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Paper Citation Record · LEDGER

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence

As of 23 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2608.12290.

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

pith.paper-citation-record.v1
2608.12290 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:13:08.029353Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved24
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8f95c0a-b0df-47b5-8523-e93a074d6f35 · outbound

This paper cites Sora as an agi world model? a complete survey on text-to-video generation.arXiv preprint arXiv:2403.05131, 2024.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Sora as an agi world model? a complete survey on text-to-video generation.arXiv preprint arXiv:2403.05131, 2024

Reference 1

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Observation c9103f11-a681-445b-a44b-e9ff486e56e0 · outbound

This paper cites From Sora What We Can See: A Survey of Text-to-Video Generation.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence From Sora What We Can See: A Survey of Text-to-Video Generation

Reference 2

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source=pdf_text observed=2026-08-16T00:13:07.889909Z digest=sha256:cd8528bf4c0713a958b142d1ef3c65dfdd5b335fe1550ea86fbc2e20a08b1b51

Observation 9f41bf44-4b78-4733-aaf6-c4a0cdb945f8 · outbound

This paper cites Video-to-Video Synthesis.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Video-to-Video Synthesis

Reference 3

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source=pdf_text observed=2026-08-16T00:13:07.893999Z digest=sha256:a25c959cedfac82ce3529183eff2f51416363d28bbb315fd097781e3dd860b9f

Observation 22da8293-2197-4be9-8596-cd3f910ca4a8 · outbound

This paper cites Videocrafter2: Overcoming data limitations for high-quality video diffusion models.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Videocrafter2: Overcoming data limitations for high-quality video diffusion models

Reference 4

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Observation 97a86b19-cdfb-4996-bb06-5373d77e36a3 · outbound

This paper cites Vpo: Aligning text-to-video generation models with prompt optimization.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Vpo: Aligning text-to-video generation models with prompt optimization

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 29ccdd61-46d4-4268-88a1-48cbaa67c17e · outbound

This paper cites Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Open-Sora 2.0: Training a Commercial-Level Video Generation Model in $200k

Reference 6

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source=pdf_text observed=2026-08-16T00:13:07.905862Z digest=sha256:c44649b0b431e363d8c2fc5c09ca9848a6bf1a42ebad8d0a7adbe98919460ce8

Observation fafbe7e1-a240-4e7d-b560-1aea411dec71 · outbound

This paper cites Make it move: controllable image-to- video generation with text descriptions.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Make it move: controllable image-to- video generation with text descriptions

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:07.910874Z digest=sha256:8f96827af3f0facd2abf22ba8c55119817b02c15f0a203967a66f58130021ea7

Observation 7b047e86-1dfb-43be-9482-3ea1a00badca · outbound

This paper cites Prompt-a-video: Prompt your video diffusion model via preference-aligned llm.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Prompt-a-video: Prompt your video diffusion model via preference-aligned llm

Reference 8

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-16T00:13:07.915715Z digest=sha256:bc294d7bb2fe4e9902e43155eeaa32c80fe6179b692e56d0d6dac94dfbc059f2

Observation aeee1728-edb0-48c4-94da-a78d5a726bd7 · outbound

This paper cites We need to talk about random seeds.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence We need to talk about random seeds

Reference 9

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source=pdf_text observed=2026-08-16T00:13:07.919177Z digest=sha256:d3dc4f7c898c28aa6cf7a4cc9a29204e4cf7e823dc2503a5c41eff9af72d44b4

Observation e20c3403-42fd-4898-843d-e43c073d6a2a · outbound

This paper cites Rethink- ing the spatial inconsistency in classifier-free diffusion guidance.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Rethink- ing the spatial inconsistency in classifier-free diffusion guidance

Reference 10

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 095499db-1823-487a-a1b2-216db7450e39 · outbound

This paper cites Davidsonian scene graph: Im- proving reliability in fine-grained evaluation for text-to-image generation.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Davidsonian scene graph: Im- proving reliability in fine-grained evaluation for text-to-image generation

