1 citations · 1 across the 7 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.SE2026
ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models
Jiasheng Zheng, Xin Zheng, Boxi Cao +8
Code sandboxes have emerged as a critical infrastructure for advancing the coding capabilities of large language models, providing verifiable feedback for both RL training and eval…
cs.LG2026
Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
Zhengzhao Ma, Xueru Wen, Boxi Cao +6
Reinforcement Learning from Verifiable Rewards (RLVR) significantly enhances large language models (LLMs) reasoning but severely suffers from calibration degeneration, where models…
cs.AI2026
Empowering Small Language Models with Factual Hallucination-Aware Reasoning for Financial Classification
Han Yuan, Yilin Wu, Li Zhang +1
Small language models (SLMs) are increasingly used for financial classification due to their fast inference and local deployability. However, compared with large language models, S…