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Research

Papers

1. Fine-tuning Language Encoding Models on Slow fMRI Improves Prediction for Fast ECoG

   Aditya R. Vaidya, Richard J. Antonello, and Alexander G. Huth

   Manuscript 2026

2. Abstraction Induces the Brain Alignment of Language and Speech Models

   Emily Cheng, Aditya R. Vaidya, and Richard J. Antonello

   ICML 2026

3. Does the Brain Really Know What Word Is Coming Next?

   Richard J. Antonello

   eLife 2026 (Insight)

4. AVMeme Exam: A Multimodal Multilingual Multicultural Benchmark for LLMs' Contextual and Cultural Knowledge and Thinking

   Xilin Jiang, Qiaolin Wang, Junkai Wu, Xiaomin He, Zhongweiyang Xu, et al. (including Richard J. Antonello and Nima Mesgarani)

   Manuscript 2026

5. Far from the Shallow: Brain-Predictive Reasoning Embedding through Residual Disentanglement

   Linyang He*, Tianjun Zhong*, Richard J. Antonello, Gavin Mischler, Micah Goldblum, and Nima Mesgarani

   NeurIPS 2025

6. Evaluating Scientific Theories as Predictive Models in Language Neuroscience

   Chandan Singh*, Richard J. Antonello*, Sihang Guo, Gavin Mischler, Jianfeng Gao, Nima Mesgarani†, and Alexander G. Huth†

   bioRxiv 2025

7. Interpretable Embeddings of Speech Explain and Enhance the Brain Encoding Performance of Audio Models

   Riki Shimizu, Richard J. Antonello, Chandan Singh, and Nima Mesgarani

   Manuscript 2025

8. Neuro2Semantic: A Transfer Learning Framework for Semantic Reconstruction of Continuous Language from Human Intracranial EEG

   Siavash Shams, Richard J. Antonello, Gavin Mischler, Stephan Bickel, Ashesh Mehta, and Nima Mesgarani

   Interspeech 2025

9. Quantifying Semantic Functional Specialization in the Brain Using Encoding Models of Natural Language

   Jiaqi Chen*, Richard J. Antonello*, Kaavya Chaparala, Coen Arrow, and Nima Mesgarani

   CMCL 2025

10. BrainWavLM: Fine-tuning Speech Representations with Brain Responses to Language

    Nishitha Vattikonda*, Aditya R. Vaidya*, Richard J. Antonello, and Alexander G. Huth

    Manuscript 2025

11. Crafting Interpretable Embeddings by Asking LLMs Questions

    Vinamra Benara*, Chandan Singh*, John X. Morris, Richard J. Antonello, Ion Stoica, Alexander G. Huth, and Jianfeng Gao

    NeurIPS 2024

12. Generative Causal Testing to Bridge Data-Driven Models and Scientific Theories in Language Neuroscience

    Richard J. Antonello*, Chandan Singh*, Shailee Jain, Aliyah Hsu, Sihang Guo, Jianfeng Gao, Bin Yu†, and Alexander G. Huth†

    Manuscript 2024

13. Evidence from fMRI Supports a Two-Phase Abstraction Process in Language Models

    Richard J. Antonello* and Emily Cheng*

    UniReps 2024 (Oral, Best Paper Award)

14. Predictive Coding or Just Feature Discovery? An Alternative Account of Why Language Models Fit Brain Data

    Richard J. Antonello and Alexander G. Huth

    Neurobiology of Language 2024 (Best Paper Award, Society for the Neurobiology of Language 2025)

15. How Many Bytes Can You Take Out of Brain-to-Text Decoding?

    Richard J. Antonello, Nihita Sarma, Jerry Tang, Jiaru Song, and Alexander G. Huth

    Manuscript 2024

16. Scaling Laws for Language Encoding Models in fMRI

    Richard J. Antonello, Aditya R. Vaidya, and Alexander G. Huth

    NeurIPS 2023

17. Explaining Black Box Text Modules in Natural Language with Language Models

    Chandan Singh*, Aliyah R. Hsu*, Richard J. Antonello, Shailee Jain, Alexander G. Huth, Bin Yu, and Jianfeng Gao

    Manuscript 2023

18. Low-Dimensional Structure in the Space of Language Representations Is Reflected in Brain Responses

    Richard J. Antonello, Javier Turek, Vy Vo, and Alexander G. Huth

    NeurIPS 2021

19. Selecting Informative Contexts Improves Language Model Fine-tuning

    Richard J. Antonello, Nicole M. Beckage, Javier S. Turek, and Alexander G. Huth

    ACL 2021

* equal contribution. † equal supervision.

Thesis

1. Predictive Power in Language Encoding Models

   Richard J. Antonello

   PhD thesis, The University of Texas at Austin, 2024