5 papers
TIGER: Text-Informed Generalized Enzyme-Reaction Retrieval
Yuhang Zhang, Keyan Ding, Peilin Chen +5
Enzyme-reaction retrieval is a fundamental problem in computational biology, underpinning enzyme characterization, reaction mechanism elucidation, and the rational design of metabo…
Position: Let's Develop Data Probes to Fundamentally Understand How Data Affects LLM Performance
Shiqiang Wang, Herbert Woisetschläger, Hans Arno Jacobsen +1
Data is fundamental to large language models (LLMs). However, understanding of what makes certain data useful for different stages of an LLM workflow, including training, tuning, a…
Preventing Rank Collapse in Federated Low-Rank Adaptation with Client Heterogeneity
Fei Wu, Jia Hu, Geyong Min +1
Federated low-rank adaptation (FedLoRA) has facilitated communication-efficient and privacy-preserving fine-tuning of foundation models for downstream tasks. In practical federated…
Efficient Orthogonal Fine-Tuning with Principal Subspace Adaptation
Fei Wu, Jia Hu, Geyong Min +1
Driven by the rapid growth of model parameters, parameter-efficient fine-tuning (PEFT) has become essential for adapting large models to diverse downstream tasks under constrained…
Adaptive Rank Allocation for Federated Parameter-Efficient Fine-Tuning of Language Models
Fei Wu, Jia Hu, Geyong Min +1
Pre-trained Language Models (PLMs) have demonstrated their superiority and versatility in modern Natural Language Processing (NLP), effectively adapting to various downstream tasks…