Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-20T10:26:30.661042Z
Paper Citation Record · LEDGER
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos
As of 14 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 3 inbound Pith citation observations for arXiv:2605.18984.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T08:38:48.378542Z
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
51 of 51 outbound references displayed
- verified exact20
- verified fuzzy21
- unresolved10
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation c54c235c-aa0d-4b82-a2f6-ba2e812783fb · outbound
This paper cites Qwen3-VL Technical Report.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Qwen3-VL Technical Report
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:28:12.010636Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0b4db979-b290-4c2d-9222-bc8a0575823b · outbound
This paper cites Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Edit-Compass & EditReward-Compass: A Unified Benchmark for Image Editing and Reward Modeling
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:28:12.004383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 55d00733-8c81-4ce3-96a9-2f0e7bf1b5a8 · outbound
This paper cites Avocado: An audiovisual video captioner driven by temporal orchestration.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Avocado: An audiovisual video captioner driven by temporal orchestration
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T10:28:11.986376Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 433a8555-43f4-4252-8770-fc814bdbf8f6 · outbound
This paper cites Versavid-r1: A versatile video understanding and reasoning model from question answering to captioning tasks.arXiv e-prints, pages arXiv–2506.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Versavid-r1: A versatile video understanding and reasoning model from question answering to captioning tasks.arXiv e-prints, pages arXiv–2506
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.819989Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation cfee9ff1-bbe8-44ac-b72d-0ad9d2a8fbd5 · outbound
This paper cites Opengpt-4o-image: A compre- hensive dataset for advanced image generation and editing.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Opengpt-4o-image: A compre- hensive dataset for advanced image generation and editing
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T10:28:11.979112Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 394b8485-04cd-47da-878f-2004801b393e · outbound
This paper cites EmbodiedEval: Evaluate Multimodal LLMs as Embodied Agents.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos EmbodiedEval: Evaluate Multimodal LLMs as Embodied Agents
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T10:28:12.023952Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d26e1dce-6d9b-4a8e-a523-405ef12cdf17 · outbound
This paper cites Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:28:12.007859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 01a12773-02d4-467a-8a96-15ed311cadc4 · outbound
This paper cites Gemini 3.1 pro.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Gemini 3.1 pro
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.823715Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation a0b33ede-92e5-41ca-9f3d-1a3c5a793172 · outbound
This paper cites an unresolved cited work.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Unresolved cited work
Reference 9
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T10:28:12.829532Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 4f6e236f-b176-4518-8f24-8972be9d9b88 · outbound
This paper cites Gemini 3 flash.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Gemini 3 flash
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.832997Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation cb65038c-e526-40f0-889e-439c846cac38 · outbound
This paper cites LTX-2: Efficient Joint Audio-Visual Foundation Model.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos LTX-2: Efficient Joint Audio-Visual Foundation Model
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:28:12.020869Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 2ace0ac1-81cd-473f-a744-b365884927b8 · outbound
This paper cites GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:28:11.982339Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 8f3bf829-9786-4db9-a05d-5b830f4de318 · outbound
This paper cites Kling ai: Video generation model.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Kling ai: Video generation model
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.842277Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 2bd2e945-f692-4292-a725-af2ad7fa3a90 · outbound
This paper cites Aegis: Authen- ticity evaluation benchmark for ai-generated video sequences.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Aegis: Authen- ticity evaluation benchmark for ai-generated video sequences
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.844192Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 4be6c718-9cf5-4d22-bb4c-33e8b720ea27 · outbound
This paper cites Skyra: Ai- generated video detection via grounded artifact reasoning.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Skyra: Ai- generated video detection via grounded artifact reasoning
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.811885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 78962e4b-aeb3-450e-b542-673c0d2a190e · outbound
This paper cites Uve: Are mllms uni- fied evaluators for ai-generated videos?.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Uve: Are mllms uni- fied evaluators for ai-generated videos?
