Paper Citation Record · LEDGER

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

As of 4 August 2026, this Paper Citation Record lists 100 of 155 outbound references and 27 inbound Pith citation observations for arXiv:2402.11411.

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

pith.paper-citation-record.v1
2402.11411 v1

Coverage vector

measured 100 of 155 reference resolution

Typed states for the displayed outbound observations.

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measured 127 of 127 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T19:56:33.552171Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T17:40:00.879942Z

Reference resolution

100 of 155 outbound references displayed

verified exact13
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 153cdda1-d688-4453-8701-caf449085967 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 18

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Langley , title =

Reference 20

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Unresolved cited work

Reference 21

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Unresolved cited work

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Unresolved cited work

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Unresolved cited work

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Unresolved cited work

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Newell and P

Reference 26

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Unresolved cited work

Reference 27

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2018 , eprint=

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This paper cites Generalized Results for the Existence and Consistency of the.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Generalized Results for the Existence and Consistency of the

Reference 29

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2017 , eprint=

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This paper cites John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov

Reference 31

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Unresolved cited work

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Terry , title =

Reference 33

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2020 , eprint=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2022 , eprint=

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This paper cites Training language models to follow instructions with human feedback , url =.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Training language models to follow instructions with human feedback , url =

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2022 , eprint=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning and Daly, Raymond E

Reference 40

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning ArXiv , year=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning TL ; DR : Mining R eddit to Learn Automatic Summarization

Reference 42

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2022 , eprint=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis , articleno =

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Robotics Research: Volume 1

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Active preference-based learning of reward functions , year=

Reference 46

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2019 , note=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning doi: 10.18653/v1/K16-1028

Reference 48

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Aligning Language Models with Preferences through F-Divergence Minimization , year =

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning On Reinforcement Learning and Distribution Matching for Fine-Tuning Language Models with no Catastrophic Forgetting , url =

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning International Conference on Learning Representations , year=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2022 , eprint=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning The Eleventh International Conference on Learning Representations , year=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Cross-Task Generalization via Natural Language Crowdsourcing Instructions

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Language Models are Few-Shot Learners , url =

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Proceedings of The 26th International Conference on Artificial Intelligence and Statistics , pages =

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2020 , url=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning CoRR , year=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Williams

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Reliability and Learnability of Human Bandit Feedback for Sequence-to-Sequence Reinforcement Learning

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning International Conference on Learning Representations , year=

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Deep Reinforcement Learning from Human Preferences , url =

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Reference 65

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Learning Trajectory Preferences for Manipulators via Iterative Improvement , url =

Reference 66

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Preference-based reinforcement learning: evolutionary direct policy search using a preference-based racing algorithm , journal =

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning The K-armed dueling bandits problem , journal =

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Proceedings of The 28th Conference on Learning Theory , pages =

Reference 69

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Observation 8595e394-5c1a-4297-b818-30d2a07e4dc2 · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning PaLM: Scaling Language Modeling with Pathways

Reference 70

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4f6c83c5-1cc3-4a08-84de-263fea9a110d · outbound

This paper cites Advances in neural information processing systems , volume=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Advances in neural information processing systems , volume=

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.858851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0d6de068-0e3a-492e-a612-7b0519c372f7 · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-05-17T10:58:53.503814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8f1e4349-7987-49d4-8d72-5ea700e43444 · outbound

This paper cites Proceedings of the 24th international conference on Machine learning , pages=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Proceedings of the 24th international conference on Machine learning , pages=

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.862584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 869ea475-59ab-4ee6-872e-4871193cedc0 · outbound

This paper cites Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reference 75

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T10:58:53.512739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c95a52db-fc14-43e6-b792-a57acb23f7e2 · outbound

This paper cites Neural Text Generation with Unlikelihood Training.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Neural Text Generation with Unlikelihood Training

Reference 76

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T10:58:53.517004Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d7f6ea5e-f465-4fa6-811b-d240a2bb62a8 · outbound

This paper cites Thirty-seventh Conference on Neural Information Processing Systems , year=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Thirty-seventh Conference on Neural Information Processing Systems , year=

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.866826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fbab6bb0-a921-440a-8e7c-db75b5090ffb · outbound

This paper cites 2023 , jouranl=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , jouranl=

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.872381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f3809557-a219-4b0c-b329-35f7f9dda6f2 · outbound

This paper cites 2019 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2019 , eprint=

