Papers by Doron Cohen
Motivational Interviewing Transcripts Annotated with Global Scores (2024.lrec-main)
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| Challenge: | Motivational interviewing (MI) is a counseling approach that aims to increase intrinsic motivation and commitment to change. |
| Approach: | They propose to annotate MI therapy sessions written in English from public sources . they explore the potential use of the dataset for training MI language models . |
| Outcome: | The proposed dataset includes 242 MI demonstration transcripts annotated with therapist behavioral codes and global scores and client language EAsy Rating (CLEAR) tags for client speech. |
Agent Assist through Conversation Analysis (2020.emnlp-demos)
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Kshitij Fadnis, Nathaniel Mills, Jatin Ganhotra, Haggai Roitman, Gaurav Pandey, Doron Cohen, Yosi Mass, Shai Erera, Chulaka Gunasekara, Danish Contractor, Siva Patel, Q. Vera Liao, Sachindra Joshi, Luis Lastras, David Konopnicki
| Challenge: | Using conversational approach to information retrieval for agent assistance, customer support agents are a critical part of an organization's customer support team. |
| Approach: | They propose a conversational approach to information retrieval for agent assistance that monitors an evolving conversation and recommends both responses and URLs of documents. |
| Outcome: | The proposed system monitors an evolving conversation and recommends both responses and URLs of documents the agent can use in replies to their client. |
Conversational Document Prediction to Assist Customer Care Agents (2020.emnlp-main)
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Jatin Ganhotra, Haggai Roitman, Doron Cohen, Nathaniel Mills, Chulaka Gunasekara, Yosi Mass, Sachindra Joshi, Luis Lastras, David Konopnicki
| Challenge: | Using a conversational search system, the agent/system can ask clarification questions and interactively modify the search results as the conversation progresses. |
| Approach: | They propose to use a public dataset to analyze the task of predicting the documents that customer care agents can use to facilitate users’ needs. |
| Outcome: | The proposed model is more efficient than existing models and is more cost-effective than existing ones. |
TRUE: Re-evaluating Factual Consistency Evaluation (2022.naacl-main)
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Or Honovich, Roee Aharoni, Jonathan Herzig, Hagai Taitelbaum, Doron Kukliansy, Vered Cohen, Thomas Scialom, Idan Szpektor, Avinatan Hassidim, Yossi Matias
| Challenge: | Grounded text generation systems often generate factual inconsistencies, hindering their real-world applicability. |
| Approach: | They propose a method to assess factual consistency metrics on standardized texts . they recommend NLI and question generation-and-answering-based methods as starting points . |
| Outcome: | The proposed method is more actionable and interpretable than previous methods. |
A Summarization System for Scientific Documents (D19-3)
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Shai Erera, Michal Shmueli-Scheuer, Guy Feigenblat, Ora Peled Nakash, Odellia Boni, Haggai Roitman, Doron Cohen, Bar Weiner, Yosi Mass, Or Rivlin, Guy Lev, Achiya Jerbi, Jonathan Herzig, Yufang Hou, Charles Jochim, Martin Gleize, Francesca Bonin, Francesca Bonin, David Konopnicki
| Challenge: | a qualitative user study identified the most valuable scenarios for scientific content consumption. |
| Approach: | They propose a system that retrieves and summarizes scientific documents for a given information need. |
| Outcome: | The proposed system ingested 270,000 scientific papers and validated with human experts. |