Papers by Yoav Kantor
From Arguments to Key Points: Towards Automatic Argument Summarization (2020.acl-main)
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| Challenge: | Recent work on topic-related argument mining has made it difficult to read and digest large amounts of information. |
| Approach: | They propose to represent arguments as a small set of talking points, termed key points, each scored according to its salience. |
| Outcome: | The proposed method can predict key points in advance, and it performs well. |
Welcome to the Real World: Efficient, Incremental and Scalable Key Point Analysis (2023.emnlp-industry)
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| Challenge: | Key Point Analysis (KPA) extracts the main points from opinions and quantifies their prevalence. |
| Approach: | They propose a key point analysis framework that extracts the main points from opinions and quantifies their prevalence. |
| Outcome: | The proposed system is able to match sentences to key points over five datasets and demonstrate its performance. |
Quantitative argument summarization and beyond: Cross-domain key point analysis (2020.emnlp-main)
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| Challenge: | Recent work on multi-document summarization lacks quantitative aspect of summarizing views, arguments or opinions . authors develop method for automatic extraction of key points, which is comparable to a human expert . |
| Approach: | They propose to map arguments to a small set of expert-generated key points . they demonstrate that the applicability of key point analysis goes well beyond argumentation data . |
| Outcome: | The proposed method outperforms arguments in municipal surveys and user reviews . it is shown that the extraction of key points is comparable to a human expert . |
A Dataset of General-Purpose Rebuttal (D19-1)
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Matan Orbach, Yonatan Bilu, Ariel Gera, Yoav Kantor, Lena Dankin, Tamar Lavee, Lili Kotlerman, Shachar Mirkin, Michal Jacovi, Ranit Aharonov, Noam Slonim
| Challenge: | a key element in argumentation is rebuttal, the ability to contest an argument by presenting a counter-argument. |
| Approach: | They propose a method based on general rebuttal arguments to produce a critical response to a long argumentative text. |
| Outcome: | The proposed method overcomes the need for topic-specific arguments to be provided . it allows creating responses beyond the scope of topics for which specific arguments are available . |
Listening Comprehension over Argumentative Content (D18-1)
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Shachar Mirkin, Guy Moshkowich, Matan Orbach, Lili Kotlerman, Yoav Kantor, Tamar Lavee, Michal Jacovi, Yonatan Bilu, Ranit Aharonov, Noam Slonim
| Challenge: | In argumentation domain, people are exposed directly to audio (or the video), without access to a written version. |
| Approach: | They present a task for machine listening comprehension in the argumentation domain and a dataset in English. |
| Outcome: | The proposed task is based on 200 speeches arguing for or against 50 controversial topics and uses baseline methods to address it. |
Semantic Relatedness of Wikipedia Concepts – Benchmark Data and a Working Solution (L18-1)
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| Challenge: | Existing methods to measure relatedness between Wikipedia concepts are lacking. |
| Approach: | They propose a new type of concept relatedness dataset, WORD, which is annotated by a human . they use this dataset to assess relatedness between Wikipedia concepts using supervised methods. |
| Outcome: | The proposed dataset outperforms existing methods for measuring relatedness between Wikipedia concepts. |
From Key Points to Key Point Hierarchy: Structured and Expressive Opinion Summarization (2023.acl-long)
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| Challenge: | Key Point Analysis (KPA) is a new method for analyzing textual comments . it uses a list of concise sentences or phrases to extract key points from data . |
| Approach: | They propose to organize key points into a hierarchy according to their specificity . they compare methods for predicting pairwise relations between key points . |
| Outcome: | The proposed method improves on predicting pairwise key point relations and weak supervision. |
Project Debater APIs: Decomposing the AI Grand Challenge (2021.emnlp-demo)
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| Challenge: | Project Debater is the first AI system that can debate human experts on complex topics. |
| Approach: | They describe Project Debater's architecture and evaluate its performance . they will focus on Key Point Analysis, a novel technology that identifies main points . |
| Outcome: | The proposed system can debate human experts on complex topics. |
Every Bite Is an Experience: Key Point Analysis of Business Reviews (2021.acl-long)
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| Challenge: | Existing methods for summarizing reviews focus on measuring sentiment toward aspects of the review . recent work shows that KPA improves performance without domain-specific annotation . |
| Approach: | They propose a framework that provides both textual and quantitative summary of the main points in review data. |
| Outcome: | The proposed framework significantly improves on existing methods without annotations and human supervision. |
CHAMP: Efficient Annotation and Consolidation of Cluster Hierarchies (2023.emnlp-demo)
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| Challenge: | Various annotation tasks require a complex hierarchical structure over nodes, where each node is a cluster of items. |
| Approach: | They propose an open source tool that incrementally constructs clusters and hierarchy simultaneously over any type of text. |
| Outcome: | The proposed approach significantly reduces annotation time and guarantees transitivity at the cluster and hierarchy levels. |