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:07.926505Z digest=sha256:a95f230876153471f3128b67ec8c9790d8c4b284ba693446cabf691d5e2376a7

Observation b47020f3-6d8d-4be6-8676-2b8c562c350f · outbound

This paper cites Generative adversarial nets.Ad- vances in neural information processing systems, 27, 2014.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Generative adversarial nets.Ad- vances in neural information processing systems, 27, 2014

Reference 12

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:07.931198Z digest=sha256:6d10ac66db150a33a2f17469b1616d4a914ec650861b756f6978c54787616f9d

Observation 5b715188-d148-489c-826f-2a3c1806c92c · outbound

This paper cites An introduction to variational autoencoders.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence An introduction to variational autoencoders

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:07.935930Z digest=sha256:54a1b5865262b9809e182a0172b686c8fc69e95a2556a9d3312fb4c844cbc3a4

Observation c38568ca-0a37-4b95-8a3d-d2c9a9a7f250 · outbound

This paper cites Denoising diffusion probabilistic models.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Denoising diffusion probabilistic models

Reference 14

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source=pdf_text observed=2026-08-16T00:13:07.939843Z digest=sha256:db5313d4e5245ed27c152de9b2890dcc5ac777c368fb35d237b1641b03aedceb

Observation 3504e273-0b37-4512-a8e4-28d86f5fa033 · outbound

This paper cites Generating videos with scene dynamics.Advances in neural information processing systems, 29, 2016.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Generating videos with scene dynamics.Advances in neural information processing systems, 29, 2016

Reference 15

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:07.942537Z digest=sha256:500106787e488c1c0c1a55eb0bc8f53bd1e6db8245cb4586479e8eb0c926afe5

Observation 870864cb-e4b4-4db8-9f0b-3b9bfeae0dba · outbound

This paper cites Video generation models as world simulators.OpenAI Blog, 1:8, 2024.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Video generation models as world simulators.OpenAI Blog, 1:8, 2024

Reference 16

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source=pdf_text observed=2026-08-16T00:13:07.944892Z digest=sha256:7019048b88a97e82a797fd4744e6c83e7b49b31b46a08ac5887cea905aefce36

Observation 19413c11-d6c3-4c2a-adf6-f9d954f0e54c · outbound

This paper cites Scalable diffusion models with transformers.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Scalable diffusion models with transformers

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 4737dac9-b01a-4c71-9a3c-ef395f62f854 · outbound

This paper cites Videomar: Autoregressive video generation with continuous tokens.Advances in neural information processing systems, 38:56928– 56958, 2026.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Videomar: Autoregressive video generation with continuous tokens.Advances in neural information processing systems, 38:56928– 56958, 2026

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:07.950153Z digest=sha256:695db3c3c4197157961be045704863a49bca0bb1b1abdf5ec704353865d7a39f

Observation 009f7f40-00ea-4dd0-ad96-c17889aa96ba · outbound

This paper cites Adding conditional control to text- to-image diffusion models.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Adding conditional control to text- to-image diffusion models

Reference 19

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Observation fdb5da39-2e25-4b74-a9d5-0d86b3400b09 · outbound

This paper cites Prompt-to-Prompt Image Editing with Cross Attention Control.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Prompt-to-Prompt Image Editing with Cross Attention Control

Reference 20

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source=pdf_text observed=2026-08-16T00:13:07.957413Z digest=sha256:ee938c826c4ec573ba2790d4e04d0ac8f4ffab2ca3cbcc6660a41cce20dae834

Observation 4677660a-20ef-4f54-9cb2-771010c3c817 · outbound

This paper cites Control-A-Video: Controllable Text-to-Video Diffusion Models with Motion Prior and Reward Feedback Learning.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Control-A-Video: Controllable Text-to-Video Diffusion Models with Motion Prior and Reward Feedback Learning

Reference 21

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Observation ce4a85ef-1689-4ad1-b500-2808bb780b32 · outbound

This paper cites Align your latents: High-resolution video synthesis with latent diffusion models.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Align your latents: High-resolution video synthesis with latent diffusion models

