Papers by Satoshi Sato

3 papers
Gauging the Gap Between Human and Machine Text Simplification Through Analytical Evaluation of Simplification Strategies and Errors (2023.findings-eacl)

Copied to clipboard

Challenge: Recent studies on text simplification have focused on lexical and syntactic simplification, but few studies have attempted to assess what kind of editing operations are performed by the systems in concrete terms.
Approach: They develop an analytical evaluation framework for neural text simplification systems that includes fine-grained taxonomies of simplification strategies and errors.
Outcome: The framework was used to evaluate TS models produced by human editors and multiple neural TS systems and found that human editors perform deletions and local substitutions while excessively omitting important information.
Modeling Personal Biases in Language Use by Inducing Personalized Word Embeddings (N19-1)

Copied to clipboard

Challenge: Existing studies have attempted to personalize models to improve performance on NLP tasks such as sentiment analysis but they did not estimate subjective input.
Approach: They propose a method of modeling personal biases in word meanings with personalized word embeddings by solving a task on subjective text while regarding words used by different individuals as different words.
Outcome: The proposed method improves sentiment analysis and target task with reviews retrieved from RateBeer.
Automatic Decomposition of Text Editing Examples into Primitive Edit Operations: Toward Analytic Evaluation of Editing Systems (2024.lrec-main)

Copied to clipboard

Challenge: Existing methods to automate text editing tasks are blackboxed and do not understand the behavior of the systems.
Approach: They propose a task of automatic decomposition of text editing examples into primitive edit operations by using a phrase aligner and a large language model.
Outcome: The proposed method perfectly decomposes 44% and 64% of editing examples . Detailed analyses also provide insights into the difficulties of this task .

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations