1 citations · 2 across the 7 of their papers we have counts for
11 papers
Correcting Contextual Deletions in DNA Nanopore Readouts
Yuan-Pon Chen, Olgica Milenkovic, João Ribeiro +1
The problem of designing codes for deletion-correction and synchronization has received renewed interest due to applications in DNA-based data storage systems that use nanopore seq…
Spatially-Coupled Network RNA Velocities: A Control-Theoretic Perspective
Boya Hou, Maxim Raginsky, Abhishek Pandey +1
RNA velocity is an important model that combines cellular spliced and unspliced RNA counts to infer dynamical properties of various regulatory functions. Despite its wide applicabi…
The Trojan Knowledge: Bypassing Commercial LLM Guardrails via Harmless Prompt Weaving and Adaptive Tree Search
Rongzhe Wei, Peizhi Niu, Xinjie Shen +7
Large language models (LLMs) remain vulnerable to jailbreak attacks that bypass safety guardrails to elicit harmful outputs. Existing approaches overwhelmingly operate within the p…
WaveletDiff: Multilevel Wavelet Diffusion For Time Series Generation
Yu-Hsiang Wang, Olgica Milenkovic
Time series are ubiquitous in many applications that involve forecasting, classification and causal inference tasks, such as healthcare, finance, audio signal processing and climat…
GUARD: Guided Unlearning and Retention via Data Attribution for Large Language Models
Peizhi Niu, Evelyn Ma, Huiting Zhou +4
Unlearning in large language models is becoming increasingly important due to regulatory compliance, copyright protection, and privacy concerns. However, a key challenge in LLM unl…
Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness
Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu +9
Machine unlearning techniques aim to mitigate unintended memorization in large language models (LLMs). However, existing approaches predominantly focus on the explicit removal of i…