Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data | Paper Citation Record

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This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 1

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This paper cites Vicas: A dataset for combining holistic and pixel-level video un- derstanding using captions with grounded segmentation.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Vicas: A dataset for combining holistic and pixel-level video un- derstanding using captions with grounded segmentation

Reference 2

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This paper cites Qwen2.5-VL Technical Report.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Qwen2.5-VL Technical Report

Reference 3

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This paper cites PySceneDetect: Video Scene Cut Detection.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data PySceneDetect: Video Scene Cut Detection

Reference 4

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This paper cites Sharegpt4video: Improving video understanding and generation with better captions.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Sharegpt4video: Improving video understanding and generation with better captions

Reference 5

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This paper cites Panda-70m: Captioning 70m videos with multiple cross-modality teachers.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Panda-70m: Captioning 70m videos with multiple cross-modality teachers

Reference 6

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

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 7

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This paper cites VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data VideoLLaMA 2: Advancing Spatial-Temporal Modeling and Audio Understanding in Video-LLMs

Reference 8

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Observation 048c6c3c-bdd1-4fc5-86b3-6ebce32f8450 · outbound

This paper cites PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data PerceptionLM: Open-Access Data and Models for Detailed Visual Understanding

Reference 9

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This paper cites Unifying Specialized Visual Encoders for Video Language Models.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Unifying Specialized Visual Encoders for Video Language Models

Reference 10

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This paper cites Videorefer benchmark evaluation for general mllms.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Videorefer benchmark evaluation for general mllms

Reference 11

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This paper cites Mevis: A large-scale benchmark for video segmentation with motion expressions.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Mevis: A large-scale benchmark for video segmentation with motion expressions

Reference 12

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This paper cites Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis

Reference 13

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Observation c4716635-c7ba-48e6-befe-dd37db008796 · outbound

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Unresolved cited work

Reference 14

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Observation dc4f1d6e-e92b-4609-96e1-011c9c7cfa23 · outbound

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

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Vtg-llm: Integrating timestamp knowledge into video llms for enhanced video temporal grounding

Reference 15

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Observation 239fdc4d-74dd-4aac-8b13-50ca7b2927b2 · outbound

This paper cites Omni-RGPT: Unifying Image and Video Region-level Understanding via Token Marks.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Omni-RGPT: Unifying Image and Video Region-level Understanding via Token Marks

Reference 16

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This paper cites CogVLM2: Visual Language Models for Image and Video Understanding.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data CogVLM2: Visual Language Models for Image and Video Understanding

Reference 17

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

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Vtimellm: Empower llm to grasp video moments

Reference 18

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Observation ca09e8d2-9d88-44e3-bebf-71617c12196e · outbound

This paper cites Tgif-qa: Toward spatio-temporal reasoning in visual question answering.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Tgif-qa: Toward spatio-temporal reasoning in visual question answering

Reference 19

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Observation c7f1e1c6-471c-4efa-b6ad-ef27fa137087 · outbound

This paper cites Referring to any person, 2025.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Referring to any person, 2025

Reference 20

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Observation 8d707d43-44e9-44ae-bad0-275f8ebeb5f5 · outbound

This paper cites Miradata: A large-scale video dataset with long durations and structured captions.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Miradata: A large-scale video dataset with long durations and structured captions

Reference 21

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Observation 64164d42-fc27-40eb-8b7d-6a7dd2404fe1 · outbound

This paper cites Large-scale Pre-training for Grounded Video Caption Generation.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Large-scale Pre-training for Grounded Video Caption Generation

Reference 22

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Observation 490269bf-c118-43c1-9d77-91433c9dc0bd · outbound

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

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Detecting mo- ments and highlights in videos via natural language queries

Reference 23

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data LLaVA-OneVision: Easy Visual Task Transfer

Reference 24

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Observation 565fbcb7-361f-4c0f-a99e-47a1c40b960c · outbound

