Paper Citation Record · LEDGER

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain

As of 13 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2607.05171.

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

pith.paper-citation-record.v1
2607.05171 v1

Coverage vector

measured 32 of 32 reference resolution

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measured 32 of 32 standing notices

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

32 of 32 outbound references displayed

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External citation measurements

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Outbound references

Observation 38ab5232-5ff1-462e-84cf-4ed7d85ef78d · outbound

This paper cites Transformer brain encoders explain human high-level visual responses.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Transformer brain encoders explain human high-level visual responses

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.146366Z

Source-reported events for the cited work

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Observation f3345c05-e5ca-406d-a192-4e89843bb05c · outbound

This paper cites Scaling laws for language encoding models in fmri.Advances in Neural Information Processing Systems, 36, 2024.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Scaling laws for language encoding models in fmri.Advances in Neural Information Processing Systems, 36, 2024

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.192961Z

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Observation abf39596-eee0-4f3f-8f8c-4c49fa33ac62 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations.Advances in Neural Information Processing Systems, 33:12449–12460, 2020.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain wav2vec 2.0: A framework for self-supervised learning of speech representations.Advances in Neural Information Processing Systems, 33:12449–12460, 2020

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.158125Z

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Observation 285fdb4d-a541-4c64-877b-4caabb8f5623 · outbound

This paper cites The Wisdom of a Crowd of Brains: A Universal Brain Encoder.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain The Wisdom of a Crowd of Brains: A Universal Brain Encoder

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-07-08T01:24:27.123936Z

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Observation bb0e6a7d-6761-4128-81fe-5c09c7a7fdff · outbound

This paper cites The wisdom of a crowd of brains: A universal brain encoder, 2025.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain The wisdom of a crowd of brains: A universal brain encoder, 2025

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.194698Z

Source-reported events for the cited work

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Observation dc59a640-1f06-48b6-ad56-aeb9ee47577d · outbound

This paper cites WavLM: Large-scale self-supervised pre- training for full stack speech processing.IEEE Journal of Selected Topics in Signal Processing, 16(6):1505–1518, 2022.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain WavLM: Large-scale self-supervised pre- training for full stack speech processing.IEEE Journal of Selected Topics in Signal Processing, 16(6):1505–1518, 2022

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.164102Z

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Observation 793c4d28-b742-4cdf-9ea4-b5c65ea41de4 · outbound

This paper cites A foundation model of vision, audition, and language for in-silico neuroscience.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain A foundation model of vision, audition, and language for in-silico neuroscience

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.183040Z

Source-reported events for the cited work

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Observation 373185e9-4acd-4265-936c-b1439a5383bc · outbound

This paper cites Hierarchical processing in spoken language compre- hension.Journal of Neuroscience, 23(8):3423–3431, 2003.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Hierarchical processing in spoken language compre- hension.Journal of Neuroscience, 23(8):3423–3431, 2003

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.134371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c5ca23d6-b641-4148-a2bc-3c0fef222357 · outbound

This paper cites New method for fmri investigations of language: defining rois functionally in individual subjects.Journal of Neurophysiology, 104(2):1177–1194, 2010.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain New method for fmri investigations of language: defining rois functionally in individual subjects.Journal of Neurophysiology, 104(2):1177–1194, 2010

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.153024Z

Source-reported events for the cited work

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Observation 93f0dfcf-5584-4eb9-9af5-2ad6d6b443ae · outbound

This paper cites Freesurfer.NeuroImage, 62(2):774–781, aug 2012.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Freesurfer.NeuroImage, 62(2):774–781, aug 2012

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.187008Z

Source-reported events for the cited work

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Observation 0c154231-9b97-4777-b269-23e95158e3e3 · outbound

This paper cites Sereno, Roger B.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Sereno, Roger B

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.159270Z

Source-reported events for the cited work

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Observation 7efd46ae-e542-4e92-930c-005138e079a0 · outbound

This paper cites The Algonauts Project 2025 Challenge: How the Human Brain Makes Sense of Multimodal Movies.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain The Algonauts Project 2025 Challenge: How the Human Brain Makes Sense of Multimodal Movies

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-07-08T01:24:27.129457Z

Source-reported events for the cited work

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Observation db961120-5605-4f98-aecd-4ffe989d682e · outbound

This paper cites A multi-modal parcellation of human cerebral cortex.Nature, 536(7615):171–178.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain A multi-modal parcellation of human cerebral cortex.Nature, 536(7615):171–178

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.177380Z

Source-reported events for the cited work

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Observation a1966b81-cd14-4a45-a9c7-52a20af2fd3c · outbound

This paper cites The cortical organization of speech processing.Nat.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain The cortical organization of speech processing.Nat

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.166287Z

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Observation fc65cac8-0274-4793-a672-1281696d9f1e · outbound

This paper cites LoRA: Low-rank adaptation of large language models.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain LoRA: Low-rank adaptation of large language models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.137926Z

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Observation ce8317a1-28c7-4d52-a529-6bb12d7cba7e · outbound