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.875357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation cb2885d3-5ac1-403b-8d39-009b16eb70ca · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.878394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 48db0e37-7184-4f93-97b7-bce0e4c01d2f · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.881307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0115f249-be4a-4212-90a5-3e30e02fc2f5 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.883907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bd64859f-7d23-4031-8c80-bbac08e0d11c · outbound

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2024 , eprint=

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.886888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 92f01713-7fd3-46ef-adb9-dd2eeb63665d · outbound

This paper cites 2024 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2024 , eprint=

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.889932Z

Source-reported events for the cited work

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Observation d552d09d-2e91-46d9-bb5e-41c33f9b453c · outbound

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.892571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9c3fc964-fd97-4ed0-a812-4c167c0e90b9 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.556736Z

Source-reported events for the cited work

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Observation d06aa540-a865-4e65-b9de-adf91add97ff · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.559553Z

Source-reported events for the cited work

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Observation d5922ec7-ef27-46f6-97ae-03b1cf7dfe44 · outbound

This paper cites 2022 , url=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2022 , url=

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.562331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3f7af7c4-329f-4396-9049-924abeba60b3 · outbound

This paper cites 2023 , journal =.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , journal =

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.565099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9186b98a-fb40-44ec-8e2f-a30594f46fd7 · outbound

This paper cites 2023 , journal =.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , journal =

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.568007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 20cc911a-f32e-4481-a0e2-936172ea44c1 · outbound

This paper cites The method of paired comparisons , author=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning The method of paired comparisons , author=

Reference 93

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.571132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 92ecd3ef-bb9d-40f6-abd0-b7fb885ac8a2 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.573911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 70e536ae-f7a9-45fe-af82-c7f6bc2a396b · outbound

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning The 36th Conference on Neural Information Processing Systems (NeurIPS) , year=

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.577431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation d80cc23c-0874-4759-aa8f-c457cbdf41ed · outbound

This paper cites Leveraging Vision-Language Models for Granular Market Change Prediction.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Leveraging Vision-Language Models for Granular Market Change Prediction

Reference 96

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.521157Z

Source-reported events for the cited work

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Observation e197ca5e-53ec-43f2-80fe-f5ca3812de62 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Advances in Neural Information Processing Systems , volume=

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.580831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3aa9b8b4-bf5c-4f15-a4c5-a53ce07fc804 · outbound

This paper cites International conference on machine learning , pages=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning International conference on machine learning , pages=

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.583892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b2fbcb8b-0a54-401e-98a3-804569077cd5 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.586702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b3b00542-5ce1-4b38-a27f-62ce79999461 · outbound

This paper cites Hashimoto , title =.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Hashimoto , title =

Reference 101

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.589480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e2c0e346-1f0e-4f4f-ad9c-55340e05a152 · outbound

This paper cites Medical Image Understanding with Pretrained Vision Language Models: A Comprehensive Study.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Medical Image Understanding with Pretrained Vision Language Models: A Comprehensive Study

Reference 102

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.384587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 395f5aae-546c-4906-9bb4-a968de4d363c · outbound

This paper cites ArXiv , volume =.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning ArXiv , volume =

Reference 104

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.592007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bb0f1236-eab3-4e04-ae4d-712852f71cc7 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 106

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.594415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1e1ad3cc-47e6-4423-87c5-22d9012ed816 · outbound

This paper cites 2023 , journal=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , journal=

Reference 107

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.597055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4feda9ac-034f-43c1-83c8-f6a18c55c1d0 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 108

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.601395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ea6e499f-d4d4-4cf8-a0a0-4897c07a4e04 · outbound

This paper cites an unresolved cited work.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Unresolved cited work

Reference 109

Resolution: unresolved; raw_fallback, observed 2026-05-17T10:58:53.604332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 86ce2efd-55f9-4c77-90c8-d75e408645c9 · outbound

This paper cites 2020 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2020 , eprint=

Reference 110

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.607117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f27c654c-ebd4-42b7-a941-c0568f55d8ba · outbound

This paper cites 2022 , journal=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2022 , journal=

Reference 111

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.609882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b0345305-1f1b-4876-825c-13c6729b6fe5 · outbound

This paper cites 2016 , journal=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2016 , journal=

Reference 112

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.612422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e35ba45c-277c-4059-be38-fe52da81c9c4 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 113

