8 citations · 9 across the 32 of their papers we have counts for
9 papers · 2 filters
Clinical Intent Extraction: A FHIR-Aligned Representation and the CIRCA Benchmark
Alexander Apartsin, Yehudit Aperstein
Prospective clinical actions, the follow-ups, orders, referrals, and instructions that deter-mine what happens to a patient next, are annotated today in thin fragments across incom…
Clinical Communication Processing with Models Trained on LLM-Generated Synthetic Data: A Structured Survey and Novel Application Case Studies
Alexander Apartsin, Yehudit Aperstein
Much clinical value is conveyed not through structured records but through communication: exchanges in which patients describe symptoms, clinicians reason and give instructions, am…
CoEval: Ranking Language Models for Custom Tasks Without Labeled Data or Trustworthy Benchmarks
Alexander Apartsin, Yehudit Aperstein
Selecting a pretrained language model, or evaluating a fine-tuned one, for a specific application is a high-value decision, yet the public benchmarks used to make it are poorly sui…
Reliable Extraction of Clinical Follow-Up Instructions: A Hybrid Neural-Symbolic Pipeline
Michal Laufer, Yehudit Aperstein, Alexander Apartsin
Objective. Outpatient notes carry follow-up instructions pairing actions with future times ("MRI brain in two weeks"). Extracting (action, date) pairs supports scheduling and audit…
Toward a Benchmark for Controllable Simulation of Imperfect Students with Large Language Models
Alexander Apartsin, Omri Sason, Yehudit Aperstein
Teacher education requires deliberate practice with learners who exhibit identifiable strengths, weaknesses, and partial mastery. Large language models could support such practice…
A Controlled Synthetic Benchmark for Educational Aspect-Based Sentiment Analysis
Yehudit Aperstein, Alexander Apartsin
Educational aspect-based sentiment analysis (ABSA) can support course improvement, but public aspect-labeled student feedback remains scarce because educational reviews are private…
IRC-Bench: Recognizing Entities from Contextual Cues in First-Person Reminiscences
Yehudit Aperstein, Eden Moran, Alexander Apartsin
When people recount personal memories, they often refer to people, places, and events indirectly, relying on con-textual cues rather than explicit names. Such implicit references a…
SeaAlert: Robust Severity Classification and LLM-Based Information Extraction for Noisy Maritime Distress Communications
Tomer Atia, Yehudit Aperstein, Alexander Apartsin
Maritime distress communications transmitted over very high frequency (VHF) radio are safety-critical voice messages used to report emergencies at sea. Under the Global Maritime Di…
LLM-guided headline rewriting for clickability enhancement without clickbait
Yehudit Aperstein, Linoy Halifa, Sagiv Bar +1
Enhancing reader engagement while preserving informational fidelity is a central challenge in controllable text generation for news media. Optimizing news headlines for reader enga…