Robot gaze does not reflexively cue human attention. - Henny Admoni; Caroline Bank; Joshua Tan; Mariya Toneva; Brian Scassellati (CogSci, 2011)

The Physical Presence of a Robot Tutor Increases Cognitive Learning Gains. - Daniel Leyzberg; Samuel Spaulding; Mariya Toneva; Brian Scassellati (CogSci, 2012)

An Exploration of Social Grouping in Robots: Effects of Behavioral Mimicry, Appearance, and Eye Gaze. - Ahsan Nawroj; Mariya Toneva; Henny Admoni; Brian Scassellati (CogSci, 2014)

Applying artificial vision models to human scene understanding. - Elissa Michele Aminoff; Mariya Toneva; Abhinav Shrivastava; Xinlei Chen; Ishan Misra; Abhinav Gupta 001; Michael J. Tarr (Frontiers Comput. Neurosci., 2015)

An Empirical Study of Example Forgetting during Deep Neural Network Learning. - Mariya Toneva; Alessandro Sordoni; Remi Tachet des Combes; Adam Trischler; Yoshua Bengio; Geoffrey J. Gordon (ICLR (Poster), 2019)

Inducing brain-relevant bias in natural language processing models. - Dan Schwartz; Mariya Toneva; Leila Wehbe (NeurIPS, 2019)

Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain). - Mariya Toneva; Leila Wehbe (NeurIPS, 2019)

Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction. - Mariya Toneva; Otilia Stretcu; Barnabás Póczos; Leila Wehbe; Tom M. Mitchell (NeurIPS, 2020)

Does injecting linguistic structure into language models lead to better alignment with brain recordings? - Mostafa Abdou; Ana Valeria González-Garduño; Mariya Toneva; Daniel Hershcovich; Anders Søgaard (CoRR, 2021)

Single-Trial MEG Data Can Be Denoised Through Cross-Subject Predictive Modeling. - Srinivas Ravishankar; Mariya Toneva; Leila Wehbe (Frontiers Comput. Neurosci., 2021)

Same Cause; Different Effects in the Brain. - Mariya Toneva; Jennifer Williams; Anand Bollu; Christoph Dann; Leila Wehbe (CLeaR, 2022)

Deep Learning for Brain Encoding and Decoding. - Subba Reddy Oota; Jashn Arora; Manish Gupta 001; Raju Surampudi Bapi; Mariya Toneva (CogSci, 2022)

Language models and brain alignment: beyond word-level semantics and prediction. - Gabriele Merlin; Mariya Toneva (CoRR, 2022)

Training language models for deeper understanding improves brain alignment. - Khai Loong Aw; Mariya Toneva (CoRR, 2022)

Combining computational controls with natural text reveals aspects of meaning composition. - Mariya Toneva; Tom M. Mitchell; Leila Wehbe (Nat. Comput. Sci., 2022)

Bridging Language in Machines with Language in the Brain - Mariya Toneva (2022)

What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation. - Gabriele Merlin; Vedant Nanda; Ruchit Rawal; Mariya Toneva (CoLLAs, 2023)

Training language models to summarize narratives improves brain alignment. - Khai Loong Aw; Mariya Toneva (ICLR, 2023)

Joint processing of linguistic properties in brains and language models. - Subba Reddy Oota; Manish Gupta 001; Mariya Toneva (NeurIPS, 2023)

Large language models can segment narrative events similarly to humans. - Sebastian Michelmann; Manoj Kumar; Kenneth A. Norman; Mariya Toneva (CoRR, 2023)

Pointwise Representational Similarity. - Camila Kolling; Till Speicher; Vedant Nanda; Mariya Toneva; Krishna P. Gummadi (CoRR, 2023)

Getting aligned on representational alignment. - Ilia Sucholutsky; Lukas Muttenthaler; Adrian Weller; Andi Peng; Andreea Bobu; Been Kim; Bradley C. Love; Erin Grant; Jascha Achterberg; Joshua B. Tenenbaum; Katherine M. Collins; Katherine L. Hermann; et al. (CoRR, 2023)

Vision-Language Integration in Multimodal Video Transformers (Partially) Aligns with the Brain. - Dota Tianai Dong; Mariya Toneva (CoRR, 2023)

Data and code from: Large language models can segment narrative events similarly to humans. - Sebastian Michelmann; Manoj Kumar; Kenneth A. Norman; Mariya Toneva (Zenodo, 2023)

Speech language models lack important brain-relevant semantics. - Subba Reddy Oota; Emin Çelik; Fatma Deniz; Mariya Toneva (ACL (1), 2024)

Perturbed examples reveal invariances shared by language models. - Ruchit Rawal; Mariya Toneva (ACL (Findings), 2024)

Language models and brains align due to more than next-word prediction and word-level information. - Gabriele Merlin; Mariya Toneva (EMNLP, 2024)

Assessing Episodic Memory in LLMs with Sequence Order Recall Tasks. - Mathis Pink; Vy A. Vo; Qinyuan Wu; Jianing Mu; Javier S. Turek; Uri Hasson; Kenneth A. Norman; Sebastian Michelmann; Alexander Huth; Mariya Toneva (CoRR, 2024)

SLayR: Scene Layout Generation with Rectified Flow. - Cameron Braunstein; Hevra Petekkaya; Jan Eric Lenssen; Mariya Toneva; Eddy Ilg (CoRR, 2024)

Improving Semantic Understanding in Speech Language Models via Brain-tuning. - Omer Moussa; Dietrich Klakow; Mariya Toneva (ICLR, 2025)

Hints Help Finding and Fixing Bugs Differently in Python and Text-Based Program Representations. - Ruchit Rawal; Victor-Alexandru Padurean; Sven Apel; Adish Singla; Mariya Toneva (ICSE, 2025)

Investigating the Effects of Fairness Interventions Using Pointwise Representational Similarity. - Camila Kolling; Till Speicher; Vedant Nanda; Mariya Toneva; Krishna P. Gummadi (Trans. Mach. Learn. Res., 2025)

Position: Episodic Memory is the Missing Piece for Long-Term LLM Agents. - Mathis Pink; Qinyuan Wu; Vy Ai Vo; Javier Turek; Jianing Mu; Alexander Huth; Mariya Toneva (CoRR, 2025)

Brain-tuned Speech Models Better Reflect Speech Processing Stages in the Brain. - Omer Moussa; Mariya Toneva (CoRR, 2025)

Positional Biases Shift as Inputs Approach Context Window Limits. - Blerta Veseli; Julian Chibane; Mariya Toneva; Alexander Koller (CoRR, 2025)