Paper Citation Record · LEDGER

Refining Multidimensional Video Reward Models via Disentangled Influence Functions

As of 5 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2605.28203.

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

pith.paper-citation-record.v1
2605.28203 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T13:45:43.662583Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+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

35 of 35 outbound references displayed

verified exact13
verified fuzzy0
unresolved21
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4c2c8276-929f-4132-910e-93a09e36b4f1 · outbound

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

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Wan: Open and Advanced Large-Scale Video Generative Models

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-06-29T13:53:28.899896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c0485399-117f-40bb-ad74-2277ecb07f06 · outbound

This paper cites Kling-Omni Technical Report.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Kling-Omni Technical Report

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-06-29T13:53:28.907216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8ab92f39-c31d-483b-9ec0-35b012df52d5 · outbound

This paper cites HunyuanVideo: A Systematic Framework For Large Video Generative Models.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions HunyuanVideo: A Systematic Framework For Large Video Generative Models

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-06-29T13:53:28.892190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation bf11c1c6-6a14-4e5c-ab7d-39411e582ab8 · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-06-29T13:53:28.909933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4664f098-c94d-4e92-85b1-24f4dafe3c0e · outbound

This paper cites CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-06-29T13:53:28.902384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a076c62b-6e82-4c83-9a32-6b0e72b6b0ee · outbound

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

Refining Multidimensional Video Reward Models via Disentangled Influence Functions ModelScope Text-to-Video Technical Report

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-06-29T13:53:28.875499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a40fbba8-4cab-4222-a0bb-282c461071c5 · outbound

This paper cites Learning to summarize with human feedback.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Learning to summarize with human feedback

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37839c27-50ea-4692-81c1-c7366237d90b · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Fine-Tuning Language Models from Human Preferences

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-06-29T13:53:28.904611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f863fe9b-6d4e-40d9-b2e2-4e51f42ad9ad · outbound

This paper cites Deep reinforcement learning from human preferences.Advances in neural information processing systems, 30, 2017.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Deep reinforcement learning from human preferences.Advances in neural information processing systems, 30, 2017

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba7a37b0-d7c5-481c-8ff6-a6c6cd6e018a · outbound

This paper cites Evalcrafter: Benchmarking and evaluating large video generation models.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Evalcrafter: Benchmarking and evaluating large video generation models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7940855a-6a7f-45c0-8017-46ed7d2a4a2a · outbound

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

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Vbench: Comprehensive benchmark suite for video generative models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3965412-3538-4c15-a62e-22829ad11376 · outbound

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

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Fetv: A benchmark for fine-grained evaluation of open-domain text-to-video generation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bebce10-846c-425b-8845-a11f0662afa8 · outbound

This paper cites Mj-video: Benchmarking and rewarding video generation with fine-grained video preference.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Mj-video: Benchmarking and rewarding video generation with fine-grained video preference

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcfdb1db-f566-4193-837a-949c57f3cbe5 · outbound

This paper cites Videoscore: Building automatic metrics to simulate fine-grained human feedback for video generation.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Videoscore: Building automatic metrics to simulate fine-grained human feedback for video generation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b80344cc-a755-4576-b0c0-b251f7386931 · outbound

This paper cites VisionReward: Fine-Grained Multi-Dimensional Human Preference Learning for Image and Video Generation.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions VisionReward: Fine-Grained Multi-Dimensional Human Preference Learning for Image and Video Generation

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-06-29T13:53:28.892673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3d41a57a-bb1c-4ef2-9d28-fc1946c0eb42 · outbound

This paper cites Improving Video Generation with Human Feedback.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Improving Video Generation with Human Feedback

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-06-29T13:53:28.889766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6a9f8b96-9fd2-43a4-886b-b1379412f12b · outbound

This paper cites Understanding Impact of Human Feedback via Influence Functions.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Understanding Impact of Human Feedback via Influence Functions

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T13:53:28.897339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a3d09cd6-24e5-47fc-8904-432954eb2bf0 · outbound

This paper cites Understanding black-box predictions via influence functions.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Understanding black-box predictions via influence functions

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 714183a3-e9ff-4cb4-af5e-ec38b31b5deb · outbound

