97 citations · 146 across the 33 of their papers we have counts for
7 papers · 1 filter
Toward Secure Tuning: Mitigating Security Risks from Instruction Fine-Tuning
Yanrui Du, Sendong Zhao, Jiawei Cao +6
Instruction fine-tuning has emerged as a critical technique for customizing Large Language Models (LLMs) to specific applications. However, recent studies have highlighted signific…
MolFusion: Multimodal Fusion Learning for Molecular Representations via Multi-granularity Views
Muzhen Cai, Sendong Zhao, Haochun Wang +4
Artificial Intelligence predicts drug properties by encoding drug molecules, aiding in the rapid screening of candidates. Different molecular representations, such as SMILES and mo…
MoGU: A Framework for Enhancing Safety of Open-Sourced LLMs While Preserving Their Usability
Yanrui Du, Sendong Zhao, Danyang Zhao +6
Large Language Models (LLMs) are increasingly deployed in various applications. As their usage grows, concerns regarding their safety are rising, especially in maintaining harmless…
AS-ES Learning: Towards Efficient CoT Learning in Small Models
Nuwa Xi, Yuhan Chen, Sendong Zhao +3
Chain-of-Thought (CoT) serves as a critical emerging ability in LLMs, especially when it comes to logical reasoning. Attempts have been made to induce such ability in small models…
LLMs May Perform MCQA by Selecting the Least Incorrect Option
Haochun Wang, Sendong Zhao, Zewen Qiang +3
In the field of NLP, Large Language Models (LLMs) have markedly enhanced performance across a variety of tasks. However, the comprehensive evaluation of LLMs remains an inevitable…
Beyond Direct Diagnosis: LLM-based Multi-Specialist Agent Consultation for Automatic Diagnosis
Haochun Wang, Sendong Zhao, Zewen Qiang +3
Automatic diagnosis is a significant application of AI in healthcare, where diagnoses are generated based on the symptom description of patients. Previous works have approached thi…
MolTailor: Tailoring Chemical Molecular Representation to Specific Tasks via Text Prompts
Haoqiang Guo, Sendong Zhao, Haochun Wang +2
Deep learning is now widely used in drug discovery, providing significant acceleration and cost reduction. As the most fundamental building block, molecular representation is essen…