Search Results for author: Yoav Katz

Found 14 papers, 5 papers with code

Active Learning for BERT: An Empirical Study

1 code implementation EMNLP 2020 Liat Ein-Dor, Alon Halfon, Ariel Gera, Eyal Shnarch, Lena Dankin, Leshem Choshen, Marina Danilevsky, Ranit Aharonov, Yoav Katz, Noam Slonim

Here, we present a large-scale empirical study on active learning techniques for BERT-based classification, addressing a diverse set of AL strategies and datasets.

Active Learning Binary text classification +4

Where to start? Analyzing the potential value of intermediate models

no code implementations31 Oct 2022 Leshem Choshen, Elad Venezian, Shachar Don-Yehia, Noam Slonim, Yoav Katz

Such a model, finetuned on some source dataset, may provide a better starting point for a new finetuning process on a desired target dataset.

VIRATrustData: A Trust-Annotated Corpus of Human-Chatbot Conversations About COVID-19 Vaccines

no code implementations24 May 2022 Roni Friedman, João Sedoc, Shai Gretz, Assaf Toledo, Rose Weeks, Naor Bar-Zeev, Yoav Katz, Noam Slonim

Public trust in medical information is crucial for successful application of public health policies such as vaccine uptake.

Chatbot

Multi-Domain Targeted Sentiment Analysis

no code implementations NAACL 2022 Orith Toledo-Ronen, Matan Orbach, Yoav Katz, Noam Slonim

Our results and analysis show that our approach is a promising step towards a practical domain-robust TSA system.

Sentiment Analysis

Fusing finetuned models for better pretraining

no code implementations6 Apr 2022 Leshem Choshen, Elad Venezian, Noam Slonim, Yoav Katz

We also show that fusing is often better than intertraining.

Overview of the 2021 Key Point Analysis Shared Task

no code implementations EMNLP (ArgMining) 2021 Roni Friedman, Lena Dankin, Yufang Hou, Ranit Aharonov, Yoav Katz, Noam Slonim

We describe the 2021 Key Point Analysis (KPA-2021) shared task on key point analysis that we organized as a part of the 8th Workshop on Argument Mining (ArgMining 2021) at EMNLP 2021.

Argument Mining Text Summarization

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

Financial Event Extraction Using Wikipedia-Based Weak Supervision

no code implementations WS 2019 Liat Ein-Dor, Ariel Gera, Orith Toledo-Ronen, Alon Halfon, Benjamin Sznajder, Lena Dankin, Yonatan Bilu, Yoav Katz, Noam Slonim

Extraction of financial and economic events from text has previously been done mostly using rule-based methods, with more recent works employing machine learning techniques.

BIG-bench Machine Learning Event Extraction

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