12 papers
When Retain Constraints Conflict: Mitigating Forget-Retain Interference in Tabular Data
Zijie Liu, Jinhao Duan, Bingqi Shang +3
Machine unlearning aims to remove the influence of designated training data while preserving model utility, but its behavior on tabular data remains underexplored. This gap is impo…
DrugReason: Dynamic Multi-View Reasoning over Knowledge Graph and Language Evidence for Drug Repurposing
Zijie Liu, Hongxuan Li, Zhen Tan +5
Drug repurposing aims to identify new therapeutic uses for existing compounds and, compared with de novo drug discovery, offers a faster and more cost-effective path to clinical tr…
Stochastic Meta-Unlearning: Bridging Language Backbone and Multimodal Unlearning
Zijie Liu, Jinhao Duan, Gaowen Liu +2
Machine unlearning for vision-language models (VLMs) remains underexplored. Unlike language models, VLMs combine a language backbone with visual components, which makes unlearning…
RAVEN: Agentic RAG for Automated Vulnerability Repair
Varun Gadey, Zijie Liu, Alexandra Dmitrienko
Automated vulnerability repair has emerged as a promising direction to mitigate the growing number of software vulnerabilities. Recent advances in Large Language Models (LLMs) have…
GEMQ: Global Expert-Level Mixed-Precision Quantization for MoE LLMs
Jianing Deng, Song Wang, Dongwei Wang +4
Mixture-of-Experts Large Language Models (MoE-LLMs) achieve strong performance but incur substantial memory overhead due to massive expert parameters. Mixed-precision quantization…
SWE-Next: Scalable Real-World Software Engineering Tasks for Agents
Jiarong Liang, Zhiheng Lyu, Zijie Liu +4
Executable software engineering data is valuable for training SWE agents, but scaling it remains difficult for two reasons: only a small fraction of real repository changes yield v…