Video Understanding System.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos ChatVideo: A Tracklet-centric Multimodal and Versatile Video Understanding System

Reference 52

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ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Omnivid: A generative framework for universal video understanding

Reference 53

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Observation f34862bb-cd24-414a-b9a5-ddde6d1215ee · outbound

This paper cites Text is mass: Modeling as stochastic embedding for text-video retrieval, 2024.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Text is mass: Modeling as stochastic embedding for text-video retrieval, 2024

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:51:18.283505Z

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Observation 09b2e3e7-88b7-464a-aabb-3bfc16f0a067 · outbound

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

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos HawkEye: Training Video-Text LLMs for Grounding Text in Videos

Reference 55

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Observation b96e8328-abb2-4c62-89d9-c9ad92851365 · outbound

This paper cites Five factors that guide attention in visual search.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Five factors that guide attention in visual search

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:51:18.270664Z

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Observation 33b0a0e2-eeea-45ab-ba58-bc38164d8fb1 · outbound

This paper cites Msr-vtt: A large video description dataset for bridging video and language.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Msr-vtt: A large video description dataset for bridging video and language

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:51:18.258309Z

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Observation 1a570ca5-d499-4696-9f06-b73cd1f2e861 · outbound

This paper cites PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning

Reference 58

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Observation 3d11ef86-3c09-4298-adee-355fb136229e · outbound

This paper cites SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T14:51:17.699205Z

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Observation 9e40798d-db98-4886-944f-82aedba8fb24 · outbound

This paper cites Clip-vip: Adapting pre- trained image-text model to video-language representation alignment.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Clip-vip: Adapting pre- trained image-text model to video-language representation alignment

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:51:18.247005Z

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Observation 6290a9e5-877f-4046-b121-d32a102f6e91 · outbound

This paper cites Clip-vip: Adapting pre- trained image-text model to video-language representation alignment, 2023.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Clip-vip: Adapting pre- trained image-text model to video-language representation alignment, 2023

Reference 61

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Observation 39f0e8a5-21c9-470e-b485-db4f92b1617e · outbound

This paper cites Vidchapters-7m: Video chapters at scale,.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Vidchapters-7m: Video chapters at scale,

Reference 62

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Observation c9001ed8-d3d1-4cf2-89d8-19583cb0605e · outbound

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ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Vid2seq: Large-scale pretraining of a vi- sual language model for dense video captioning

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:51:18.212240Z

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Observation fe54dfd1-c547-4831-b9f9-96fa5c24a3a1 · outbound

This paper cites Self-chained image-language model for video localization and question answering.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Self-chained image-language model for video localization and question answering

Reference 64

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Observation 6dc5565c-50d5-4e59-9bab-48ea7cf2f19e · outbound

This paper cites A joint se- quence fusion model for video question answering and re- trieval.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos A joint se- quence fusion model for video question answering and re- trieval

Reference 65

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Observation 4db7b359-bc0c-425b-8507-1cbba8219f49 · outbound

This paper cites A sim- ple llm framework for long-range video question-answering,.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos A sim- ple llm framework for long-range video question-answering,

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-12T14:51:17.722170Z

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Observation 11d10cb2-8c7c-4929-a6b0-fef46608327a · outbound

This paper cites Span-based Localizing Network for Natural Language Video Localization.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Span-based Localizing Network for Natural Language Video Localization

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T14:51:17.726089Z

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Observation b79c7ce4-cf4f-45e0-be7b-fba95f2d2af5 · outbound

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

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-12T14:51:17.730863Z

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Observation ed8e90c1-123a-42a6-8552-8f642f137f6f · outbound

This paper cites Learning 2d temporal adjacent networks for moment local- ization with natural language.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Learning 2d temporal adjacent networks for moment local- ization with natural language

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:51:18.179532Z

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Observation 4458d16d-b41f-4419-8d00-ddaebcc8bdbc · outbound

This paper cites Learning video representations from large lan- guage models.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos Learning video representations from large lan- guage models

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:51:18.167474Z

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Observation 6de24dff-be19-4a52-86a4-6078f8679cf5 · outbound

This paper cites <video> Does the <event> happen in the video? Answer yes or no.

ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in Hour-Long Videos <video> Does the <event> happen in the video? Answer yes or no

Reference 4096

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T14:51:18.154762Z

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