This paper cites Natural speech reveals the semantic maps that tile human cerebral cortex.Nature, 532(7600):453–458, 2016.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Natural speech reveals the semantic maps that tile human cerebral cortex.Nature, 532(7600):453–458, 2016

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.140145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 05dfe73b-c140-4d12-b407-a24f874aa0a8 · outbound

This paper cites Incorporating context into language encoding models for fmri.Advances in Neural Information Processing Systems, 31, 2018.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Incorporating context into language encoding models for fmri.Advances in Neural Information Processing Systems, 31, 2018

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.155748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3346719c-bd0a-470d-82de-41ad2c6f4ddf · outbound

This paper cites A natural language fmri dataset for voxelwise encoding models.Scientific Data, 10(1):555, 2023.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain A natural language fmri dataset for voxelwise encoding models.Scientific Data, 10(1):555, 2023

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.150152Z

Source-reported events for the cited work

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Observation 0ef9a434-854b-4fbf-91ed-b8b7111f370e · outbound

This paper cites Nathan Spreng, Jonathan R.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Nathan Spreng, Jonathan R

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.179049Z

Source-reported events for the cited work

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Observation 86b3d1ba-f78e-4ad9-8286-828bd6c4986a · outbound

This paper cites Toward a realistic model of speech processing in the brain with self-supervised learning.Advances in Neural Information Processing Systems, 35:33428–33443, 2022.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Toward a realistic model of speech processing in the brain with self-supervised learning.Advances in Neural Information Processing Systems, 35:33428–33443, 2022

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.197208Z

Source-reported events for the cited work

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Observation ccba429e-c6f0-4511-b455-825e358804c6 · outbound

This paper cites Improving semantic understanding in speech language models via brain-tuning.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Improving semantic understanding in speech language models via brain-tuning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.184918Z

Source-reported events for the cited work

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Observation f0e4da14-5a15-4e3a-9c59-0066b9a2a8e3 · outbound

This paper cites Brain-tuned Speech Models Better Reflect Speech Processing Stages in the Brain.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Brain-tuned Speech Models Better Reflect Speech Processing Stages in the Brain

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-07-08T01:24:27.116373Z

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Observation 790a4197-61a2-44af-b013-e0dbcff784ff · outbound

This paper cites Brain-tuning improves generalizability and efficiency of brain alignment in speech models.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Brain-tuning improves generalizability and efficiency of brain alignment in speech models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.162091Z

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This paper cites narratives.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain narratives

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.188935Z

Source-reported events for the cited work

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Observation 55940e43-1f52-44a6-b138-d5ba2275cb87 · outbound

This paper cites Speech language models lack important brain-relevant semantics.Annual Meeting of the Association for Computational Linguistics (ACL), 2024.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Speech language models lack important brain-relevant semantics.Annual Meeting of the Association for Computational Linguistics (ACL), 2024

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.143465Z

Source-reported events for the cited work

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Observation bc10ec41-18e0-4de5-978b-4f1047d0de65 · outbound

This paper cites The neural architecture of language: Integrative modeling converges on predictive processing.Proceedings of the National Academy of Sciences, 2021.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain The neural architecture of language: Integrative modeling converges on predictive processing.Proceedings of the National Academy of Sciences, 2021

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.181013Z

Source-reported events for the cited work

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Observation 8c9f68b2-6710-4480-8a23-1bd7096e3101 · outbound

This paper cites Identification of a pathway for intelligible speech in the left temporal lobe.Brain, 123(12):2400–2406, 2000.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Identification of a pathway for intelligible speech in the left temporal lobe.Brain, 123(12):2400–2406, 2000

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.172571Z

Source-reported events for the cited work

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Observation c0dcdf66-dd5f-4edb-b80d-575f2a65c3ec · outbound

This paper cites Cneuromod-things, a densely- sampled fmri dataset for visual neuroscience.Scientific Data, 2026.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Cneuromod-things, a densely- sampled fmri dataset for visual neuroscience.Scientific Data, 2026

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.168418Z

Source-reported events for the cited work

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Observation 640027b8-5007-4f5e-8ae2-684537b450a3 · outbound

This paper cites Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain).Advances in Neural Information Processing Systems, 32, 2019.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain).Advances in Neural Information Processing Systems, 32, 2019

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.170306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cc6b70f4-f5da-4940-860b-248d8ded2826 · outbound

This paper cites Self-supervised models of audio effectively explain human cortical responses to speech.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Self-supervised models of audio effectively explain human cortical responses to speech

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.190662Z

Source-reported events for the cited work

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Observation b4d81a2a-468c-4f88-a768-128905265d35 · outbound

This paper cites Vaidya, Richard J.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Vaidya, Richard J

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-07-08T01:24:27.174226Z

Source-reported events for the cited work

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Observation d42d42aa-587f-492e-b818-55a46763d24e · outbound

This paper cites Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses.PloS One, (11), 2014.

RABBiT: Rapidly adaptive BOLD foundation model via brain-tuning for accurate zero-shot and few-shot prediction of speech-elicited responses in the brain Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses.PloS One, (11), 2014

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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