This paper cites Estimating training data influence by tracing gradient descent.Advances in Neural Information Processing Systems, 33:19920–19930, 2020.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Estimating training data influence by tracing gradient descent.Advances in Neural Information Processing Systems, 33:19920–19930, 2020

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96664d27-0c83-416c-bdd6-c85d53cd4e00 · outbound

This paper cites Boosting text-to-video generative model with mllms feedback.Advances in Neural Information Processing Systems, 37:139444–139469, 2024.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Boosting text-to-video generative model with mllms feedback.Advances in Neural Information Processing Systems, 37:139444–139469, 2024

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11d8e0d6-b12e-458b-bd89-944291fe8891 · outbound

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

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-06-29T13:53:28.894710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b6c95465-430f-4bf5-9683-596fe0f6e968 · outbound

This paper cites Clipscore: A reference-free evaluation metric for image captioning.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Clipscore: A reference-free evaluation metric for image captioning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f86c4e7d-8f54-401d-81a0-c8491b3bb0dd · outbound

This paper cites Mantis: Interleaved multi-image instruction tuning.Transactions on Machine Learning Research.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Mantis: Interleaved multi-image instruction tuning.Transactions on Machine Learning Research

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1aa8b947-42b5-48c7-b7b6-13fd4bc18810 · outbound

This paper cites Video-llava: Learning united visual representation by alignment before projection.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Video-llava: Learning united visual representation by alignment before projection

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e0ffc87-f1c3-4624-a199-268e91361696 · outbound

This paper cites Multi-task learning using uncertainty to weigh losses for scene geometry and semantics.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Multi-task learning using uncertainty to weigh losses for scene geometry and semantics

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a58cd9d-9adc-4d8a-a649-7b7767a311a0 · outbound

This paper cites Gradient surgery for multi-task learning.Advances in neural information processing systems, 33:5824–5836, 2020.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Gradient surgery for multi-task learning.Advances in neural information processing systems, 33:5824–5836, 2020

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c17ec987-0d2e-418f-a3e4-4b5fb974f382 · outbound

This paper cites Reasonable effectiveness of random weighting: A litmus test for multi-task learning.Transactions on Machine Learning Research.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Reasonable effectiveness of random weighting: A litmus test for multi-task learning.Transactions on Machine Learning Research

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e71559e-bd07-466a-8447-49c8c528a8ea · outbound

This paper cites Data pruning via moving-one-sample-out.Advances in Neural Information Processing Systems, 36, 2024.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Data pruning via moving-one-sample-out.Advances in Neural Information Processing Systems, 36, 2024

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7171cf9b-fc48-4ded-b42f-8a5dcd90a4c6 · outbound

This paper cites Relatif: Identifying explanatory training samples via relative influence.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Relatif: Identifying explanatory training samples via relative influence

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f4b982d-32d4-4d04-933c-bba738f1c738 · outbound

This paper cites TRAK: Attributing Model Behavior at Scale.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions TRAK: Attributing Model Behavior at Scale

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:53:28.884287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4a96ac10-48b2-4b86-b11a-0a2810fb293a · outbound

This paper cites Fast approximate natural gradient descent in a kronecker factored eigenbasis.Advances in neural information processing systems, 31, 2018.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Fast approximate natural gradient descent in a kronecker factored eigenbasis.Advances in neural information processing systems, 31, 2018

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd6594cc-e897-44bf-a580-37e8033248b2 · outbound

This paper cites Variational Bayesian Last Layers.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Variational Bayesian Last Layers

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:53:28.884633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 19cd5792-f147-4146-83e8-6e16e2e8bb79 · outbound

This paper cites Genai arena: An open evaluation platform for generative models.Advances in Neural Information Processing Systems, 37:79889–79908, 2024.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Genai arena: An open evaluation platform for generative models.Advances in Neural Information Processing Systems, 37:79889–79908, 2024

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37ea4c01-51e4-438c-84b8-f1a755cfbf4d · outbound

This paper cites an unresolved cited work.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Unresolved cited work

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-29T13:45:43.662583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 766f9afa-8562-49f3-98be-6e10a0398c11 · outbound

This paper cites an unresolved cited work.

Refining Multidimensional Video Reward Models via Disentangled Influence Functions Unresolved cited work

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-06-29T13:53:28.881925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

No inbound Pith citation observations are available.