activity
20182022
most citedLearn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering

215 citations · 221 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2022

SPARTAN: Sparse Hierarchical Memory for Parameter-Efficient Transformers

Ameet Deshpande, Md Arafat Sultan, Anthony Ferritto +3

Fine-tuning pre-trained language models (PLMs) achieves impressive performance on a range of downstream tasks, and their sizes have consequently been getting bigger. Since a differ…

cs.CL2022215 cited

Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering

Pan Lu, Swaroop Mishra, Tony Xia +6

When answering a question, humans utilize the information available across different modalities to synthesize a consistent and complete chain of thought (CoT). This process is norm…

cs.CL20226 cited

NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks

Swaroop Mishra, Arindam Mitra, Neeraj Varshney +4

Given the ubiquitous nature of numbers in text, reasoning with numbers to perform simple calculations is an important skill of AI systems. While many datasets and models have been…

cs.LG2021

Programming Puzzles

Tal Schuster, Ashwin Kalyan, Oleksandr Polozov +1

We introduce a new type of programming challenge called programming puzzles, as an objective and comprehensive evaluation of program synthesis, and release an open-source dataset o…

stat.ML2018

Learn from Your Neighbor: Learning Multi-modal Mappings from Sparse Annotations

Ashwin Kalyan, Stefan Lee, Anitha Kannan +1

Many structured prediction problems (particularly in vision and language domains) are ambiguous, with multiple outputs being correct for an input - e.g. there are many ways of desc…