activity
20202025
most citedSelf-Refine: Iterative Refinement with Self-Feedback

221 citations · 383 across the 22 of their papers we have counts for

collaborators
Showing 2021Show all

8 papers · 1 filter

cs.AI2021★ 3 cited

Interscript: A dataset for interactive learning of scripts through error feedback

Niket Tandon, Aman Madaan, Peter Clark +2

How can an end-user provide feedback if a deployed structured prediction model generates inconsistent output, ignoring the structural complexity of human language? This is an emerg…

cs.CL2021

Learning to Repair: Repairing model output errors after deployment using a dynamic memory of feedback

Niket Tandon, Aman Madaan, Peter Clark +1

Large language models (LMs), while powerful, are not immune to mistakes, but can be difficult to retrain. Our goal is for an LM to continue to improve after deployment, without ret…

cs.AI2021

Think about it! Improving defeasible reasoning by first modeling the question scenario

Aman Madaan, Niket Tandon, Dheeraj Rajagopal +3

Defeasible reasoning is the mode of reasoning where conclusions can be overturned by taking into account new evidence. Existing cognitive science literature on defeasible reasoning…

cs.LG2021

Dual Encoding U-Net for Spatio-Temporal Domain Shift Frame Prediction

Jay Santokhi, Dylan Hillier, Yiming Yang +3

The landscape of city-wide mobility behaviour has altered significantly over the past 18 months. The ability to make accurate and reliable predictions on such behaviour has likewis…

cs.CL2021

Could you give me a hint? Generating inference graphs for defeasible reasoning

Aman Madaan, Dheeraj Rajagopal, Niket Tandon +2

Defeasible reasoning is the mode of reasoning where conclusions can be overturned by taking into account new evidence. A commonly used method in cognitive science and logic literat…

cs.CL2021

Improving Neural Model Performance through Natural Language Feedback on Their Explanations

Aman Madaan, Niket Tandon, Dheeraj Rajagopal +4

A class of explainable NLP models for reasoning tasks support their decisions by generating free-form or structured explanations, but what happens when these supporting structures…

cs.CL2021★ 1 cited

CURIE: An Iterative Querying Approach for Reasoning About Situations

Dheeraj Rajagopal, Aman Madaan, Niket Tandon +5

Recently, models have been shown to predict the effects of unexpected situations, e.g., would cloudy skies help or hinder plant growth? Given a context, the goal of such situationa…

cs.CL2021★ 2 cited

Meta Back-translation

Hieu Pham, Xinyi Wang, Yiming Yang +1

Back-translation is an effective strategy to improve the performance of Neural Machine Translation~(NMT) by generating pseudo-parallel data. However, several recent works have foun…