Reference 22

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Observation a16255e4-5a38-47a6-868c-f8b2a87dbe2e · outbound

This paper cites Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery.Advances in Neural Information Processing Systems, 36:51008– 51025, 2023.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery.Advances in Neural Information Processing Systems, 36:51008– 51025, 2023

Reference 23

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:07.968906Z digest=sha256:9ee4dd89c9373405ab3595dd0fe62f22e1b506da96b795ed143fb6ac4cc4461b

Observation 3b41dc66-33b7-48d9-9fc6-882ea0627777 · outbound

This paper cites Training diffusion models with reinforcement learning.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Training diffusion models with reinforcement learning

Reference 24

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source=pdf_text observed=2026-08-16T00:13:07.972276Z digest=sha256:5f73c1a15d498c64c7aaf8538ebb9b995915e3da9df8466da8231069042535ba

Observation e9a07f51-2cec-4925-9e0d-c4b3d4a540fb · outbound

This paper cites Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Automated Black-box Prompt Engineering for Personalized Text-to-Image Generation

Reference 25

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source=pdf_text observed=2026-08-16T00:13:07.975903Z digest=sha256:cf2910dfed4372771eafd770331cac814275abc836fa42eac51eac1c87782caf

Observation 3e0d2840-b9bf-455c-baeb-499a845dc5ab · outbound

This paper cites Optimizing prompts for text-to-image generation.Advances in Neural Information Processing Systems, 36:66923–66939, 2023.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Optimizing prompts for text-to-image generation.Advances in Neural Information Processing Systems, 36:66923–66939, 2023

Reference 26

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source=pdf_text observed=2026-08-16T00:13:07.980321Z digest=sha256:c16bfc1aa4a2d00046e3d19ca974acd951c52ea6adf603278d6a451728829014

Observation 9935308e-1195-4139-a07a-5979e6c46037 · outbound

This paper cites Classifier-Free Diffusion Guidance.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Classifier-Free Diffusion Guidance

Reference 27

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source=pdf_text observed=2026-08-16T00:13:07.984156Z digest=sha256:a9b672ae680d1d53fcec45a0002662abc0246085191a209a06fb3321a2a13a16

Observation 387431e4-0d33-4e2f-b543-1e8862808797 · outbound

This paper cites Practical bayesian optimization of machine learning algorithms.Advances in neural information processing systems, 25, 2012.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Practical bayesian optimization of machine learning algorithms.Advances in neural information processing systems, 25, 2012

Reference 28

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source=pdf_text observed=2026-08-16T00:13:07.987991Z digest=sha256:12388d446954bd784050e7bd23d533ed0180ab1cae10f34bd2b9e3b2e8fc932e

Observation ff1845b9-acc5-4ae8-8f29-449d4484db46 · outbound

This paper cites MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

Reference 29

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Observation 48d9777c-f819-4fe7-a286-e40bdf9d490d · outbound

This paper cites DialogGen: Multi-modal Interactive Dialogue System for Multi-turn Text-to-Image Generation.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence DialogGen: Multi-modal Interactive Dialogue System for Multi-turn Text-to-Image Generation

Reference 30

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source=pdf_text observed=2026-08-16T00:13:07.994952Z digest=sha256:a4c0a0169de1d3cc5c09d150edfabe560d843388c882d02c6dc168c860bccfaf

Observation 313c2745-76c7-4f70-b0cf-006006b4bee8 · outbound

This paper cites The Rise and Potential of Large Language Model Based Agents: A Survey.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence The Rise and Potential of Large Language Model Based Agents: A Survey

Reference 31

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source=pdf_text observed=2026-08-16T00:13:07.998387Z digest=sha256:3b2ac1a79462a1d452c4f952d9ba2ca4fa0f68f320c8f7b58da9cf87f4717942

Observation 56392c04-b1fc-47e5-8da4-bec93729cc01 · outbound

This paper cites A survey on large language model based autonomous agents.Frontiers of Computer Science, 18(6):186345, 2024.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence A survey on large language model based autonomous agents.Frontiers of Computer Science, 18(6):186345, 2024

