3 papers
cs.LG2025
LSPO: Length-aware Dynamic Sampling for Policy Optimization in LLM Reasoning
Weizhe Chen, Sven Koenig, Bistra Dilkina
Since the release of Deepseek-R1, reinforcement learning with verifiable rewards (RLVR) has become a central approach for training large language models (LLMs) on reasoning tasks.…
cs.CL2025
Iterative Deepening Sampling as Efficient Test-Time Scaling
Weizhe Chen, Sven Koenig, Bistra Dilkina
Recent reasoning models, such as OpenAI's O1 series, have demonstrated exceptional performance on complex reasoning tasks and revealed new test-time scaling laws. Inspired by this,…
cs.LG2024
Flaming-hot Initiation with Regular Execution Sampling for Large Language Models
Weizhe Chen, Zhicheng Zhang, Guanlin Liu +6
Since the release of ChatGPT, large language models (LLMs) have demonstrated remarkable capabilities across various domains. A key challenge in developing these general capabilitie…