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.615190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4f2f7c76-5d29-4d02-872a-a3a3f9bf9c70 · outbound

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2016 , url=

Reference 114

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.617716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c11b25c7-e01d-40ca-8512-33bcaf17e99b · outbound

This paper cites 2022 , journal=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2022 , journal=

Reference 115

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.620279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6f31a737-4e07-4105-99a0-8e40819306c2 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 116

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.622921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 76bf69e4-134d-40b5-be13-501c256e2713 · outbound

This paper cites 2022 , journal=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2022 , journal=

Reference 117

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.625568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b6c2a7e6-4087-42ca-aba7-37e856b2bba9 · outbound

This paper cites 2023 , journal=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , journal=

Reference 118

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.628114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3fb2ba25-0561-439e-bc55-f540deabc583 · outbound

This paper cites Understanding Dataset Difficulty with.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning Understanding Dataset Difficulty with

Reference 119

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.630931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3fcb5033-3a5d-4db2-a045-fb255fa55a4a · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 120

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.633677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8ad383c5-2e53-430a-be9f-b6a72c05e482 · outbound

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Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , url=

Reference 121

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.736157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation da78542d-85a1-487d-9e6d-b13c27a314a4 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 122

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.638769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0c6006e1-a58d-4a09-8ff7-7a2f670d1fd2 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 123

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.641305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6d30c901-6d3a-4b4d-9eab-3ea02a4e1854 · outbound

This paper cites 2023 , eprint=.

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning 2023 , eprint=

Reference 124

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T10:58:53.643806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Pith citing papers

Observation be264d2a-80aa-4fa5-9f5c-2405eb800588 · inbound

Hallucination of Multimodal Large Language Models: A Survey cites this paper.

Hallucination of Multimodal Large Language Models: A Survey Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 230

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 4333e800-1215-4743-824c-3182ebe00606 · inbound

InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output cites this paper.

InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 183

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

Source-reported events for the cited work

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Observation e1c57527-ba88-4854-b44e-60aca8582f2a · inbound

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization cites this paper.

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 120

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 998d0e57-9131-4403-b214-5b3736738381 · inbound

VidHal: Benchmarking Temporal Hallucinations in Vision LLMs cites this paper.

VidHal: Benchmarking Temporal Hallucinations in Vision LLMs Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-05-23T16:58:12.008190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 82567c0a-0954-4279-a60b-f7b26c0491a6 · inbound

Visual-RFT: Visual Reinforcement Fine-Tuning cites this paper.

Visual-RFT: Visual Reinforcement Fine-Tuning Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 90b4d342-0c3d-4bed-bcd9-25b54fa1cbaf · inbound

Seed1.5-VL Technical Report cites this paper.

Seed1.5-VL Technical Report Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 180

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation edb6763f-e2c1-4a77-b79f-f724c776e5dd · inbound

Mitigating Object Hallucinations via Sentence-Level Early Intervention cites this paper.

Mitigating Object Hallucinations via Sentence-Level Early Intervention Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 86

Resolution: verified exact; local_arxiv, observed 2026-05-25T08:35:32.493103Z

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Observation 30b42ec6-0547-43d4-b6b9-6efe512f3a97 · inbound

Advancing Multimodal Judge Models through a Capability-Oriented Benchmark and MCTS-Driven Data Generation cites this paper.

Advancing Multimodal Judge Models through a Capability-Oriented Benchmark and MCTS-Driven Data Generation Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 52

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HTDC: Hesitation-Triggered Differential Calibration for Mitigating Hallucination in Large Vision-Language Models cites this paper.

HTDC: Hesitation-Triggered Differential Calibration for Mitigating Hallucination in Large Vision-Language Models Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation 11e65227-ea07-4a2d-9b53-a6858eb8e864 · inbound

Visual Preference Optimization with Rubric Rewards cites this paper.

Visual Preference Optimization with Rubric Rewards Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation 7b57ff5e-77d4-4e92-a03e-d0de8794041f · inbound

S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models cites this paper.

S2H-DPO: Hardness-Aware Preference Optimization for Vision-Language Models Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 133

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation 9a008cd4-7980-46e1-b6f8-c688e827671d · inbound

DT2IT-MRM: Debiased Preference Construction and Iterative Training for Multimodal Reward Modeling cites this paper.

