Search Results for author: Roy Bar-Haim

Found 12 papers, 1 papers with code

Project Debater APIs: Decomposing the AI Grand Challenge

no code implementations EMNLP (ACL) 2021 Roy Bar-Haim, Yoav Kantor, Elad Venezian, Yoav Katz, Noam Slonim

Engaging in a live debate requires a diverse set of skills, and Project Debater has been developed accordingly as a collection of components, each designed to perform a specific subtask.

Argument Mining

Advances in Debating Technologies: Building AI That Can Debate Humans

no code implementations ACL 2021 Roy Bar-Haim, Liat Ein-Dor, Matan Orbach, Elad Venezian, Noam Slonim

We present a complete pipeline of a debating system, and discuss the information flow and the interaction between the various components.

Argument Mining Stance Classification

Every Bite Is an Experience: Key Point Analysis of Business Reviews

no code implementations ACL 2021 Roy Bar-Haim, Lilach Eden, Yoav Kantor, Roni Friedman, Noam Slonim

Previous work on review summarization focused on measuring the sentiment toward the main aspects of the reviewed product or business, or on creating a textual summary.

Sentiment Analysis

Quantitative Argument Summarization and Beyond: Cross-Domain Key Point Analysis

2 code implementations EMNLP 2020 Roy Bar-Haim, Yoav Kantor, Lilach Eden, Roni Friedman, Dan Lahav, Noam Slonim

Recent work has proposed to summarize arguments by mapping them to a small set of expert-generated key points, where the salience of each key point corresponds to the number of its matching arguments.

Document Summarization Key Point Matching +1

From Arguments to Key Points: Towards Automatic Argument Summarization

no code implementations ACL 2020 Roy Bar-Haim, Lilach Eden, Roni Friedman, Yoav Kantor, Dan Lahav, Noam Slonim

Generating a concise summary from a large collection of arguments on a given topic is an intriguing yet understudied problem.

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