Paper Citation Record · LEDGER

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation

As of 16 August 2026, this Paper Citation Record lists 100 of 111 outbound references and 4 inbound Pith citation observations for arXiv:2505.12098.

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

pith.paper-citation-record.v1
2505.12098 v1

Coverage vector

measured 100 of 111 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:46:46.420145Z

measured 104 of 104 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:16:47.490821Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:56:59.272327Z

Reference resolution

100 of 111 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 61a35551-7f2a-4690-942f-dad9a23d3306 · outbound

This paper cites A survey of ai text-to-image and ai text-to-video generators,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation A survey of ai text-to-image and ai text-to-video generators,

Reference 1

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Observation 5b8f57f8-2501-4f08-9e6e-c24c02ac98f9 · outbound

This paper cites A survey on video diffusion models,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation A survey on video diffusion models,

Reference 2

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Observation 2e44c3a8-09d5-46dd-9c68-fe981fa4d090 · outbound

This paper cites Evaluation of text-to-video generation models: A dynamics perspective,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Evaluation of text-to-video generation models: A dynamics perspective,

Reference 3

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Observation 15dd866e-086f-4f47-83ab-5347401615be · outbound

This paper cites InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition

Reference 4

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Observation 15736eb3-5dd8-4477-91e5-21bddb86a63b · outbound

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

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation mplug-owl3: Towards long image-sequence understanding in multi-modal large language models,

Reference 5

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Observation 60c06238-d86d-4ead-a420-149f21fbe5ea · outbound

This paper cites LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models

Reference 6

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Observation ca2b3726-1037-499f-9fc2-c8bb07261c1a · outbound

This paper cites Aigv-assessor: Benchmarking and evaluating the perceptual quality of text-to-video generation with lmm,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Aigv-assessor: Benchmarking and evaluating the perceptual quality of text-to-video generation with lmm,

Reference 7

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Observation 99c91dc4-bbf9-4826-bda9-d1e73bff9f72 · outbound

This paper cites Evaluating and improving compositional text-to-visual generation,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Evaluating and improving compositional text-to-visual generation,

Reference 8

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Observation 58aecaa8-fdb7-4a39-826b-71ceb23667e1 · outbound

This paper cites VBench: Comprehensive benchmark suite for video generative models,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation VBench: Comprehensive benchmark suite for video generative models,

Reference 9

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Observation b5ad89dd-09f6-486f-ae60-2f0bf0f1592f · outbound

This paper cites VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation VBench-2.0: Advancing Video Generation Benchmark Suite for Intrinsic Faithfulness

Reference 10

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Observation 9793d22f-e635-431c-aa52-446efa8aa278 · outbound

This paper cites Eval- crafter: Benchmarking and evaluating large video generation models,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Eval- crafter: Benchmarking and evaluating large video generation models,

Reference 11

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Observation a74f312d-709c-426c-86ff-64f71f99afc7 · outbound

This paper cites Fetv: A benchmark for fine- grained evaluation of open-domain text-to-video generation,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Fetv: A benchmark for fine- grained evaluation of open-domain text-to-video generation,

Reference 12

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Observation efe373d1-982b-4f13-be01-6203fd93c494 · outbound

This paper cites Q-Eval-100K: Evaluating Visual Quality and Alignment Level for Text-to-Vision Content.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Q-Eval-100K: Evaluating Visual Quality and Alignment Level for Text-to-Vision Content

Reference 13

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This paper cites Measuring the Quality of Text-to-Video Model Outputs: Metrics and Dataset.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Measuring the Quality of Text-to-Video Model Outputs: Metrics and Dataset

Reference 14

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Observation 47c68798-8b00-467d-a50b-6009b943bfeb · outbound

This paper cites Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model

Reference 15

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Observation c867d89c-cfd2-446f-b1b3-820443e436ff · outbound

This paper cites Subjective-aligned dataset and metric for text-to-video quality assessment,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Subjective-aligned dataset and metric for text-to-video quality assessment,

Reference 16

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Observation c5dddfb8-e313-44b3-80c5-4a77023e37df · outbound

This paper cites Gaia: Rethinking action quality assessment for ai-generated videos,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Gaia: Rethinking action quality assessment for ai-generated videos,

Reference 17

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Observation 5c02f201-e318-4cea-95e2-fbbe8a392221 · outbound

This paper cites LMME3DHF: Benchmarking and Evaluating Multimodal 3D Human Face Generation with LMMs.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation LMME3DHF: Benchmarking and Evaluating Multimodal 3D Human Face Generation with LMMs

Reference 18

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Observation 9be9ceb2-d771-4ee6-8171-43822aac8f3a · outbound

