2 papers
cs.CR2026
Leaky Language Models: Stealing Architecture and Inference Optimizations via Per-Token Timing
Sadegh Majidi, Niloofar Mireshghallah, Kazem Taram
This work presents LeakyLMs, a set of attacks that leak proprietary model, architecture, and deployment information from production language models. LeakyLMs is the first to demons…
cs.AI2025
From Building Blocks to Planning: Multi-Step Spatial Reasoning in LLMs with Reinforcement Learning
Amir Tahmasbi, Sadegh Majidi, Kazem Taram +1
Spatial reasoning in large language models (LLMs) has gained increasing attention due to applications in navigation and planning. Despite strong general language capabilities, LLMs…