4 citations · 9 across the 11 of their papers we have counts for
3 papers · 1 filter
LoFT: Local Proxy Fine-tuning For Improving Transferability Of Adversarial Attacks Against Large Language Model
Muhammad Ahmed Shah, Roshan Sharma, Hira Dhamyal +10
It has been shown that Large Language Model (LLM) alignments can be circumvented by appending specially crafted attack suffixes with harmful queries to elicit harmful responses. To…
On Feature Importance and Interpretability of Speaker Representations
Frederik Rautenberg, Michael Kuhlmann, Jana Wiechmann +3
Unsupervised speech disentanglement aims at separating fast varying from slowly varying components of a speech signal. In this contribution, we take a closer look at the embedding…
Investigating Speaker Embedding Disentanglement on Natural Read Speech
Michael Kuhlmann, Adrian Meise, Fritz Seebauer +2
Disentanglement is the task of learning representations that identify and separate factors that explain the variation observed in data. Disentangled representations are useful to i…