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Quality assessment of in-the-wild videos,

Reference 19

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Observation c41296fd-8525-42d1-ae45-26c8bb5b14cf · outbound

This paper cites A deep learning based no-reference quality assessment model for ugc videos,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation A deep learning based no-reference quality assessment model for ugc videos,

Reference 20

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Fast-vqa: Efficient end-to- end video quality assessment with fragment sampling,

Reference 21

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Observation 491b2055-99c1-4323-b4df-01a08c10689f · outbound

This paper cites Exploring video quality assessment on user generated contents from aesthetic and technical perspectives,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Exploring video quality assessment on user generated contents from aesthetic and technical perspectives,

Reference 22

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Geneval: An object-focused framework for evaluating text-to- image alignment,

Reference 23

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Methodology for the subjective assessment of the quality of television pictures,

Reference 24

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Improved training of wasserstein gans,

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Observation bb565e60-b0e0-4449-8dbb-dc2d3829b8d4 · outbound

This paper cites Towards Accurate Generative Models of Video: A New Metric & Challenges.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 26

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Visual instruction tuning,

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Making a “completely blind

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Aigcoiqa2024: Perceptual quality assessment of ai generated omnidirectional images,

Reference 29

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Finevq: Fine- grained user generated content video quality assessment,

Reference 30

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Quality Assessment for AI Generated Images with Instruction Tuning

Reference 31

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation HarmonyIQA: Pioneering Benchmark and Model for Image Harmonization Quality Assessment

Reference 32

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Blindly assess quality of in-the-wild videos via quality-aware pre-training and motion perception,

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Pick-a-pic: An open dataset of user preferences for text-to-image generation,

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Learning without human scores for blind image quality assessment,

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation No-reference image quality assessment in the spatial domain,

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Jimeng ai

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Vidu ai

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Lora: Low-rank adaptation of large language models,

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Swin transformer: Hierarchical vision transformer using shifted windows,

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Blind image quality estimation via distortion aggravation,

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Blind quality assessment based on pseudo- reference image,

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Blind image quality assessment based on high order statistics aggregation,

Reference 46

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Reference 47

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Blip: Bootstrapping language-image pre-training for unified vision- language understanding and generation,

Reference 48

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Laion-5b: An open large-scale dataset for training next generation image-text models,

Reference 49

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Imagereward: Learning and evaluating human preferences for text-to-image generation,

Reference 50

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LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Human preference score: Better aligning text-to-image models with human preference,

Reference 51

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This paper cites EvalMuse-40K: A Reliable and Fine-Grained Benchmark with Comprehensive Human Annotations for Text-to-Image Generation Model Evaluation.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation EvalMuse-40K: A Reliable and Fine-Grained Benchmark with Comprehensive Human Annotations for Text-to-Image Generation Model Evaluation

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.138692Z

Source-reported events for the cited work

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Observation 05ecb803-3790-4fc2-8c0d-8daf8f1fbfef · outbound

This paper cites DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.142211Z

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Observation 1d4bc4fc-0be7-4b65-a30a-ecc2c620d7b3 · outbound

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

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Video-LLaVA: Learning United Visual Representation by Alignment Before Projection

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.145646Z

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Observation 7c114032-4fad-4103-8b82-879326445598 · outbound

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

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation VideoLLaMA 3: Frontier Multimodal Foundation Models for Image and Video Understanding

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.149232Z

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Observation 9c1e9db0-baf2-4b5d-876e-623b9dd10707 · outbound

This paper cites Qwen2.5-VL Technical Report.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Qwen2.5-VL Technical Report

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.266138Z

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Observation cb615db2-9e93-4f70-85ec-ce592d6f28c0 · outbound

This paper cites Llama 3.2: Revolutionizing edge ai and vision with open, customizable models,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Llama 3.2: Revolutionizing edge ai and vision with open, customizable models,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.285190Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 970e3531-6178-436b-9a17-85be54aa8254 · outbound

This paper cites CogAgent: A Visual Language Model for GUI Agents.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation CogAgent: A Visual Language Model for GUI Agents

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.273001Z

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Observation efe47176-b4ff-43eb-87c1-804b72632c54 · outbound

This paper cites InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.276526Z

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Observation e651e428-6d02-48fa-a6a5-4c574a25ea3e · outbound

This paper cites LLaVA-OneVision: Easy Visual Task Transfer.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation LLaVA-OneVision: Easy Visual Task Transfer

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.280449Z

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Observation ff836913-1b37-4ce2-aa6f-0e068e386471 · outbound

This paper cites Gemini1.5-pro.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Gemini1.5-pro

