23 citations · 51 across the 8 of their papers we have counts for
8 papers
Understanding Usage and Engagement in AI-Powered Scientific Research Tools: The Asta Interaction Dataset
Dany Haddad, Dan Bareket, Joseph Chee Chang +19
AI-powered scientific research tools are rapidly being integrated into research workflows, yet the field lacks a clear lens into how researchers use these systems in real-world set…
AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite
Jonathan Bragg, Mike D'Arcy, Nishant Balepur +36
AI agents hold the potential to revolutionize scientific productivity by automating literature reviews, replicating experiments, analyzing data, and even proposing new directions o…
Do Pretrained Contextual Language Models Distinguish between Hebrew Homograph Analyses?
Avi Shmidman, Cheyn Shmuel Shmidman, Dan Bareket +2
Semitic morphologically-rich languages (MRLs) are characterized by extreme word ambiguity. Because most vowels are omitted in standard texts, many of the words are homographs with…
The Perfect Victim: Computational Analysis of Judicial Attitudes towards Victims of Sexual Violence
Eliya Habba, Renana Keydar, Dan Bareket +1
We develop computational models to analyze court statements in order to assess judicial attitudes toward victims of sexual violence in the Israeli court system. The study examines…
Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All
Eylon Gueta, Avi Shmidman, Shaltiel Shmidman +6
We present a new pre-trained language model (PLM) for modern Hebrew, termed AlephBERTGimmel, which employs a much larger vocabulary (128K items) than standard Hebrew PLMs before. W…
AlephBERT:A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application With
Amit Seker, Elron Bandel, Dan Bareket +3
Large Pre-trained Language Models (PLMs) have become ubiquitous in the development of language understanding technology and lie at the heart of many artificial intelligence advance…
Neural Modeling for Named Entities and Morphology (NEMO^2)
Dan Bareket, Reut Tsarfaty
Named Entity Recognition (NER) is a fundamental NLP task, commonly formulated as classification over a sequence of tokens. Morphologically-Rich Languages (MRLs) pose a challenge to…
From SPMRL to NMRL: What Did We Learn (and Unlearn) in a Decade of Parsing Morphologically-Rich Languages (MRLs)?
Reut Tsarfaty, Dan Bareket, Stav Klein +1
It has been exactly a decade since the first establishment of SPMRL, a research initiative unifying multiple research efforts to address the peculiar challenges of Statistical Pars…