4 papers
Breaking Bad: Interpretability-Based Safety Audits of State-of-the-Art LLMs
Krishiv Agarwal, Ramneet Kaur, Colin Samplawski +6
Effective safety auditing of large language models (LLMs) demands tools that go beyond black-box probing and systematically uncover vulnerabilities rooted in model internals. We pr…
Jailbreaking the Matrix: Nullspace Steering for Controlled Model Subversion
Vishal Pramanik, Maisha Maliha, Susmit Jha +1
Large language models remain vulnerable to jailbreak attacks -- inputs designed to bypass safety mechanisms and elicit harmful responses -- despite advances in alignment and instru…
Spatio-Temporal Pruning for Compressed Spiking Large Language Models
Yi Jiang, Malyaban Bal, Brian Matejek +3
Large Language Models (LLMs) present significant challenges for deployment in energy-constrained environments due to their large model sizes and high inference latency. Spiking Neu…
Debugging and Runtime Analysis of Neural Networks with VLMs (A Case Study)
Boyue Caroline Hu, Divya Gopinath, Corina S. Pasareanu +3
Debugging of Deep Neural Networks (DNNs), particularly vision models, is very challenging due to the complex and opaque decision-making processes in these networks. In this paper,…