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20242026
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cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…