Paper Citation Record · LEDGER

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach

As of 11 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 2 inbound Pith citation observations for arXiv:2502.00577.

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

pith.paper-citation-record.v1
2502.00577 v2

Coverage vector

measured 75 of 75 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T18:37:22.590578Z

measured 77 of 77 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-10T02:11:19.672753Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T13:41:05.828465Z

Reference resolution

75 of 75 outbound references displayed

verified exact1
verified fuzzy37
unresolved37
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c9d8d66-ebdd-4b17-af06-253c8a43d3fd · outbound

This paper cites write newline.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach write newline

Reference 1

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Observation d44157cd-1a25-4b38-8d17-421693562e0e · outbound

This paper cites GPT-4 Technical Report.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach GPT-4 Technical Report

Reference 2

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Observation d1afc926-5eed-4ce2-b80f-3ed66436bb61 · outbound

This paper cites Deep Variational Information Bottleneck.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Deep Variational Information Bottleneck

Reference 3

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Observation b97511ad-ee4a-4ce6-a54a-fc2dae7d07f9 · outbound

This paper cites I., Baratin, A., Rajeshwar, S., Ozair, S., Bengio, Y., Courville, A., and Hjelm, D.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach I., Baratin, A., Rajeshwar, S., Ozair, S., Bengio, Y., Courville, A., and Hjelm, D

Reference 4

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

Reference 6

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

Reference 7

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Observation d2981d15-d58d-4fe9-ae07-61d109924f7a · outbound

This paper cites Rev: Information-theoretic evaluation of free-text rationales.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Rev: Information-theoretic evaluation of free-text rationales

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:23.252425Z

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Observation 90199bd6-4d82-4b70-adbd-8ab9732a126e · outbound

This paper cites Infogan: Interpretable representation learning by information maximizing generative adversarial nets.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Infogan: Interpretable representation learning by information maximizing generative adversarial nets

Reference 9

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This paper cites Club: A contrastive log-ratio upper bound of mutual information.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Club: A contrastive log-ratio upper bound of mutual information

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:23.236574Z

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Observation 4a518a6a-892b-46e9-b43f-43b9676e921e · outbound

This paper cites Fairfil: Contrastive neural debiasing method for pretrained text encoders.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Fairfil: Contrastive neural debiasing method for pretrained text encoders

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:23.226954Z

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Observation 07e0b3e4-df60-4972-ab6d-9a4f1cf1465b · outbound

This paper cites Unsupervised Cross-lingual Representation Learning at Scale.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unsupervised Cross-lingual Representation Learning at Scale

Reference 12

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

Reference 13

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Observation 34580dcd-73ef-4662-bcfb-e3fad7547bda · outbound

This paper cites An information-theoretic approach to distribution shifts.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach An information-theoretic approach to distribution shifts

Reference 14

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Observation 87f04269-61c4-45cf-9295-d5068b1a2d46 · outbound

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

Reference 15

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Observation d3630b04-568a-4559-bad8-1da5abaf4e09 · outbound

This paper cites Finetune like you pretrain: Improved finetuning of zero-shot vision models.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Finetune like you pretrain: Improved finetuning of zero-shot vision models

Reference 16

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Observation c12eb1bc-7f36-44ee-99a7-8fa12ad952ea · outbound

This paper cites How well does gpt-4v (ision) adapt to distribution shifts? a preliminary investigation.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach How well does gpt-4v (ision) adapt to distribution shifts? a preliminary investigation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:23.179624Z

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Observation c558a017-6367-4981-b109-4435838c6ad7 · outbound

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

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Clipscore: A reference-free evaluation metric for image captioning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:23.170272Z

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Observation 595f81a9-01bc-470d-81db-68b15b4815e7 · outbound

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

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Observation 795091c5-efa2-4f92-9dff-2760c72cb1e0 · outbound

This paper cites The Representation Jensen-Shannon Divergence.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach The Representation Jensen-Shannon Divergence

Reference 21

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

Reference 22

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Observation b219e170-0943-41fd-8a3a-86ef68d1b749 · outbound

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach GPT-4o System Card

Reference 23

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach E5-V: Universal Embeddings with Multimodal Large Language Models

Reference 24

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

Reference 25

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Prometheus: Inducing fine-grained evaluation capability in language models

Reference 26

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Rademacher complexities and bounding the excess risk in active learning

Reference 27

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This paper cites A mutual information maximization perspective of language representation learning.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach A mutual information maximization perspective of language representation learning

Reference 28

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Estimating mutual information

Reference 29

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Fine-tuning can distort pretrained features and underperform out-of-distribution

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:23.085315Z

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Llava-med: Training a large language-and-vision assistant for biomedicine in one day

Reference 31

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Robust prompt optimization for large language models against distribution shifts

Reference 32

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach and Turner, R

Reference 33

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Evaluating object hallucination in large vision-language models

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Aligning Instruction Tuning with Pre-training

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Foundations of machine learning, 2018

Reference 40

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach J., and Jordan, M

Reference 41

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Towards calibrated robust fine-tuning of vision-language models

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.978881Z

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Dawin: Training-free dynamic weight interpolation for robust adaptation

Reference 43

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Representation Learning with Contrastive Predictive Coding

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Training language models to follow instructions with human feedback

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Estimation of entropy and mutual information

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach On variational bounds of mutual information

Reference 48

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 49

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

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This paper cites A novel domain adaptation theory with jensen--shannon divergence.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach A novel domain adaptation theory with jensen--shannon divergence

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.913514Z

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Opening the Black Box of Deep Neural Networks via Information

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Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

Reference 53

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Observation 84411106-544c-4db3-a93d-a1f039b14286 · outbound

This paper cites and Rawat, A.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach and Rawat, A

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.893450Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bf5878ee-c166-4ceb-95dd-94c368f55069 · outbound

This paper cites An information-theoretic approach to prompt engineering without ground truth labels.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach An information-theoretic approach to prompt engineering without ground truth labels

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.883331Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 61e28932-da66-4439-8072-c051a3b558f9 · outbound

This paper cites and Goldfeld, Z.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach and Goldfeld, Z

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.873438Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 396b85c9-7909-47de-ac21-e3c895cd1b95 · outbound

This paper cites K., Fukumizu, K., Gretton, A., Sch \"o lkopf, B., and Lanckriet, G.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach K., Fukumizu, K., Gretton, A., Sch \"o lkopf, B., and Lanckriet, G

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.863789Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4007c452-fcec-41c3-a437-431d8b8c7f62 · outbound

This paper cites Measuring robustness to natural distribution shifts in image classification.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Measuring robustness to natural distribution shifts in image classification

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-09T18:37:22.539823Z

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Observation e8a4ce3c-6946-4be8-bb79-cc9f84edde3a · outbound

This paper cites K., Khetan, A., Lin, Z., and Oh, S.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach K., Khetan, A., Lin, Z., and Oh, S

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.848252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 936fba69-c066-4a33-bba8-b9dd8bc9f5c4 · outbound

This paper cites Trainable projected gradient method for robust fine-tuning.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Trainable projected gradient method for robust fine-tuning

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-09T18:37:22.545829Z

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Observation f3908a94-f943-473b-b524-6886821bfcc2 · outbound

This paper cites K., Gelly, S., and Lucic, M.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach K., Gelly, S., and Lucic, M

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.833132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 88be08d1-cc4b-4d24-a09d-e229bebfeb43 · outbound

This paper cites A., Saeidi, A., Hegde, S., Therala, A., Bardoliya, F.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach A., Saeidi, A., Hegde, S., Therala, A., Bardoliya, F

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.823660Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e811a48b-b2dc-4b9d-b6fb-0b6a8a644b8f · outbound

This paper cites an unresolved cited work.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Unresolved cited work

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-09T18:37:22.554670Z

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Observation 85d12f2c-5e41-4663-9aa1-24e07adc26aa · outbound

This paper cites Info \ bert \ : Improving robustness of language models from an information theoretic perspective.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Info \ bert \ : Improving robustness of language models from an information theoretic perspective

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.808025Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4d58bd9c-ea6d-4f0d-a203-46ecba6ed8cd · outbound

This paper cites W., Li, M., Kornblith, S., Roelofs, R., Lopes, R.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach W., Li, M., Kornblith, S., Roelofs, R., Lopes, R

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-09T18:37:22.560644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebd55dcc-bce5-4288-8f13-7113462c25c4 · outbound

This paper cites and Barron, A.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach and Barron, A

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.792194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation da279d00-45b7-4ff6-bf4a-95005ea0f1d1 · outbound

This paper cites Beaf: Observing before-after changes to evaluate hallucination in vision-language models.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Beaf: Observing before-after changes to evaluate hallucination in vision-language models

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.782109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e1bbe5de-e55f-4f3e-9871-1d6820e88789 · outbound

This paper cites Bartscore: Evaluating generated text as text generation.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Bartscore: Evaluating generated text as text generation

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.772255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0993dd2c-5b40-40b4-ba61-ab61612eade1 · outbound

This paper cites J., and Ma, Y.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach J., and Ma, Y

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.762537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 80bdf995-892e-410b-b130-73aed7171a4b · outbound

This paper cites Q., and Artzi, Y.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Q., and Artzi, Y

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.753047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f8263fc8-0269-4b0f-913b-db250b239418 · outbound

This paper cites On the Out-Of-Distribution Generalization of Multimodal Large Language Models.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach On the Out-Of-Distribution Generalization of Multimodal Large Language Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-09T18:37:22.578529Z

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Observation b0217c10-9445-4a76-a337-5cfeb598707b · outbound

This paper cites Why are visually-grounded language models bad at image classification? Conference on Neural Information Processing Systems (NeurIPS), 2024 b.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Why are visually-grounded language models bad at image classification? Conference on Neural Information Processing Systems (NeurIPS), 2024 b

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.743393Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4a9de093-9523-4ed9-b828-7108383240f3 · outbound

This paper cites Judging llm-as-a-judge with mt-bench and chatbot arena.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Judging llm-as-a-judge with mt-bench and chatbot arena

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-09T18:37:22.584434Z

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Unavailable: canonical work link unavailable.

Observation 85a6fae4-c831-42ea-9361-3579b660e8d2 · outbound

This paper cites Adapting Large Multimodal Models to Distribution Shifts: The Role of In-Context Learning.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Adapting Large Multimodal Models to Distribution Shifts: The Role of In-Context Learning

Reference 74

Resolution: verified exact; local_arxiv, observed 2026-08-09T18:37:22.626485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 295e550e-b6f7-4238-8dee-f701e91defc1 · outbound

This paper cites Mini GPT -4: Enhancing vision-language understanding with advanced large language models.

Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach Mini GPT -4: Enhancing vision-language understanding with advanced large language models

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T18:37:22.727739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation 4156a342-abaa-4fcd-a198-11b220ee5573 · inbound

CoDA: Towards Effective Cross-domain Knowledge Transfer via CoT-guided Domain Adaptation cites this paper.

CoDA: Towards Effective Cross-domain Knowledge Transfer via CoT-guided Domain Adaptation Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach

Reference 57

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:11:20.666732Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1a676061-af5c-4753-8f4a-f4775b23dae9 · inbound

COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling cites this paper.

COMPASS: COntinual Multilingual PEFT with Adaptive Semantic Sampling Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:41:05.837033Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.