Mariya Toneva

According to our database, Mariya Toneva authored at least 24 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

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

Dota Tianai Dong, Mariya Toneva

CoRR, 2023

Speech language models lack important brain-relevant semantics.

Subba Reddy Oota, Emin Çelik, Fatma Deniz, Mariya Toneva

CoRR, 2023

Perturbed examples reveal invariances shared by language models.

Ruchit Rawal, Mariya Toneva

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, Kerem Oktar, Klaus Greff, Martin N. Hebart, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas P. O'Connell, Thomas Unterthiner, Andrew K. Lampinen, Klaus-Robert Müller, Mariya Toneva, Thomas L. Griffiths

CoRR, 2023

Pointwise Representational Similarity.

Camila Kolling, Till Speicher, Vedant Nanda, Mariya Toneva, Krishna P. Gummadi

CoRR, 2023

Large language models can segment narrative events similarly to humans.

Sebastian Michelmann, Manoj Kumar, Kenneth A. Norman, Mariya Toneva

CoRR, 2023

Joint processing of linguistic properties in brains and language models.

Subba Reddy Oota, Manish Gupta, Mariya Toneva

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Training language models to summarize narratives improves brain alignment.

Khai Loong Aw, Mariya Toneva

Proceedings of the Eleventh International Conference on Learning Representations, 2023

What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation.

Gabriele Merlin, Vedant Nanda, Ruchit Rawal, Mariya Toneva

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Combining computational controls with natural text reveals aspects of meaning composition.

Mariya Toneva, Tom M. Mitchell, Leila Wehbe

Nat. Comput. Sci., 2022

Training language models for deeper understanding improves brain alignment.

Khai Loong Aw, Mariya Toneva

CoRR, 2022

Language models and brain alignment: beyond word-level semantics and prediction.

Gabriele Merlin, Mariya Toneva

CoRR, 2022

Deep Learning for Brain Encoding and Decoding.

Subba Reddy Oota, Jashn Arora, Manish Gupta, Raju Surampudi Bapi, Mariya Toneva

Proceedings of the 44th Annual Meeting of the Cognitive Science Society, 2022

Same Cause; Different Effects in the Brain.

Mariya Toneva, Jennifer Williams, Anand Bollu, Christoph Dann, Leila Wehbe

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

Single-Trial MEG Data Can Be Denoised Through Cross-Subject Predictive Modeling.

Srinivas Ravishankar, Mariya Toneva, Leila Wehbe

Frontiers Comput. Neurosci., 2021

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

2020

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain).

Mariya Toneva, Leila Wehbe

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Inducing brain-relevant bias in natural language processing models.

Dan Schwartz, Mariya Toneva, Leila Wehbe

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

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

Proceedings of the 7th International Conference on Learning Representations, 2019

2015

Applying artificial vision models to human scene understanding.

Elissa Michele Aminoff, Mariya Toneva, Abhinav Shrivastava, Xinlei Chen, Ishan Misra, Abhinav Gupta, Michael J. Tarr

Frontiers Comput. Neurosci., 2015

2014

An Exploration of Social Grouping in Robots: Effects of Behavioral Mimicry, Appearance, and Eye Gaze.

Ahsan Nawroj, Mariya Toneva, Henny Admoni, Brian Scassellati

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 2014

2012

The Physical Presence of a Robot Tutor Increases Cognitive Learning Gains.

Daniel Leyzberg, Samuel Spaulding, Mariya Toneva, Brian Scassellati

Proceedings of the 34th Annual Meeting of the Cognitive Science Society, 2012

2011

Robot gaze does not reflexively cue human attention.

Henny Admoni, Caroline Bank, Joshua Tan, Mariya Toneva, Brian Scassellati

Proceedings of the 33th Annual Meeting of the Cognitive Science Society, 2011