Paper Citation Record · LEDGER

Multi-modal brain encoding models for multi-modal stimuli

As of 8 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2505.20027.

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

pith.paper-citation-record.v1
2505.20027 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:06:32.501427Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

24 of 24 outbound references displayed

verified exact0
verified fuzzy13
unresolved11
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9ba5bfa8-5391-4071-9a59-785c40ee93f6 · outbound

This paper cites In each plot, Pink Area (Left Circle - Intersection) represents the unique variance explained by the multi-modal model that is not shared with the unimodal model.

Multi-modal brain encoding models for multi-modal stimuli In each plot, Pink Area (Left Circle - Intersection) represents the unique variance explained by the multi-modal model that is not shared with the unimodal model

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:32.927406Z

Source-reported events for the cited work

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Observation 22e8a338-243f-4ec0-8d3d-23f461d1738a · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Multi-modal brain encoding models for multi-modal stimuli Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:35.263524Z

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Observation 6dd3f966-64c5-43de-8149-b03d432bfe01 · outbound

This paper cites Visual representations in the human brain are aligned with large language models.

Multi-modal brain encoding models for multi-modal stimuli Visual representations in the human brain are aligned with large language models

Reference 6

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Observation e59cb067-dee2-440f-b6b4-7ed8929d83bb · outbound

This paper cites Among unimodal speech models, the AST model shows better normalized brain alignment than the Wav2vec2.0 model.

Multi-modal brain encoding models for multi-modal stimuli Among unimodal speech models, the AST model shows better normalized brain alignment than the Wav2vec2.0 model

Reference 8

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Observation 4151980c-22a8-4911-af5f-92c1738484a2 · outbound

This paper cites The brain tells a story: Unveiling distinct representations of semantic content in speech, objects, and stories in the human brain with large language models.

Multi-modal brain encoding models for multi-modal stimuli The brain tells a story: Unveiling distinct representations of semantic content in speech, objects, and stories in the human brain with large language models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:30.898778Z

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Observation bcacfdbd-c71a-498d-a849-5a5b301732ac · outbound

This paper cites an unresolved cited work.

Multi-modal brain encoding models for multi-modal stimuli Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:06:34.476482Z

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Observation 7cfc39ab-b7cb-4807-8806-b71ce74d042b · outbound

This paper cites Brain-score: Which artificial neural network for object recognition is most brain-like? BioRxiv, pp.

Multi-modal brain encoding models for multi-modal stimuli Brain-score: Which artificial neural network for object recognition is most brain-like? BioRxiv, pp

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:34.302287Z

Source-reported events for the cited work

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Observation 7db2ba9b-27ef-4597-9f5a-41bfc6d29714 · outbound

This paper cites Lxmert: Learning cross-modality encoder representations from transform- ers.

Multi-modal brain encoding models for multi-modal stimuli Lxmert: Learning cross-modality encoder representations from transform- ers

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:34.153219Z

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Observation 205a8d2c-2bf2-4ca3-9f36-b0f471d1a214 · outbound

This paper cites Video-llama: An instruction-tuned audio-visual language model for video understanding.

Multi-modal brain encoding models for multi-modal stimuli Video-llama: An instruction-tuned audio-visual language model for video understanding

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:33.860988Z

Source-reported events for the cited work

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Observation 5d506d9a-960e-4f37-9b21-87353934180f · outbound

This paper cites an unresolved cited work.

Multi-modal brain encoding models for multi-modal stimuli Unresolved cited work

Reference 18

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:06:33.746565Z

Source-reported events for the cited work

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Observation 67ccef55-84cc-47ae-9390-45521ccb4f65 · outbound

This paper cites D D ETAILS OF PRETRAINED TRANSFORMER MODELS Details of each pretrained Transformer model are reported in Table 1 in Appendix.

Multi-modal brain encoding models for multi-modal stimuli D D ETAILS OF PRETRAINED TRANSFORMER MODELS Details of each pretrained Transformer model are reported in Table 1 in Appendix

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:33.589117Z

Source-reported events for the cited work

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Observation dbaec8a5-789e-4970-baf4-f9d476f50d58 · outbound

This paper cites IB Concat Shuffle.

