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20232026
most citedScientific Large Language Models: A Survey on Biological & Chemical Domains

34 citations · 62 across the 14 of their papers we have counts for

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6 papers · 1 filter

cs.CL2024★ 2 cited

MKGL: Mastery of a Three-Word Language

Lingbing Guo, Zhongpu Bo, Zhuo Chen +10

Large language models (LLMs) have significantly advanced performance across a spectrum of natural language processing (NLP) tasks. Yet, their application to knowledge graphs (KGs),…

cs.CL2024★ 7 cited

Advancing biomolecular understanding and design following human instructions

Xiang Zhuang, Keyan Ding, Tianwen Lyu +9

Understanding and designing biomolecules, such as proteins and small molecules, is central to advancing drug discovery, synthetic biology and enzyme engineering. Recent breakthroug…

cs.CL2024★ 6 cited

SciSafeEval: A Comprehensive Benchmark for Safety Alignment of Large Language Models in Scientific Tasks

Tianhao Li, Jingyu Lu, Chuangxin Chu +12

Large language models (LLMs) have a transformative impact on a variety of scientific tasks across disciplines including biology, chemistry, medicine, and physics. However, ensuring…

cs.LG2024

Sample-Efficient Human Evaluation of Large Language Models via Maximum Discrepancy Competition

Kehua Feng, Keyan Ding, Hongzhi Tan +8

Reliable evaluation of large language models (LLMs) is impeded by two key challenges: objective metrics often fail to reflect human perception of natural language, and exhaustive h…

cs.CL2024

StableMask: Refining Causal Masking in Decoder-only Transformer

Qingyu Yin, Xuzheng He, Xiang Zhuang +4

The decoder-only Transformer architecture with causal masking and relative position encoding (RPE) has become the de facto choice in language modeling. Despite its exceptional perf…

cs.CL2024★ 34 cited

Scientific Large Language Models: A Survey on Biological & Chemical Domains

Qiang Zhang, Keyang Ding, Tianwen Lyv +22

Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelli…