7 citations · 15 across the 5 of their papers we have counts for
5 papers
Knowledge Index of Noah's Ark
Sheng Jin, Minghao Liu, Yunze Xiao +24
Knowledge benchmarks for LLMs face three issues: scaling-driven designs that do not operationalize disciplinary representativeness; flat-payment annotation that permits lazy consen…
Dr. DocBench: A Comprehensive Benchmark for Expert-Level and Difficult Document Parsing
Minglai Yang, Xinyan Velocity Yu, Pengyuan Li +22
Document parsing and recognition are fundamental capabilities for vision-language models (VLMs) and document processing systems. However, existing Optical Character Recognition (OC…
MatExpert: Decomposing Materials Discovery by Mimicking Human Experts
Qianggang Ding, Santiago Miret, Bang Liu
Material discovery is a critical research area with profound implications for various industries. In this work, we introduce MatExpert, a novel framework that leverages Large Langu…
HoneyComb: A Flexible LLM-Based Agent System for Materials Science
Huan Zhang, Yu Song, Ziyu Hou +2
The emergence of specialized large language models (LLMs) has shown promise in addressing complex tasks for materials science. Many LLMs, however, often struggle with distinct comp…
HoneyBee: Progressive Instruction Finetuning of Large Language Models for Materials Science
Yu Song, Santiago Miret, Huan Zhang +1
We propose an instruction-based process for trustworthy data curation in materials science (MatSci-Instruct), which we then apply to finetune a LLaMa-based language model targeted…