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.275500Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d482f168-e05a-4ca4-aeca-9b013a45b568 · outbound

This paper cites Claude3.5.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Claude3.5

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.266572Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9144f4d9-4333-4048-91b2-af05fb14161e · outbound

This paper cites Grok2 vision.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Grok2 vision

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.258149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9243cd1b-c85a-4e4f-a461-f9e47bb5fae0 · outbound

This paper cites Chatgpt-4o.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Chatgpt-4o

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.249632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation df98fcd3-02db-4a78-86a4-45cbea9d647f · outbound

This paper cites Pixverse: Ai video creation platform.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Pixverse: Ai video creation platform

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.241020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 553f17d8-6a13-4630-b229-d8620dc11c56 · outbound

This paper cites Wanxiang.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Wanxiang

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.231965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ba761b63-d2da-4fe2-bde6-7130fe9a28f7 · outbound

This paper cites Hailuo ai.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Hailuo ai

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.222778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 512faa2f-f5b9-477a-8f56-0af0f4310f3b · outbound

This paper cites Team, “Sora.”https://openai.com/research/video-generation-models-as-world-simulators ,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Team, “Sora.”https://openai.com/research/video-generation-models-as-world-simulators ,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.214627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e11c36e8-7e6e-4681-8621-271b32ffcb65 · outbound

This paper cites Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.313528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e37b01b3-705c-4b39-8c5c-4b5570bfb9dd · outbound

This paper cites Introducing gen-3 alpha: A new frontier for video generation.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Introducing gen-3 alpha: A new frontier for video generation

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.196511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d3e6c0fd-1c2c-4398-a063-509f1150adbe · outbound

This paper cites Kling ai.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Kling ai

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.187346Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ece6ebe9-88e5-4fa7-b2cf-ab5b365c8dbd · outbound

This paper cites Team, “Gemo.” https://www.genmo.ai, 2024.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Team, “Gemo.” https://www.genmo.ai, 2024

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.178265Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1827f4e8-bbc8-4fa2-9245-2eccf06fba5d · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.326100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df667d26-fcdb-4311-96eb-eb9b0164927f · outbound

This paper cites Team, “Xunfei.” https://typemovie.art/, 2024.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Team, “Xunfei.” https://typemovie.art/, 2024

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.169833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 11fcc47c-0da7-4c0d-b2fc-199df9ef65b3 · outbound

This paper cites Pyramidal flow matching for efficient video generative modeling,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Pyramidal flow matching for efficient video generative modeling,

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.332082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b19dd4e6-a8d4-42f3-a353-c4f399307d56 · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Wan: Open and Advanced Large-Scale Video Generative Models

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.335101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d787cc19-6e4b-48af-8967-89d90ccde02e · outbound

This paper cites Allegro: Open the Black Box of Commercial-Level Video Generation Model.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Allegro: Open the Black Box of Commercial-Level Video Generation Model

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.338428Z

Source-reported events for the cited work

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Observation 8cb38cda-cf41-44bc-b751-6bf9f3ae61a2 · outbound

This paper cites VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation VideoCrafter2: Overcoming Data Limitations for High-Quality Video Diffusion Models

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.342097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 08df4b1d-f2ad-402c-8e47-dd0efceea38b · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.345771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 172303cf-eef3-4237-acd8-a9e7b98addaf · outbound

This paper cites Easyanimate: A high-performance long video generation method based on transformer architecture,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Easyanimate: A high-performance long video generation method based on transformer architecture,

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.349363Z

Source-reported events for the cited work

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Observation c15cdad3-2c9c-4dbf-9b58-b6c45adcc72b · outbound

This paper cites LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation LAVIE: High-Quality Video Generation with Cascaded Latent Diffusion Models

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.352495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ba89d31-8912-4380-a8e3-fe8a242c480d · outbound

This paper cites Hotshot-XL.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Hotshot-XL

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.160943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 64d0ee34-a58c-4238-9783-39a4d8531532 · outbound

This paper cites Latte: Latent diffusion transformer for video generation,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Latte: Latent diffusion transformer for video generation,

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.151841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 69fd7429-2994-43d3-842e-b96fd21aec47 · outbound

This paper cites VideoCrafter1: Open Diffusion Models for High-Quality Video Generation.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation VideoCrafter1: Open Diffusion Models for High-Quality Video Generation

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.363343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a4fc38e-3dd6-4096-acf5-f0942e7a6183 · outbound

This paper cites Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video Generators

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.366831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87c5e10e-66cb-4f8a-8f30-d3e460b0ffb3 · outbound

This paper cites Autoregressive Video Generation without Vector Quantization.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Autoregressive Video Generation without Vector Quantization

