91 citations · 270 across the 62 of their papers we have counts for
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Learning as Reasoning Unfolds: Progressive Rollout Allocation for Efficient Reinforcement Learning
Heyang Jiang, Henry Liu, Baharan Mirzasoleiman
Reinforcement learning with verifiable rewards (RLVR) has emerged as a highly effective framework for improving LLM reasoning, with methods such as GRPO among its most successful i…
Understanding the Role of Training Data in Test-Time Scaling
Adel Javanmard, Baharan Mirzasoleiman, Vahab Mirrokni
Test-time scaling improves the reasoning capabilities of large language models (LLMs) by allocating extra compute to generate longer Chains-of-Thoughts (CoTs). This enables models…
LoRA is All You Need for Safety Alignment of Reasoning LLMs
Yihao Xue, Baharan Mirzasoleiman
Reasoning-capable LLMs have achieved major breakthroughs in solving complex problems, but recent work shows that acquiring and deploying strong reasoning can introduce significant…
Bootstrapping LLM Robustness for VLM Safety via Reducing the Pretraining Modality Gap
Wenhan Yang, Spencer Stice, Ali Payani +1
Ensuring Vision-Language Models (VLMs) generate safe outputs is crucial for their reliable deployment. However, LVLMs suffer from drastic safety degradation compared to their LLM b…