140 citations · 359 across the 24 of their papers we have counts for
6 papers · 1 filter
Vision-Language Integration in Multimodal Video Transformers (Partially) Aligns with the Brain
Dota Tianai Dong, Mariya Toneva
Integrating information from multiple modalities is arguably one of the essential prerequisites for grounding artificial intelligence systems with an understanding of the real worl…
Speech language models lack important brain-relevant semantics
Subba Reddy Oota, Emin Çelik, Fatma Deniz +1
Despite known differences between reading and listening in the brain, recent work has shown that text-based language models predict both text-evoked and speech-evoked brain activit…
Perturbed examples reveal invariances shared by language models
Ruchit Rawal, Mariya Toneva
The rapid growth in natural language processing (NLP) research has led to numerous new models, outpacing our understanding of how they compare to established ones. One major reason…
What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation
Gabriele Merlin, Vedant Nanda, Ruchit Rawal +1
The pretrain-finetune paradigm usually improves downstream performance over training a model from scratch on the same task, becoming commonplace across many areas of machine learni…
Investigating the Effects of Fairness Interventions Using Pointwise Representational Similarity
Camila Kolling, Till Speicher, Vedant Nanda +2
Machine learning (ML) algorithms can often exhibit discriminatory behavior, negatively affecting certain populations across protected groups. To address this, numerous debiasing me…
Large language models can segment narrative events similarly to humans
Sebastian Michelmann, Manoj Kumar, Kenneth A. Norman +1
Humans perceive discrete events such as "restaurant visits" and "train rides" in their continuous experience. One important prerequisite for studying human event perception is the…