Papers by Guy Mor-Lan

6 papers
The Enemy from Within: A Study of Political Delegitimization Discourse in Israeli Political Speech (2025.emnlp-main)

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Challenge: a new computational model for political delegitimization discourse is proposed for analysis of democratic discourse . we identify the importance of PDD as a powerful tool in political competition .
Approach: They propose a computational classification pipeline for political delegitimization discourse . they annotate a Hebrew-language corpus of 10,410 sentences from parliamentary speeches, facebook posts and leading news outlets .
Outcome: The proposed model achieves an F1 of 0.74 for binary detection and a macro-F1 of 0.6 for classification of delegitimization characteristics.
FactAppeal: Identifying Epistemic Factual Appeals in News Media (2026.findings-eacl)

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Challenge: Existing methods focus on the content of factual statements and ignore the epistemic structures that confer credibility and persuasive force to these claims.
Approach: They propose a task of Epistemic Appeal Identification to identify whether and how factual statements have been anchored by external sources or evidence.
Outcome: The proposed task identifies whether and how factual statements have been anchored by external sources or evidence.
Exploring Factual Entailment with NLI: A News Media Study (2024.starsem-1)

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Challenge: Recent studies have focused on the relationship between factuality and Natural Language Inference (NLI).
Approach: They propose a novel annotation scheme that models factual rather than textual entailment and use it to annotate a dataset of naturally occurring sentences from news articles.
Outcome: The proposed annotation scheme can be used to model factual relationships on a dataset of naturally occurring sentences from news articles.
HebID: Detecting Social Identities in Hebrew-language Political Text (2025.findings-emnlp)

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Challenge: Existing NLP datasets focus on coarse-grained identity categories . existing datasets are mostly English-centric and focus on fine-grain categories based on cultural contexts.
Approach: They introduce the first multilabel Hebrew corpus for social identity detection . they use Hebrew-tuned encoders alongside 2B-9B-parameter decoders .
Outcome: The proposed classifier is based on a national public survey and uses Hebrew-tuned encoders to analyze political discourse and political speeches.
IsraParlTweet: The Israeli Parliamentary and Twitter Resource (2024.lrec-main)

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Challenge: IsraParlTweet is a linked corpus of parliamentary discussions from the Knesset between 1992-2023 and Twitter posts made by Members of the Kneset between 2008-2023.
Approach: They propose a linked corpus of parliamentary discussions from the Knesset between 1992-2023 and Twitter posts made by Members of the Kneset between 2008-2023.
Outcome: IsraParlTweet can be used to conduct quantitative and qualitative analyses and provide valuable insights into political discourse in Israel.
Location Not Found: Exposing Implicit Local and Global Biases in Multilingual LLMs (2026.acl-long)

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Challenge: Multilingual large language models have minimized the fluency gap between languages, but they are exposed to the risk of biases as knowledge and norms may propagate across languages.
Approach: They propose a test set with 2,156 questions in 12 languages to quantify models' biases . they show a global bias towards answers relevant to the US-locale .
Outcome: The proposed model can answer locale-ambiguous questions in 12 languages.

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