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Paper Citation Record · LEDGER

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

As of 16 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 2026-08-15T06:32:42.880941+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
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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:b23e409bd74abca32fbfa1935d2ea9503b0355f2b2005fb1761bd0e8c9b9da06

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=sha256:8cbed2c3b5a3370e11fd4b19ec4a75cc0c272637ba2604160ce5b13a78d7a722

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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source=pdf_text observed=2026-08-16T00:13:07.897803Z digest=sha256:5142ae879f7099180705e1f4c131c54eb28324913080551db42ebb7ec06fbf02

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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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+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:dc67fe6a7bf119493f97290a4281df0e0c72730f69f7e44b9596899d9de904d3

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-16T00:13:07.910874Z digest=sha256:f0fff61ec6a1aace8493d111327f09bdf8cd72054ba94c41b4a63e9ca0ee3b40

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

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

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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=sha256:94ae46de8ee1a89695a85dc478a388fbbf73140872977c02ada6534d0e7a791e

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-16T00:13:07.922856Z digest=sha256:1b6376e1dedb4ba03c354b91725f0aff33061083c4731fa4e842842edc80ee93

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 2026-08-15T06:32:42.880941+00:00.

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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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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.

source=pdf_text observed=2026-08-16T00:13:07.931198Z digest=sha256:51fcea88ef9e6c586ffc74508f83d1b4fc1f0fe1cbd5356767427c9b9edce357

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-16T00:13:07.935930Z digest=sha256:8ef29dbd07d94e626204b929993d6180b421fea07c318d0f0a84258c1a834832

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=sha256:3b1b8dc2c657afb02ceb3c2f59571b9c19f928e98ed6404d475814e911bc9950

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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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.

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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=sha256:84c416175082b8525257aa4ec2d6afce1e0f990a7603999babe67eb8f25da0f6

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 2026-08-15T06:32:42.880941+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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-16T00:13:07.950153Z digest=sha256:1b2a9c1f15ce677d76323d8f25d3d1bc2b9bd51d00a2de3db232ff47bc3c1a36

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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source=pdf_text observed=2026-08-16T00:13:07.953983Z digest=sha256:8a8fb468e050ffebc8f652e599a4dcb025cc382df5fcc88a19d6e7332cb795da

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=sha256:1e5f3b420ad73fcfd4e282b5b74b94a9dd57bc0779862e491b7adbe9df038f80

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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source=pdf_text observed=2026-08-16T00:13:07.968906Z digest=sha256:5f53a4a551a5018dfb6be434659ad6f4259f69076bbbb0802ab3c9f2b7e409d8

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:fc893774b9ad66d348c3dc44ffef52ca5044b84e28cd411602acad76aa322c9d

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=sha256:2a43a3a1f8375e6b6e2c2b2040f92327f48f6eed5202b8a426a0f9c78f05a905

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=sha256:28b670d79625a703899258f627f28b462387999b7576dfc9e9cc81d6efdc2e4c

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:aac875fd7b94dd7c64dc0f884fa15180de3d7aad20f5eb03fb6c56ac3806cc1a

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=sha256:8bc71252c432051fcaaf376990681cc5bca028cc0f9d4da06b68ae93e4a80e73

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=sha256:8cf528fdbf1d0a8d205fbb72468fa600a63e37d0600dde94e6f4412aac2b1ec7

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=sha256:1d4ebf846cb6f9f2303530ca74315a75b205e5f4dc0d465305f6eee229a92f57

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=sha256:3e5b0b0c48ec82b109e7b93581ac65ecf7148a13d9772044d10533538573b300

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-16T00:13:08.004964Z digest=sha256:ce4dfa4e5051a6b0f8f3418f407d8a56561b5c4ffebf98868dd767554dd04ddd

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=sha256:8d9f5e394982fdd43b4b6fcc1da1397cd7bb6bed99a4d78678fda7840ce4f143

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-16T00:13:08.012232Z digest=sha256:159e65f6a49bab7b72828a8c2bf24a65e0e482c3e3f39f468cd5b6ad5c5b4961

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-16T00:13:08.014817Z digest=sha256:a8de606faefe1a50aa1ef87991e8d356f3590e0bc7c85e0f9f928925d9c568aa

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=sha256:06c1d731502da9f5d38935c9d9e9187f1700bba2480d5d7eaee09b483cd1efc1

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-16T00:13:08.019856Z digest=sha256:18e11290a32825abab9155c46a314eb45830ec9e8aff7a45a51af75e655b5e57

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-16T00:13:08.022536Z digest=sha256:8e3b0da88ee0cae42eb449981b6720db4b15fe5520834c4e9d68a8d503ea24dc

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=sha256:742f00e0be416b8865547d5dec652555d6af9cfe4c74e6ea80609abbba746b23

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 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-16T00:13:08.029353Z digest=sha256:4080c3b5a907ed645e68f386c6fa29090c2417d1a4470f763a0f01e8bd620f94

Pith citing papers

No inbound Pith citation observations are available.