This paper cites VideoChat: Chat-Centric Video Understanding.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data VideoChat: Chat-Centric Video Understanding

Reference 25

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This paper cites Mvbench: A comprehensive multi-modal video understand- ing benchmark.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Mvbench: A comprehensive multi-modal video understand- ing benchmark

Reference 26

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Observation 5f901906-4b2c-4118-aa92-62de57bd8c5d · outbound

This paper cites Temporal reasoning transfer from text to video.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Temporal reasoning transfer from text to video

Reference 27

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Observation b7e4c9cd-d50d-4af7-8df4-24e422889d97 · outbound

This paper cites Llama-vid: An image is worth 2 tokens in large language models.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Llama-vid: An image is worth 2 tokens in large language models

Reference 28

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Observation 17a543bd-35a1-449b-abf9-58aa9b4c13ea · outbound

This paper cites Describe Anything: Detailed Localized Image and Video Captioning.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Describe Anything: Detailed Localized Image and Video Captioning

Reference 29

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Unleashing hour-scale video train- ing for long video-language understanding

Reference 30

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Perceive Anything: Recognize, Explain, Caption, and Segment Anything in Images and Videos

Reference 31

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 32

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data TempCompass: Do Video LLMs Really Understand Videos?

Reference 33

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This paper cites Groma: Localized visual tokenization for grounding multimodal large language models.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Groma: Localized visual tokenization for grounding multimodal large language models

Reference 34

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Observation a6ad5f79-7adc-411a-9357-50dd0a011a34 · outbound

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

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Video-ChatGPT: Towards Detailed Video Understanding via Large Vision and Language Models

Reference 35

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Point and Ask: Incorporating Pointing into Visual Question Answering

Reference 36

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data PG-Video-LLaVA: Pixel Grounding Large Video-Language Models

Reference 37

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Videoglamm: A large multimodal model for pixel-level vi- sual grounding in videos

Reference 38

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

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Momentor: Advancing Video Large Language Model with Fine-Grained Temporal Reasoning

Reference 39

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Artemis: Towards referential understanding in com- plex videos

Reference 40

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Observation f1ab99bb-d21e-4920-99d6-f9af787c780e · outbound

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Glamm: Pixel grounding large multimodal model

Reference 41

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Observation cd859a89-9070-41aa-871c-aff310a6b94a · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data SAM 2: Segment Anything in Images and Videos

Reference 43

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Observation a4b7911d-4e68-4380-aa44-c84057af99cf · outbound

This paper cites Grounded sam 2: Ground and track anything in videos with grounding dino, florence-2 and sam 2.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Grounded sam 2: Ground and track anything in videos with grounding dino, florence-2 and sam 2

Reference 44

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This paper cites xGen-MM-Vid (BLIP-3-Video): You Only Need 32 Tokens to Represent a Video Even in VLMs.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data xGen-MM-Vid (BLIP-3-Video): You Only Need 32 Tokens to Represent a Video Even in VLMs

Reference 45

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Observation 99bcb17b-27a2-48d3-93ce-16d3844b925f · outbound

This paper cites NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data NumeroLogic: Number Encoding for Enhanced LLMs' Numerical Reasoning

Reference 46

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This paper cites Sama: Towards multi-turn referen- tial grounded video chat with large language models.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Sama: Towards multi-turn referen- tial grounded video chat with large language models

Reference 47

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Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Qwen2.5: A party of foundation models, 2024

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:31.332165Z

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Observation 7214d2b9-9d9e-41f2-8fbf-0bf0ee11b373 · outbound

This paper cites Natural language processing with Python and spaCy: A practical introduction.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Natural language processing with Python and spaCy: A practical introduction

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:31.040447Z

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Observation 41ca1c2b-a3bf-4f21-bef5-9b4434fbc12a · outbound

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

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

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Observation 765d890c-9a71-4e79-97ce-21c300b094b2 · outbound