Reference 32

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source=pdf_text observed=2026-08-16T00:13:08.001886Z digest=sha256:e0053595e922f97a97f5b41d6e23e08dd577f9b119e3b1bc10d7ed13d7721fcd

Observation 3f1bbdf3-e0eb-485a-8f2f-49d6de19cbbb · outbound

This paper cites Gemini 2.5 pro (gemini-2.5-pro-preview-06-05): Our most advanced intel- ligent ai model, 2025.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Gemini 2.5 pro (gemini-2.5-pro-preview-06-05): Our most advanced intel- ligent ai model, 2025

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:08.004964Z digest=sha256:7ddac5c1f329a409288bd1ca9356a5966d80e7e5ae7c6598bd064d69220ac294

Observation 5648e3d6-94d6-4b73-8f81-68340ff34574 · outbound

This paper cites The Vizier Gaussian Process Bandit Algorithm.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence The Vizier Gaussian Process Bandit Algorithm

Reference 34

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source=pdf_text observed=2026-08-16T00:13:08.008273Z digest=sha256:85f4ee93211c7323b88f8672e93d23c4e8a9a9ec57ec3d28aa5114678c8429d2

Observation ad494e1e-9919-4adb-88bf-3662665d8126 · outbound

This paper cites Rich human feedback for text-to-image generation.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Rich human feedback for text-to-image generation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:13:08.293221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:08.012232Z digest=sha256:6f468c37d1b8447107747fddd727108b2a6349e97d2b48286a9633c19e9d2942

Observation 5fe38027-2de5-4eea-aa3f-edc6530300c9 · outbound

This paper cites Rich features for perceptual quality assessment of ugc videos.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Rich features for perceptual quality assessment of ugc videos

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:13:08.284853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:08.014817Z digest=sha256:feebbea4978ffb5c6cc803873ec5c97b8547a809ee12c27167abf8efa2b92824

Observation a43342f7-5eb8-404a-9421-f8e41af0258f · outbound

This paper cites VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence VBench++: Comprehensive and Versatile Benchmark Suite for Video Generative Models

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-16T00:13:08.017256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:13:08.017256Z digest=sha256:aa0d742f8037b2242352c55029af0ce4b98917cedc131f7886f006f4a4402168

Observation 77ac2cfb-e69e-4380-903e-8e912f731cc0 · outbound

This paper cites The devil is in the prompts: Retrieval-augmented prompt optimiza- tion for text-to-video generation.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence The devil is in the prompts: Retrieval-augmented prompt optimiza- tion for text-to-video generation

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:13:08.276333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:08.019856Z digest=sha256:ba9dc469debbeaef6224a178e4ea2b9156cf8312c64e634728210e5c3d18a46a

Observation a20b9f1b-bf11-4e22-bff7-e6d5ed9f040e · outbound

This paper cites Q-bench-video: Benchmark the video quality understanding of lmms.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Q-bench-video: Benchmark the video quality understanding of lmms

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:13:08.267250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:08.022536Z digest=sha256:db5174143c13589c6228217ee52e82e508edd15c237e9224ee3a16ada5bbd4c6

Observation 31b2333c-fe95-4ddc-8ffb-fb3b95fc08b0 · outbound

This paper cites Gemini Robotics: Bringing AI into the Physical World.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence Gemini Robotics: Bringing AI into the Physical World

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-16T00:13:08.025654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:13:08.025654Z digest=sha256:1b12bd57edc81706837e97fb52d8a5613fe746e66c993303f1354cb29f526cc6

Observation 7a5df1fe-2ad0-4c0d-96a6-ca21014bf6a1 · outbound

This paper cites scene_graph.

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence scene_graph

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:13:08.256619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-16T00:13:08.029353Z digest=sha256:9b8a3cffa2c45692700edd658046a56ba0499263d075e59b8d649b326a5dc9b2

Pith citing papers

No inbound Pith citation observations are available.