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From the 1 of 9 linked papers with an AI index.

activity
20242026
collaborators

8 papers

q-bio.QM2026

TheBioCollection: Unified Pre-Training Scale LLM Corpus for Biology

Hyunjin Seo, Hyeon Hwang, Gyubok Lee +7

The paper introduces TheBioCollection, a 52.6‑billion‑token unified corpus that aggregates diverse biological resources for pre‑training large language models, and shows that train…

cs.LG2026

Leveraging Biokinetic Knowledge Priors for Data-Scarce Bioprocess Modeling

Kyunghoon Hur, Eunjung Jeon, Hyun Woo Kim +2

While deep learning has accelerated drug discovery, its impact on biomanufacturing has been considerably more limited. The reason is data scarcity. Bioreactor experiments are high-…

q-bio.QM2026

VibeProteinBench: An Evaluation Benchmark for Language-interfaced Vibe Protein Design

Hyunjin Seo, Hongjoon Ahn, Jimin Park +16

Protein design aims to compose amino-acid sequences that fold into stable three-dimensional structures while satisfying targeted functional properties. The field is increasingly sh…

cs.CL2026

EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records

Gyubok Lee, Hyeonji Hwang, Seongsu Bae +6

We present a new text-to-SQL dataset for electronic health records (EHRs). The utterances were collected from 222 hospital staff members, including physicians, nurses, and insuranc…

cs.AI2026

From Conversation to Query Execution: Benchmarking User and Tool Interactions for EHR Database Agents

Gyubok Lee, Woosog Chay, Heeyoung Kwak +5

Despite the impressive performance of LLM-powered agents, their adoption for Electronic Health Record (EHR) data access remains limited by the absence of benchmarks that adequately…

cs.CL2025

SCARE: A Benchmark for SQL Correction and Question Answerability Classification for Reliable EHR Question Answering

Gyubok Lee, Woosog Chay, Edward Choi

Recent advances in Large Language Models (LLMs) have enabled the development of text-to-SQL models that allow clinicians to query structured data stored in Electronic Health Record…