5 papers · 1 filter
Automatic Annotation Augmentation Boosts Translation between Molecules and Natural Language
Zhiqiang Zhong, Simon Sataa-Yu Larsen, Haoyu Guo +3
Recent advancements in AI for biological research focus on integrating molecular data with natural language to accelerate drug discovery. However, the scarcity of high-quality anno…
Exploring Graph Structure Comprehension Ability of Multimodal Large Language Models: Case Studies
Zhiqiang Zhong, Davide Mottin
Large Language Models (LLMs) have shown remarkable capabilities in processing various data structures, including graphs. While previous research has focused on developing textual e…
Efficiently Predicting Mutational Effect on Homologous Proteins by Evolution Encoding
Zhiqiang Zhong, Davide Mottin
Predicting protein properties is paramount for biological and medical advancements. Current protein engineering mutates on a typical protein, called the wild-type, to construct a f…
Harnessing Large Language Models as Post-hoc Correctors
Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin
As Machine Learning (ML) models grow in size and demand higher-quality training data, the expenses associated with re-training and fine-tuning these models are escalating rapidly.…
Benchmarking Large Language Models for Molecule Prediction Tasks
Zhiqiang Zhong, Kuangyu Zhou, Davide Mottin
Large Language Models (LLMs) stand at the forefront of a number of Natural Language Processing (NLP) tasks. Despite the widespread adoption of LLMs in NLP, much of their potential…