5 papers
Hybrid-Policy Self-Editing for Composable Unstructured Knowledge Editing
Tianci Liu, Zihan Dong, Tianchun Li +8
Large language models (LLMs) achieve remarkable performance across natural language tasks, yet they are trained on static corpora and their knowledge quickly becomes outdated in a…
Uncovering Latent Pathological Signatures in Pulmonary CT via Cross-Window Knowledge Distillation
Bo Peng, Wujian Xu, Kun Wang +8
Multi-window CT imaging captures complementary pathological information across anatomical structures of differing densities, yet existing deep learning methods fuse representations…
LegalDrill: Diagnosis-Driven Synthesis for Legal Reasoning in Small Language Models
Tianchun Li, Haochen Liu, Vishwa Pardeshi +5
Small language models (SLMs) are promising for real-world deployment due to their efficiency and low operational cost. However, their limited capacity struggles with high-stakes le…
Towards Privacy-Preserving and Heterogeneity-aware Split Federated Learning via Probabilistic Masking
Xingchen Wang, Feijie Wu, Chenglin Miao +5
Split Federated Learning (SFL) has emerged as an efficient alternative to traditional Federated Learning (FL) by reducing client-side computation through model partitioning. Howeve…
Towards Universal Debiasing for Language Models-based Tabular Data Generation
Tianchun Li, Tianci Liu, Xingchen Wang +4
Large language models (LLMs) have achieved promising results in tabular data generation. However, inherent historical biases in tabular datasets often cause LLMs to exacerbate fair…