42 citations · 81 across the 24 of their papers we have counts for
11 papers · 1 filter
NL-Eye: Abductive NLI for Images
Mor Ventura, Michael Toker, Nitay Calderon +3
Will a Visual Language Model (VLM)-based bot warn us about slipping if it detects a wet floor? Recent VLMs have demonstrated impressive capabilities, yet their ability to infer out…
Are LLMs Better than Reported? Detecting Label Errors and Mitigating Their Effect on Model Performance
Omer Nahum, Nitay Calderon, Orgad Keller +2
NLP benchmarks rely on standardized datasets for training and evaluating models and are crucial for advancing the field. Traditionally, expert annotations ensure high-quality label…
LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations
Hadas Orgad, Michael Toker, Zorik Gekhman +4
Large language models (LLMs) often produce errors, including factual inaccuracies, biases, and reasoning failures, collectively referred to as "hallucinations". Recent studies have…
A Systematic Review of NLP for Dementia -- Tasks, Datasets and Opportunities
Lotem Peled-Cohen, Roi Reichart
The close link between cognitive decline and language has fostered long-standing collaboration between the NLP and medical communities in dementia research. To examine this, we rev…
On Behalf of the Stakeholders: Trends in NLP Model Interpretability in the Era of LLMs
Nitay Calderon, Roi Reichart
Recent advancements in NLP systems, particularly with the introduction of LLMs, have led to widespread adoption of these systems by a broad spectrum of users across various domains…
Can LLMs Learn Macroeconomic Narratives from Social Media?
Almog Gueta, Amir Feder, Zorik Gekhman +2
This study empirically tests the hypothesis, which posits that narratives (ideas that are spread virally and affect public beliefs) can influence eco…
Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?
Zorik Gekhman, Gal Yona, Roee Aharoni +4
When large language models are aligned via supervised fine-tuning, they may encounter new factual information that was not acquired through pre-training. It is often conjectured th…
Bored to Death: Artificial Intelligence Research Reveals the Role of Boredom in Suicide Behavior
Shir Lissak, Yaakov Ophir, Refael Tikochinski +4
Background: Recent advancements in Artificial Intelligence (AI) contributed significantly to suicide assessment, however, our theoretical understanding of this complex behavior is…
The Colorful Future of LLMs: Evaluating and Improving LLMs as Emotional Supporters for Queer Youth
Shir Lissak, Nitay Calderon, Geva Shenkman +4
Queer youth face increased mental health risks, such as depression, anxiety, and suicidal ideation. Hindered by negative stigma, they often avoid seeking help and rely on online re…
Systematic Biases in LLM Simulations of Debates
Amir Taubenfeld, Yaniv Dover, Roi Reichart +1
The emergence of Large Language Models (LLMs), has opened exciting possibilities for constructing computational simulations designed to replicate human behavior accurately. Current…
Can LLMs Replace Economic Choice Prediction Labs? The Case of Language-based Persuasion Games
Eilam Shapira, Omer Madmon, Roi Reichart +1
Human choice prediction in economic contexts is crucial for applications in marketing, finance, public policy, and more. This task, however, is often constrained by the difficultie…