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T10:28:11.996389Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 2b7562be-2acc-4499-83b1-49852ba058c8 · outbound
This paper cites an unresolved cited work.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T10:28:12.806217Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0a83a8b0-a9c0-4446-af5c-4fbb453d8e70 · outbound
This paper cites an unresolved cited work.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Unresolved cited work
Reference 18
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T10:28:12.810081Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 9fe150a7-0b48-409e-b839-c4f618194c9f · outbound
This paper cites Mavors: Multi-granularity video representation for multimodal large language model.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Mavors: Multi-granularity video representation for multimodal large language model
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.808133Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 5d48d627-0175-41f5-b314-8ad679245fc1 · outbound
This paper cites Mme-videoocr: Eval- uating ocr-based capabilities of multimodal llms in video scenarios.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Mme-videoocr: Eval- uating ocr-based capabilities of multimodal llms in video scenarios
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.802288Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation dcfa2802-3bdf-45df-ac1e-62c46d228df6 · outbound
This paper cites Speed by simplicity: A single-stream architecture for fast audio-video generative foundation model.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Speed by simplicity: A single-stream architecture for fast audio-video generative foundation model
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.804205Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation fa0f5961-b3fe-41b5-a6f3-c23a613f6d85 · outbound
This paper cites Vf- eval: Evaluating multimodal llms for generating feedback on aigc videos.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Vf- eval: Evaluating multimodal llms for generating feedback on aigc videos
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.813677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 6e1b667b-4bb8-4bad-8ab2-4af64a44ae2d · outbound
This paper cites Videoveritas: Ai-generated video detection via perception pretext reinforcement learning.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Videoveritas: Ai-generated video detection via perception pretext reinforcement learning
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T10:28:11.993113Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 76d749ad-9ae2-4d4a-b4d8-8a6ff74034dd · outbound
This paper cites Kwai keye-vl 1.5 technical report.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Kwai keye-vl 1.5 technical report
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.796201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 358803e5-c1bc-437e-b2ce-0f44f1a9d115 · outbound
This paper cites Hunyuanvideo 1.5 technical report.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Hunyuanvideo 1.5 technical report
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.798115Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 7821b086-3f33-44f9-9363-01f35282355c · outbound
This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Wan: Open and Advanced Large-Scale Video Generative Models
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:28:11.999686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c054fbb0-1c2e-4c77-9755-2156af800524 · outbound
This paper cites Geollava-8k: scaling remote-sensing multimodal large language models to 8k resolution.Ad- vances in Neural Information Processing Systems, 38:159185– 159218.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Geollava-8k: scaling remote-sensing multimodal large language models to 8k resolution.Ad- vances in Neural Information Processing Systems, 38:159185– 159218
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.794389Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 6c660d42-9de4-4463-8d8b-2db23d06d843 · outbound
This paper cites Geoeyes: On-demand visual focusing for evidence-grounded understanding of ultra-high-resolution re- mote sensing imagery.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Geoeyes: On-demand visual focusing for evidence-grounded understanding of ultra-high-resolution re- mote sensing imagery
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T10:28:12.014486Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation bcb3a668-91c0-47f6-ae8f-d56a6aec417a · outbound
This paper cites Text before vision: Staged knowledge injection matters for agentic rlvr in ultra-high- resolution remote sensing understanding.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Text before vision: Staged knowledge injection matters for agentic rlvr in ultra-high- resolution remote sensing understanding
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T10:28:12.017696Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 2947fca7-017c-47c7-bc4d-7890215934b6 · outbound
This paper cites Monet: Reasoning in latent visual space beyond images and language.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Monet: Reasoning in latent visual space beyond images and language
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.792418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 07399145-4c41-4ab1-9de0-9dcbbea2c3c0 · outbound
This paper cites InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:28:12.027068Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation efd6b785-5987-4978-abc2-6bfdb1e417ec · outbound
This paper cites BusterX: MLLM-Powered AI-Generated Video Forgery Detection and Explanation.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos BusterX: MLLM-Powered AI-Generated Video Forgery Detection and Explanation
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-06-19T17:09:47.379931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d94a8963-4adb-4f9c-9dfc-738f8f039e52 · outbound
This paper cites BusterX++: Towards Unified Cross-Modal AI-Generated Content Detection and Explanation with MLLM.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos BusterX++: Towards Unified Cross-Modal AI-Generated Content Detection and Explanation with MLLM
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-06-19T17:09:48.005747Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c85ea067-c67e-40f8-badf-372a7eb483ff · outbound
This paper cites Mimo-vl technical report.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Mimo-vl technical report