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.370251Z

Source-reported events for the cited work

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Observation b662b758-6f11-440e-947c-bb0e0e3ccbff · outbound

This paper cites ModelScope Text-to-Video Technical Report.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation ModelScope Text-to-Video Technical Report

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.373929Z

Source-reported events for the cited work

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Observation cf06afa6-8297-4d57-9058-49757e28e44d · outbound

This paper cites Tune-a- video: One-shot tuning of image diffusion models for text-to-video generation,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Tune-a- video: One-shot tuning of image diffusion models for text-to-video generation,

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.142748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ba8d69a9-4038-4117-a7cb-d31f50b5300a · outbound

This paper cites LTX-Video: Realtime Video Latent Diffusion.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation LTX-Video: Realtime Video Latent Diffusion

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.380500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 176ff004-7ab7-4b43-bcd6-2f60616b7757 · outbound

This paper cites Latent Video Diffusion Models for High-Fidelity Long Video Generation.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Latent Video Diffusion Models for High-Fidelity Long Video Generation

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.384096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 296fd56a-f4ba-4111-a16c-f4911da5b5f2 · outbound

This paper cites Zeroscope.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Zeroscope

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.133230Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 21f0a260-cfb8-41ff-9399-a8c1eee5c20c · outbound

This paper cites World Model on Million-Length Video And Language With Blockwise RingAttention.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation World Model on Million-Length Video And Language With Blockwise RingAttention

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.391478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a5f7f94-2b68-479b-971f-84ac4b686245 · outbound

This paper cites Responsible research with crowds: pay crowdworkers at least minimum wage,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Responsible research with crowds: pay crowdworkers at least minimum wage,

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.123730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f7c16bbd-9349-474b-8510-06ffa80dae80 · outbound

This paper cites Toward verifiable and reproducible human evaluation for text-to-image generation,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Toward verifiable and reproducible human evaluation for text-to-image generation,

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.114645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation af42f055-f406-45d5-b940-ce19f78f00ea · outbound

This paper cites Internvid: A large-scale video-text dataset for multimodal understanding and generation,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Internvid: A large-scale video-text dataset for multimodal understanding and generation,

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.105861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d3ff9fb9-4325-4710-9bb2-44708319fb72 · outbound

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

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Msr-vtt: A large video description dataset for bridging video and language,

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.097227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ed33fdc9-709d-48e4-aa0f-03205f982a49 · outbound

This paper cites Frozen in time: A joint video and image encoder for end-to-end retrieval,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Frozen in time: A joint video and image encoder for end-to-end retrieval,

Reference 98

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.088314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3cc1b1da-32d8-4335-bbf1-b9f1b8fc9346 · outbound

This paper cites Tgif: A new dataset and benchmark on animated gif description,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation Tgif: A new dataset and benchmark on animated gif description,

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.079523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 96c01551-6739-4012-8700-4e3227a3def4 · outbound

This paper cites T2i-compbench: A comprehensive benchmark for open- world compositional text-to-image generation,.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation T2i-compbench: A comprehensive benchmark for open- world compositional text-to-image generation,

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:46:47.069121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 6b1a57a9-e7b9-4f94-9a8e-eff47ad23972 · outbound

This paper cites LMM4LMM: Benchmarking and Evaluating Large-multimodal Image Generation with LMMs.

LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation LMM4LMM: Benchmarking and Evaluating Large-multimodal Image Generation with LMMs

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-15T20:46:46.420145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation ea652983-a7d5-42ec-beb5-76a4e9f08b94 · inbound

DFBench: Benchmarking Deepfake Image Detection Capability of Large Multimodal Models cites this paper.

DFBench: Benchmarking Deepfake Image Detection Capability of Large Multimodal Models LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T11:16:47.490821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f03c7216-4506-48bb-a9b4-1fe2e7189b63 · inbound

PhyGround: Benchmarking Physical Reasoning in Generative World Models cites this paper.

PhyGround: Benchmarking Physical Reasoning in Generative World Models LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:21:28.543375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 71868fec-ce45-41ca-801b-15d7a07607cc · inbound

LongVQUBench: Benchmarking Long-Term Video Quality Understanding of Vision-Language Models cites this paper.

LongVQUBench: Benchmarking Long-Term Video Quality Understanding of Vision-Language Models LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation

Reference 50

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T13:56:59.273921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7de1b9a1-3abf-4470-b2b2-10d662cad8e8 · inbound

Natural Language Camera Movement Understanding cites this paper.

Natural Language Camera Movement Understanding LOVE: Benchmarking and Evaluating Text-to-Video Generation and Video-to-Text Interpretation

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