3 papers
cs.LG2026
Retriever Portfolios: A Principled Approach to Adaptive RAG
Miltiadis Stouras, Vincent Cohen-Addad, Silvio Lattanzi +1
Retrieval-augmented generation (RAG) systems typically rely on a single retriever and a single set of hyperparameters, despite facing highly heterogeneous queries that range from s…
cs.LG2025
REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective
Simon Geisler, Tom Wollschläger, M. H. I. Abdalla +3
To circumvent the alignment of large language models (LLMs), current optimization-based adversarial attacks usually craft adversarial prompts by maximizing the likelihood of a so-c…
cs.LG2025
The Geometry of Refusal in Large Language Models: Concept Cones and Representational Independence
Tom Wollschläger, Jannes Elstner, Simon Geisler +3
The safety alignment of large language models (LLMs) can be circumvented through adversarially crafted inputs, yet the mechanisms by which these attacks bypass safety barriers rema…