2 papers
cs.CL2026
Budget-Aware Anytime Reasoning with LLM-Synthesized Preference Data
Xuanming Zhang, Shwan Ashrafi, Aziza Mirsaidova +5
We study the reasoning behavior of large language models (LLMs) under limited computation budgets. In such settings, producing useful partial solutions quickly is often more practi…
cs.LG2025
Tree-based Dialogue Reinforced Policy Optimization for Red-Teaming Attacks
Ruohao Guo, Afshin Oroojlooy, Roshan Sridhar +3
Despite recent rapid progress in AI safety, current large language models remain vulnerable to adversarial attacks in multi-turn interaction settings, where attackers strategically…