3 papers
cs.AI2026
The Shadow Price of Reasoning: Economic Perspective on Optimal Budget Allocation for LLMs
Xu Wan, Speed Zhu, Jianwei Cai +4
Inference-time scaling has emerged as a critical avenue for enhancing Large Language Models' performance, yet real-world deployment is constrained by strict computational budgets.…
cs.LG2025
DRIVE: Data Curation Best Practices for Reinforcement Learning with Verifiable Reward in Competitive Code Generation
Speed Zhu, Jianwei Cai, Guang Chen +3
Recent reasoning-first models (e.g., OpenAI o1, DeepSeek R1) have spurred a resurgence of interest in RLVR. Nevertheless, advances are dominated by mathematics (e.g., AIME), with c…
cs.CL2025
AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators
Jason Chou, Ao Liu, Yuchi Deng +13
Large Language Models (LLMs) have demonstrated remarkable capabilities across various domains, with code generation emerging as a key area of focus. While numerous benchmarks have…