activity
20162022
most citedGrammatical Error Correction with Neural Reinforcement Learning

10 citations · 31 across the 7 of their papers we have counts for

collaborators

14 papers

cs.CL20223 cited

Towards Automated Document Revision: Grammatical Error Correction, Fluency Edits, and Beyond

Masato Mita, Keisuke Sakaguchi, Masato Hagiwara +3

Natural language processing technology has rapidly improved automated grammatical error correction tasks, and the community begins to explore document-level revision as one of the…

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.CL20218 cited

proScript: Partially Ordered Scripts Generation via Pre-trained Language Models

Keisuke Sakaguchi, Chandra Bhagavatula, Ronan Le Bras +3

Scripts - standardized event sequences describing typical everyday activities - have been shown to help understand narratives by providing expectations, resolving ambiguity, and fi…

cs.CL2021

GrammarTagger: A Multilingual, Minimally-Supervised Grammar Profiler for Language Education

Masato Hagiwara, Joshua Tanner, Keisuke Sakaguchi

We present GrammarTagger, an open-source grammar profiler which, given an input text, identifies grammatical features useful for language education. The model architecture enables…

cs.CL20201 cited

A Dataset for Tracking Entities in Open Domain Procedural Text

Niket Tandon, Keisuke Sakaguchi, Bhavana Dalvi Mishra +5

We present the first dataset for tracking state changes in procedural text from arbitrary domains by using an unrestricted (open) vocabulary. For example, in a text describing fog…

cs.CL2019

The Universal Decompositional Semantics Dataset and Decomp Toolkit

Aaron Steven White, Elias Stengel-Eskin, Siddharth Vashishtha +9

We present the Universal Decompositional Semantics (UDS) dataset (v1.0), which is bundled with the Decomp toolkit (v0.1). UDS1.0 unifies five high-quality, decompositional semantic…