DT2IT-MRM: Debiased Preference Construction and Iterative Training for Multimodal Reward Modeling Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation e53a8fc6-98c3-4489-8446-c11c810bc9f3 · inbound

R-CoV: Region-Aware Chain-of-Verification for Alleviating Object Hallucinations in LVLMs cites this paper.

R-CoV: Region-Aware Chain-of-Verification for Alleviating Object Hallucinations in LVLMs Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation 67b11d97-2991-46f5-a364-5d92e71a201d · inbound

When Prompts Override Vision: Prompt-Induced Hallucinations in LVLMs cites this paper.

When Prompts Override Vision: Prompt-Induced Hallucinations in LVLMs Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 52

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation b6634a58-0134-4dce-82c1-9563085a49f2 · inbound

Online Self-Calibration Against Hallucination in Vision-Language Models cites this paper.

Online Self-Calibration Against Hallucination in Vision-Language Models Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation 3b2b0c1d-6aa8-48bf-9e3d-b81bf2bcb8be · inbound

Replacing Parameters with Preferences: Federated Alignment of Heterogeneous Vision-Language Models cites this paper.

Replacing Parameters with Preferences: Federated Alignment of Heterogeneous Vision-Language Models Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 29

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation 008f94a0-f7c3-495e-9658-3a08eccb3a0e · inbound

Uncertainty-Aware Exploratory Direct Preference Optimization for Multimodal Large Language Models cites this paper.

Uncertainty-Aware Exploratory Direct Preference Optimization for Multimodal Large Language Models Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

Source-reported events for the cited work

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Observation eb15ce03-13b6-46af-9b05-b7d08b7704e2 · inbound

Vocabulary Hijacking in LVLMs: Unveiling Critical Attention Heads by Excluding Inert Tokens to Mitigate Hallucination cites this paper.

Vocabulary Hijacking in LVLMs: Unveiling Critical Attention Heads by Excluding Inert Tokens to Mitigate Hallucination Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 58

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation 8ca5ef37-69d0-4287-8caa-6e96270fbace · inbound

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone cites this paper.

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

Source-reported events for the cited work

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Observation 0fbebd25-d68f-48b6-ac7f-f543fa69cbbd · inbound

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone cites this paper.

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-17T10:58:53.893696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 466356d0-9174-4779-8775-327286404a22 · inbound

Bad Seeing or Bad Thinking? Rewarding Perception for Multimodal Reasoning cites this paper.

Bad Seeing or Bad Thinking? Rewarding Perception for Multimodal Reasoning Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T10:58:53.893696Z

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Observation 159dee4a-0d09-4053-bbab-ef110ae5b5de · inbound

Deep Pre-Alignment for VLMs cites this paper.

Deep Pre-Alignment for VLMs Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 78

Resolution: metadata mismatch; local_arxiv, observed 2026-05-19T16:27:39.606281Z

Source-reported events for the cited work

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Observation bf691ecf-e3aa-4ace-b4ef-ef1b10052822 · inbound

P$^2$-DPO: Grounding Hallucination in Perceptual Processing via Calibration Direct Preference Optimization cites this paper.

P$^2$-DPO: Grounding Hallucination in Perceptual Processing via Calibration Direct Preference Optimization Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 122

Resolution: verified exact; local_arxiv, observed 2026-07-02T02:06:27.182299Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2a539766-1815-478b-94ae-c444d89c6c15 · inbound

CineCap: Structured Reasoning with Spatio-Temporal Anchors for Cinematographic Video Captioning cites this paper.

CineCap: Structured Reasoning with Spatio-Temporal Anchors for Cinematographic Video Captioning Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-07-04T17:40:00.881290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 058de06d-e698-41f4-8a54-b166c7ee7a66 · inbound

Vision-driven Preference Synthesis for Mitigating Hallucinations in VLMs cites this paper.

Vision-driven Preference Synthesis for Mitigating Hallucinations in VLMs Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-07-01T15:35:47.620953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fffd69ff-93a4-4867-bf75-206b969c592f · inbound

No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs cites this paper.

No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 96

Resolution: metadata mismatch; local_arxiv, observed 2026-07-01T10:25:41.372451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 80be012f-6bf8-4f8b-9ecb-e46c0bec50dd · inbound

Groc-PO: Grounded Context Preference Optimization for Truthful Multimodal LLMs cites this paper.

Groc-PO: Grounded Context Preference Optimization for Truthful Multimodal LLMs Aligning Modalities in Vision Large Language Models via Preference Fine-tuning

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-02T04:15:39.465899Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.