1 citations · 1 across the 7 of their papers we have counts for
7 papers
HSMLog: Small Language Model-Assisted Hardware Security Module Log Anomaly Detection with Behavioral Analysis
Chia-Hsuan Wu, Dar-Hsin Dustin Wu, Rui Fang +3
Hardware Security Module (HSM) logs capture security-critical behavior, but anomalies emerge from relationships across event sequences, keys, object states, sessions, and temporal…
Action with Visual Primitives
Weilong Guo, Yuchen Wang, Renping Zhou +5
Vision-Language-Action (VLA) models have emerged as a promising paradigm for generalist robotic manipulation. A common design in current architectures maps language instructions an…
Interference-Aware Multi-Task Unlearning
Ying-Hua Huang, Rui Fang, Hsi-Wen Chen +1
Machine unlearning aims to remove the contribution of designated training data from a trained model while preserving performance on the remaining data. Existing work mainly focuses…
LoopQ: Quantization for Looped Language Models
Rui Fang, Hsi-Wen Chen, Ming-Syan Chen +1
Looped language models (LoopLMs) increase effective computational depth by repeatedly applying shared Transformer blocks without increasing the parameter count. However, this reuse…
Amortized-Precision Quantization for Early-Exit Vision Transformers
Rui Fang, Hsi-Wen Chen, Ming-Syan Chen
Vision Transformers (ViTs) achieve strong performance across vision tasks, yet their deployment with low-precision early exiting remains fragile. Existing quantization methods assu…
KV Admission: Learning What to Write for Efficient Long-Context LLM Inference
Yen-Chieh Huang, Pi-Cheng Hsiu, Rui Fang +1
Long-context LLM inference is bottlenecked by the quadratic attention complexity and linear Key-Value (KV) cache growth. Prior approaches mitigate this via post-hoc selection or ev…
Dual Adversarial Alignment for Realistic Support-Query Shift Few-shot Learning
Siyang Jiang, Rui Fang, Hsi-Wen Chen +2
Support-query shift few-shot learning aims to classify unseen examples (query set) to labeled data (support set) based on the learned embedding in a low-dimensional space under a d…