Papers by Shai Gretz
Masked by Consensus: Disentangling Privileged Knowledge in LLM Correctness (2026.acl-long)
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| Challenge: | Recent research suggests large language models encode meta-information about their own outputs. |
| Approach: | They investigate whether large language models possess similar privileged knowledge about answer correctness . they train correctness classifiers on question representations from a model’s hidden states and external models . |
| Outcome: | The proposed model outperforms peer-model models in factual knowledge tasks, but shows no advantage in math reasoning. |
Automatic Argument Quality Assessment - New Datasets and Methods (D19-1)
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Assaf Toledo, Shai Gretz, Edo Cohen-Karlik, Roni Friedman, Elad Venezian, Dan Lahav, Michal Jacovi, Ranit Aharonov, Noam Slonim
| Challenge: | 6.3k arguments were collected from contributors of various levels, and are released as part of this work. |
| Approach: | They propose to use a language model to annotate arguments for argument ranking and argument-pair classification. |
| Outcome: | The proposed methods outperform state-of-the-art methods in the argument ranking task and argument-pair classification task. |
Zero-shot Topical Text Classification with LLMs - an Experimental Study (2023.findings-emnlp)
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Shai Gretz, Alon Halfon, Ilya Shnayderman, Orith Toledo-Ronen, Artem Spector, Lena Dankin, Yannis Katsis, Ofir Arviv, Yoav Katz, Noam Slonim, Liat Ein-Dor
| Challenge: | Topical text classification is an ancient, yet timely research area in natural language processing. |
| Approach: | They compare the zero-shot performance of a variety of LMs over a large dataset of 23 publicly available TTC datasets. |
| Outcome: | The proposed models outperform their counterparts over a large dataset and show that they perform better in a zero-shot scenario. |
Towards an argumentative content search engine using weak supervision (C18-1)
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| Challenge: | Existing work focused on detecting claims within a small set of documents . however, pinpointing relevant claims within massive unstructured corpora, received little attention. |
| Approach: | They propose to use a weak signal to develop a query for claim–sentence detection using a large text corpus. |
| Outcome: | The proposed system outperforms previous results in terms of precision and coverage. |
Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine Hesitancy (2023.findings-eacl)
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Shai Gretz, Assaf Toledo, Roni Friedman, Dan Lahav, Rose Weeks, Naor Bar-Zeev, João Sedoc, Pooja Sangha, Yoav Katz, Noam Slonim
| Challenge: | As COVID-19 vaccines were rolled out, they were met with widespread hesitancy. |
| Approach: | They propose a new framework for intent discovery that leverages existing intent classifiers to provide a real-world conversational dataset of conversations conducted by actual users with VIRA. |
| Outcome: | The proposed framework enables users to find out what they are doing and why they are hesitant. |
The workweek is the best time to start a family – A Study of GPT-2 Based Claim Generation (2020.findings-emnlp)
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| Challenge: | Argument generation is a challenging task whose impact on social media is growing . we examine how argument generation can be enhanced to provide better arguments . |
| Approach: | They propose a pipeline for argument generation based on GPT-2 . they examine the types of claims it produces, and their veracity . |
| Outcome: | The proposed pipeline improves argument generation quality and provides a clear stance on a debate topic. |