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.800046Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 1f7175d7-a71c-4471-afa6-cbe439c07696 · outbound
This paper cites MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:28:12.033963Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 003a6872-151c-417c-bad2-2e357295fe6b · outbound
This paper cites Debiasing multimodal large language models via penal- ization of language priors.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Debiasing multimodal large language models via penal- ization of language priors
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.790590Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation b80cfbf5-0edc-4e68-925f-24735fec3fbd · outbound
This paper cites MM-RLHF: The Next Step Forward in Multimodal LLM Alignment.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos MM-RLHF: The Next Step Forward in Multimodal LLM Alignment
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T10:28:11.975833Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 7b2ad82f-1f47-4297-86af-b1de134c1c45 · outbound
This paper cites When modalities conflict: How unimodal reasoning uncertainty governs preference dynamics in mllms.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos When modalities conflict: How unimodal reasoning uncertainty governs preference dynamics in mllms
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T10:28:11.968875Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 5e6778a8-eb85-4923-aac9-2454dc46c1f3 · outbound
This paper cites yes". Otherwise, classify it as.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos yes". Otherwise, classify it as
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T10:28:11.989221Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation d245eecf-0e62-4c02-910c-8ccef921aaf2 · outbound
This paper cites yes" - "no.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos yes" - "no
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.840474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation dcc9735f-ad26-4281-8811-38260b06d7b9 · outbound
This paper cites an unresolved cited work.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Unresolved cited work
Reference 43
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T10:28:12.836821Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 4ef0210c-e7a1-40e3-a9e9-f38ed2fac0fa · outbound
This paper cites <Video A>.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos <Video A>
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.847966Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 43d3b967-9c76-47a3-b12a-e7c74371910e · outbound
This paper cites <Video A>.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos <Video A>
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.831285Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 45b0b97c-bb0a-49b7-8a99-3c71171728ca · outbound
This paper cites The original task is to identify all AIGC-specific artifacts that are clearly observable in a given AI-generated video.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos The original task is to identify all AIGC-specific artifacts that are clearly observable in a given AI-generated video
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.834828Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation f0b5662b-787a-4dfb-9e95-45a0905d7449 · outbound
This paper cites an unresolved cited work.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Unresolved cited work
Reference 50
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T10:28:12.838696Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation c845e693-7f94-4c11-a13f-43060ffe83da · outbound
This paper cites an unresolved cited work.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Unresolved cited work
Reference 51
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T10:28:12.845958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 72b908b0-3571-4c7b-8a30-0846551b71b8 · outbound
This paper cites an unresolved cited work.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Unresolved cited work
Reference 52
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T10:28:12.827533Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 0a030f72-7661-4daf-9d66-14631e747e03 · outbound
This paper cites an unresolved cited work.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Unresolved cited work
Reference 53
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T10:28:12.821935Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 4c3a405a-2f54-47d2-9f76-4acc5bf60a41 · outbound
This paper cites an unresolved cited work.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Unresolved cited work
Reference 54
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T10:28:12.825698Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 010d97f5-6844-4aa6-b2d1-dd89e4445c86 · outbound
This paper cites an unresolved cited work.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos Unresolved cited work
Reference 55
- Resolution
- unresolved
- raw_fallback, observed 2026-05-20T10:28:12.815600Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 498bf751-7ee0-4e2f-a4f5-5130285fc5a6 · outbound
This paper cites yes" if the video is AIGC, and.
Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos yes" if the video is AIGC, and
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T10:28:12.818053Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Pith citing papers
Observation 473c8604-bbe8-46ef-9bd6-7289835f4d84 · inbound
G2VD: Generalizable AI-Generated Video Detection via Counterfactual Intervention and Causal Disentanglement cites this paper.
G2VD: Generalizable AI-Generated Video Detection via Counterfactual Intervention and Causal Disentanglement Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos
Reference 86
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T08:38:48.378542Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 876e8a13-a802-409f-99dc-de6a84439464 · inbound
Detect Early, Escalate Rarely: Anytime Detection of AI-Generated Video from the Compressed Bitstream cites this paper.
Detect Early, Escalate Rarely: Anytime Detection of AI-Generated Video from the Compressed Bitstream Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T12:46:13.187376Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b1320625-5011-40a3-83c6-97bb1683d67f · inbound
RefCaptioner: Multi-Reference Image-Grounded Video Captioning cites this paper.
RefCaptioner: Multi-Reference Image-Grounded Video Captioning Artifact-Bench: Evaluating MLLMs on Detecting and Assessing the Artifacts of AI-Generated Videos
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T05:08:19.981955Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.