18 citations · 24 across the 8 of their papers we have counts for
9 papers
Enhancing LLM Medical Coding with Structured External Knowledge
Yidong Gan, David D. Nguyen, Yang Lin +4
Accurate medical coding requires consulting authoritative resources such as the ICD tabular list and coding guidelines. Existing LLM-based automated methods largely rely on LLMs' i…
MedDCR: Learning to Design Agentic Workflows for Medical Coding
Jiyang Zheng, Islam Nassar, Thanh Vu +5
Medical coding converts free-text clinical notes into standardized diagnostic and procedural codes, which are essential for billing, hospital operations, and medical research. Unli…
Taming the Real-world Complexities in CPT E/M Coding with Large Language Models
Islam Nassar, Yang Lin, Yuan Jin +8
Evaluation and Management (E/M) coding, under the Current Procedural Terminology (CPT) taxonomy, documents medical services provided to patients by physicians. Used primarily for b…
OraPO: Oracle-educated Reinforcement Learning for Data-efficient and Factual Radiology Report Generation
Zhuoxiao Chen, Hongyang Yu, Ying Xu +3
Radiology report generation (RRG) aims to automatically produce clinically faithful reports from chest X-ray images. Prevailing work typically follows a scale-driven paradigm, by m…
Distill-C: Enhanced NL2SQL via Distilled Customization with LLMs
Cong Duy Vu Hoang, Gioacchino Tangari, Clemence Lanfranchi +10
The growing adoption of large language models (LLMs) in business applications has amplified interest in Natural Language to SQL (NL2SQL) solutions, in which there is competing dema…
SQLong: Enhanced NL2SQL for Longer Contexts with LLMs
Dai Quoc Nguyen, Cong Duy Vu Hoang, Duy Vu +5
Open-weight large language models (LLMs) have significantly advanced performance in the Natural Language to SQL (NL2SQL) task. However, their effectiveness diminishes when dealing…
Mastering the Craft of Data Synthesis for CodeLLMs
Meng Chen, Philip Arthur, Qianyu Feng +13
Large language models (LLMs) have shown impressive performance in \emph{code} understanding and generation, making coding tasks a key focus for researchers due to their practical a…
An Unsupervised Probability Model for Speech-to-Translation Alignment of Low-Resource Languages
Antonios Anastasopoulos, David Chiang, Long Duong
For many low-resource languages, spoken language resources are more likely to be annotated with translations than with transcriptions. Translated speech data is potentially valuabl…
Learning Crosslingual Word Embeddings without Bilingual Corpora
Long Duong, Hiroshi Kanayama, Tengfei Ma +2
Crosslingual word embeddings represent lexical items from different languages in the same vector space, enabling transfer of NLP tools. However, previous attempts had expensive res…