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Thomas Lin

5 accepted papers

2025

A Modular Approach for Clinical SLMs Driven by Synthetic Data with Pre-Instruction Tuning, Model Merging, and Clinical-Tasks Alignment

ACL 2025long

High computation costs and latency of large language models such as GPT-4 have limited their deployment in clinical settings. Small language models (SLMs) offer a cost-effective alternative, but their limited capacity requires biomedical domain adaptation, which remains challenging. An additional bo…

Cited by 0SourcePDFScholar
2025

MEDEC: A Benchmark for Medical Error Detection and Correction in Clinical Notes

ACL 2025finding

Several studies have shown that Large Language Models (LLMs) can answer medical questions correctly, even outperforming the average human score in some medical exams. However, to our knowledge, no study has been conducted to assess the ability of language models to validate existing or generated med…

2024

On Computational Limits of Modern Hopfield Models: A Fine-Grained Complexity Analysis

ICML 2024poster

We investigate the computational limits of the memory retrieval dynamics of modern Hopfield models from the fine-grained complexity analysis. Our key contribution is the characterization of a phase transition behavior in the efficiency of all possible modern Hopfield models based on the norm of patt…

Cited by 44SourcePDFScholar
2023

An Investigation of Evaluation Methods in Automatic Medical Note Generation

ACL 2023findings

Recent studies on automatic note generation have shown that doctors can save significant amounts of time when using automatic clinical note generation (Knoll et al., 2022). Summarization models have been used for this task to generate clinical notes as summaries of doctor-patient conversations (Kris…

2022

MedicalSum: A Guided Clinical Abstractive Summarization Model for Generating Medical Reports from Patient-Doctor Conversations

EMNLP 2022finding

We introduce MedicalSum, a transformer-based sequence-to-sequence architecture for summarizing medical conversations by integrating medical domain knowledge from the Unified Medical Language System (UMLS). The novel knowledge augmentation is performed in three ways: (i) introducing a guidance signal…

Cited by 38SourcePDFScholar