Multi-modal brain encoding models for multi-modal stimuli IB Concat Shuffle

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:33.087719Z

Source-reported events for the cited work

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Observation a25f3653-6466-4ddb-924c-69a6776d1c79 · outbound

This paper cites an unresolved cited work.

Multi-modal brain encoding models for multi-modal stimuli Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:06:32.740090Z

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Observation 3292dc42-8c66-4817-bab9-ad1c956519a8 · outbound

This paper cites an unresolved cited work.

Multi-modal brain encoding models for multi-modal stimuli Unresolved cited work

Reference 103

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:06:33.444335Z

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Observation dd97530a-06ba-4340-8386-d31357b2d007 · outbound

This paper cites What can 1.8 billion regressions tell us about the pressures shaping high-level visual representation in brains and machines? bioRxiv, pp.

Multi-modal brain encoding models for multi-modal stimuli What can 1.8 billion regressions tell us about the pressures shaping high-level visual representation in brains and machines? bioRxiv, pp

Reference 1999

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Observation 0fc8a5e0-b434-45d1-8707-b3ee457ecfdf · outbound

This paper cites Transformers: State-of-the-art natural language processing.

Multi-modal brain encoding models for multi-modal stimuli Transformers: State-of-the-art natural language processing

Reference 2014

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:34.012656Z

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Observation 41afd5f1-6c1f-4bd1-8af9-4f3d17a8c8f5 · outbound

This paper cites Gallant lab natural short clips 3t fmri data.

Multi-modal brain encoding models for multi-modal stimuli Gallant lab natural short clips 3t fmri data

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:34.900053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 43b55957-ee3c-4a2b-8442-c2f884424e41 · outbound

This paper cites Vision-and-language or vision-for- language? on cross-modal influence in multimodal transformers.

Multi-modal brain encoding models for multi-modal stimuli Vision-and-language or vision-for- language? on cross-modal influence in multimodal transformers

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:35.078309Z

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Observation a57bf800-62a0-43c5-8fc5-c2b911daf925 · outbound

This paper cites VisualBERT: A Simple and Performant Baseline for Vision and Language.

Multi-modal brain encoding models for multi-modal stimuli VisualBERT: A Simple and Performant Baseline for Vision and Language

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:30.809387Z

Source-reported events for the cited work

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Observation 9d148cd0-fe60-4a8e-8835-2556ab4f1816 · outbound

This paper cites Proper and common names in the semantic system.

Multi-modal brain encoding models for multi-modal stimuli Proper and common names in the semantic system

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:35.475139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1b4b6cbc-051e-458e-86a3-e7dab822e61a · outbound

This paper cites MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens.

Multi-modal brain encoding models for multi-modal stimuli MiniGPT4-Video: Advancing Multimodal LLMs for Video Understanding with Interleaved Visual-Textual Tokens

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:30.173213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c37a01f-de33-444a-8b60-41e1af7d5acf · outbound

This paper cites Vision-Language Integration in Multimodal Video Transformers (Partially) Aligns with the Brain.

Multi-modal brain encoding models for multi-modal stimuli Vision-Language Integration in Multimodal Video Transformers (Partially) Aligns with the Brain

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:30.595563Z

Source-reported events for the cited work

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Observation 64c742d8-61d2-4b29-9f90-b4ea5a8df9cd · outbound

This paper cites Mae-ast: Masked autoencoding audio spectrogram transformer.

Multi-modal brain encoding models for multi-modal stimuli Mae-ast: Masked autoencoding audio spectrogram transformer

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T14:06:30.223066Z

Source-reported events for the cited work

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Observation 6f305979-a535-4f2c-96bb-2479550afa9f · outbound

This paper cites What aspects of nlp models and brain datasets affect brain-nlp alignment? In 2023 Conference on Cognitive Computational Neuroscience,.

Multi-modal brain encoding models for multi-modal stimuli What aspects of nlp models and brain datasets affect brain-nlp alignment? In 2023 Conference on Cognitive Computational Neuroscience,

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:06:34.751838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

No inbound Pith citation observations are available.