6 papers · 1 filter
Compositional Performance Modeling of LLM Inference Clusters with Hierarchical KV Caching
Ruiyang Ma, Sheng Qi, DaiKang Kuang +2
Design-space exploration of LLM inference clusters requires predicting how hardware and serving policies interact with hierarchical key-value (KV) caching. Isolated operation profi…
Removing Information Content Does Not Certify Tamper Resistance in Open-Weight Models
Domenic Rosati, Alessa Carbo, Ali Dadsetan +5
Does removing harmful information make open-weight models resistant to fine-tuning attacks? We show that mutual information at release alone cannot universally certify slow recover…
GAPS: Dimension-Level Gates for Conditional Activation Steering
Moghis Fereidouni, Muhammad Umair Haider, Hassan Sajjad +1
Activation steering suppresses undesired behaviors in language models by adding a steering vector to the hidden state during generation. Recent conditional methods such as CAST and…
Distribution-Specific Curvature Control with Finite-Sample Guarantees for Open-Weight Safety
Domenic Rosati, Ali Dadsetan, Hong Huang +5
A short fine-tuning run can undo the safety guards of an open-weight model---retraining a refusal-trained assistant to aid weapons development or produce hate speech. Preventing su…
Limits of Convergence-Rate Control for Open-Weight Safety
Domenic Rosati, Xijie Zeng, Hong Huang +4
Open-weight foundation models can be fine-tuned for harmful purposes after release, yet no existing training resistance methods provide theoretical guarantees. Treating these inter…
Vector Quantized Latent Concepts: A Scalable Alternative to Clustering-Based Concept Discovery
Xuemin Yu, Ankur Garg, Samira Ebrahimi Kahou +1
Large language models (LLMs) encode rich semantic information in their hidden states, yet it remains difficult to understand what information these internal representations capture…