This paper cites Elysium: Exploring object-level perception in videos via mllm.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Elysium: Exploring object-level perception in videos via mllm

Reference 51

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Observation ff965332-63fc-4e5b-87ca-42b14e74a0f2 · outbound

This paper cites Tarsier: Recipes for training and evaluating large video description models, 2024.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Tarsier: Recipes for training and evaluating large video description models, 2024

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:30.357181Z

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 b15deeb9-3579-48ff-a139-a73346e85ea6 · outbound

This paper cites Language as queries for referring video object segmen- tation.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Language as queries for referring video object segmen- tation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:30.042271Z

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 88627f00-7b73-4104-9607-25201e2aaa50 · outbound

This paper cites LongViTU: Instruction Tuning for Long-Form Video Understanding.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data LongViTU: Instruction Tuning for Long-Form Video Understanding

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-05T10:58:18.003545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21cda32f-45a3-4ae8-a22a-8e9a1467a8ae · outbound

This paper cites Number it: Temporal grounding videos like flipping manga.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Number it: Temporal grounding videos like flipping manga

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:29.734566Z

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 db8b1beb-fc4e-4632-af2d-dd2f0be45627 · outbound

This paper cites Next-qa: Next phase of question-answering to explaining temporal actions.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Next-qa: Next phase of question-answering to explaining temporal actions

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:29.392629Z

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 fca9e09a-1ba7-4a9c-b092-17d5b39bb4d6 · outbound

This paper cites Video question answer- ing via gradually refined attention over appearance and mo- tion.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Video question answer- ing via gradually refined attention over appearance and mo- tion

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:29.082214Z

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 29bf663a-d044-4637-a009-e82cb6143f55 · outbound

This paper cites Pixel- aligned language model.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Pixel- aligned language model

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:28.697397Z

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 fec93ee3-44fe-4d4c-95c9-34e70626e67a · outbound

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

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-05T10:58:18.338413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e49916f7-c529-4d14-8a85-dbf10b8ef374 · outbound

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

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-05T10:58:18.397448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 823bc005-5621-42bd-9c92-70213b7cdcbd · outbound

This paper cites xgen-mm (blip-3): A family of open large multimodal models.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data xgen-mm (blip-3): A family of open large multimodal models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-05T10:58:18.453965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77f0dbfa-cd10-4f3b-99b6-b97953a77307 · outbound

This paper cites List Items One by One: A New Data Source and Learning Paradigm for Multimodal LLMs.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data List Items One by One: A New Data Source and Learning Paradigm for Multimodal LLMs

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-05T10:58:18.485504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98767322-0937-462c-b96f-9cabf0103a4f · outbound

This paper cites Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-05T10:58:18.599712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93f24843-fe72-45a5-b580-731de430261e · outbound

This paper cites Ferret: Refer and Ground Anything Anywhere at Any Granularity.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Ferret: Refer and Ground Anything Anywhere at Any Granularity

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-05T10:58:18.651851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce8cfc46-6dae-45ea-98e2-9f2899656ef4 · outbound

This paper cites Merlin: Empowering multimodal llms with foresight minds.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Merlin: Empowering multimodal llms with foresight minds

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:28.238086Z

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 2ebddabe-83ff-4b38-bf40-e465dcc7d3d2 · outbound

This paper cites Activitynet-qa: A dataset for understanding complex web videos via question answering.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Activitynet-qa: A dataset for understanding complex web videos via question answering

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:27.920430Z

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 9aece6be-3583-454e-8cbd-a93e978b42d7 · outbound

This paper cites Osprey: Pixel un- derstanding with visual instruction tuning.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Osprey: Pixel un- derstanding with visual instruction tuning

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:27.591043Z

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 3a73b83d-ca66-4222-8e4d-56efb146d259 · outbound

This paper cites Videorefer suite: Advancing spatial- temporal object understanding with video llm.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Videorefer suite: Advancing spatial- temporal object understanding with video llm

