Refiner

Refiner

Reasoning framework with feedback on intermediate steps

REFINER is an interaction-based framework for natural language reasoning tasks. It has a CRITIC model that provides structured feedback on intermediate reasoning steps, and a GENERATOR model that solves the reasoning task by first generating intermediate steps. The core idea is the interaction between the generator and critic, where the generator's steps are improved via feedback from the critic.

Machine LearningNatural LanguageOptimization
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Data Science Lab

Data Science Lab
Robert West

Prof. Robert West

Our research aims to make sense of large amounts of data. Frequently, the data we analyze is collected on the Web, e.g., using server logs, social media, wikis, online news, online games, etc. We distill heaps of raw data into meaningful insights by developing and applying algorithms and techniques in areas including social and information network analysis, machine learning, computational social science, data mining, natural language processing, and human computation.

This page was last edited on 2024-05-03.