3 papers
cs.CR2026
TamperBench: Systematically Stress-Testing LLM Safety Under Fine-Tuning and Tampering
Saad Hossain, Tom Tseng, Punya Syon Pandey +8
As increasingly capable open-weight large language models (LLMs) are deployed, improving their tamper resistance against unsafe modifications, whether accidental or intentional, be…
cs.LG2025
Geometrically Principled Randomized Optimization for Efficient LLM Training
Sahar Rajabi, Nayeema Nonta, Sirisha Rambhatla
Low-rank gradient optimization for large language models is currently divided into two categories: structured methods that rigorously identify subspaces, and randomized approaches…
cs.LG2025
SubTrack++ : Gradient Subspace Tracking for Scalable LLM Training
Sahar Rajabi, Nayeema Nonta, Sirisha Rambhatla
Training large language models (LLMs) is highly resource-intensive due to their massive number of parameters and the overhead of optimizer states. While recent work has aimed to re…