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:27.131183Z

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 d5d9aa8a-38c1-4266-bf08-5ad6c73145e3 · outbound

This paper cites Sigmoid loss for language image pre-training.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Sigmoid loss for language image pre-training

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:26.785238Z

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 9d81e749-85c4-4ba8-ae83-d53265e10d7d · outbound

This paper cites VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-05T10:58:19.096136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8918d51d-37d9-45ad-be60-d56aad392477 · outbound

This paper cites Llava-grounding: Grounded visual chat with large multimodal models.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Llava-grounding: Grounded visual chat with large multimodal models

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:26.325015Z

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 65a71161-201a-4948-826e-c30a6127c282 · outbound

This paper cites Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Ferret-v2: An Improved Baseline for Referring and Grounding with Large Language Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-05T10:58:19.257522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 103af01e-08d4-495a-a86f-d49e1f4b426e · outbound

This paper cites Gpt4roi: Instruction tuning large language model on region- of-interest.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Gpt4roi: Instruction tuning large language model on region- of-interest

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:25.935731Z

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 0db6e86d-0d55-44b4-8dbc-7acf2127e4cf · outbound

This paper cites Video instruction tuning with synthetic data, 2024.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Video instruction tuning with synthetic data, 2024

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:25.520312Z

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 59a300d9-b8e6-4ef6-a34b-318b14e219a4 · outbound

This paper cites VideoExpert: Augmented LLM for Temporal-Sensitive Video Understanding.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data VideoExpert: Augmented LLM for Temporal-Sensitive Video Understanding

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-05T10:58:19.515582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29fb73ab-44d5-4544-b861-1cfecb24fc66 · outbound

This paper cites Frames are extracted only from the seg- ment of the video.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Frames are extracted only from the seg- ment of the video

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:25.072468Z

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 796b7f92-13a3-4030-89cb-11fb6d2ec278 · outbound

This paper cites Sorry, I’m not sure.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Sorry, I’m not sure

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:24.720638Z

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 278c6d5f-1929-483f-8e31-c7a64564ef6a · outbound

This paper cites Frames are extracted only from the seg- ment of the video.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Frames are extracted only from the seg- ment of the video

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:24.365748Z

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 7ad677b9-c848-4f99-9c64-189edb0320df · outbound

This paper cites Yes” or “No.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Yes” or “No

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:23.998339Z

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 7d300569-30cc-4e3d-842d-d40c885d5598 · outbound

This paper cites Frames are extracted from the full video.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Frames are extracted from the full video

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:23.669493Z

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 6bbfbe7e-2d92-4072-90ff-90d6db7ad08a · outbound

This paper cites Frames are extracted from the full video.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Frames are extracted from the full video

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:23.298483Z

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 2f61eb7b-21ac-44fd-b0ec-b3351f8cb620 · outbound

This paper cites Frames are extracted from the full video.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Frames are extracted from the full video

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:22.941919Z

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 5fa46932-f1db-4106-b288-55198e7607f5 · outbound

This paper cites Frames are extracted from the full video.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Frames are extracted from the full video

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:22.613750Z

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 c01a5e71-d7c6-47ad-811f-86fc083866b2 · outbound

This paper cites Frames are extracted from the full video.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Frames are extracted from the full video

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:22.332818Z

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 0c0d1e74-60de-41c2-bae6-e8f3673ee118 · outbound

This paper cites Frames are extracted from the full video.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Frames are extracted from the full video

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:22.033684Z

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 ac81c5fd-500b-46bf-a0ae-bd3438dac2a7 · outbound

This paper cites Frames are extracted from the full video.

Strefer: Empowering Video LLMs with Space-Time Referring and Reasoning via Synthetic Instruction Data Frames are extracted from the full video

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T10:58:21.791400Z

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.

Coverage vector

Reference resolution

Outbound references

Pith citing papers