154 citations · 160 across the 3 of their papers we have counts for
6 papers
ChemBERTa-2: Towards Chemical Foundation Models
Walid Ahmad, Elana Simon, Seyone Chithrananda +2
Large pretrained models such as GPT-3 have had tremendous impact on modern natural language processing by leveraging self-supervised learning to learn salient representations that…
Identifying concept libraries from language about object structure
Catherine Wong, William P. McCarthy, Gabriel Grand +5
Our understanding of the visual world goes beyond naming objects, encompassing our ability to parse objects into meaningful parts, attributes, and relations. In this work, we lever…
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
Seyone Chithrananda, Gabriel Grand, Bharath Ramsundar
GNNs and chemical fingerprints are the predominant approaches to representing molecules for property prediction. However, in NLP, transformers have become the de-facto standard for…
Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects
Gabriel Grand, Yonatan Belinkov
Visual question answering (VQA) models have been shown to over-rely on linguistic biases in VQA datasets, answering questions "blindly" without considering visual context. Adversar…
On the Flip Side: Identifying Counterexamples in Visual Question Answering
Gabriel Grand, Aron Szanto, Yoon Kim +1
Visual question answering (VQA) models respond to open-ended natural language questions about images. While VQA is an increasingly popular area of research, it is unclear to what e…
Semantic projection: recovering human knowledge of multiple, distinct object features from word embeddings
Gabriel Grand, Idan Asher Blank, Francisco Pereira +1
The words of a language reflect the structure of the human mind, allowing us to transmit thoughts between individuals. However, language can represent only a subset of our rich and…