Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering
Pan Lu, Swaroop Mishra, Tony Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan, in NeurIPS, 2022.
Abstract
Bib Entry
@inproceedings{lu2022learn,
title = {Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering},
author = {Lu, Pan and Mishra, Swaroop and Xia, Tony and Qiu, Liang and Chang, Kai-Wei and Zhu, Song-Chun and Tafjord, Oyvind and Clark, Peter and Kalyan, Ashwin},
booktitle = {NeurIPS},
github_url = {https://github.com/lupantech/ScienceQA},
year = {2022}
}
Related Publications
-
AVIS: Autonomous Visual Information Seeking with Large Language Models, NeurIPS, 2023
-
Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models, NeurIPS, 2023
-
A Survey of Deep Learning for Mathematical Reasoning, ACL, 2023
-
Symbolic Chain-of-Thought Distillation: Small Models Can Also "Think" Step-by-Step, ACL, 2023
-
On the Paradox of Learning to Reason from Data, IJCAI, 2023
-
Dynamic Prompt Learning via Policy Gradient for Semi-structured Mathematical Reasoning, ICLR, 2023
-
Semantic Probabilistic Layers for Neuro-Symbolic Learning, NeurIPS, 2022
-
Neuro-Symbolic Entropy Regularization, UAI, 2022