14 citations · 30 across the 9 of their papers we have counts for
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cs.AI2026
Beyond Accuracy: Evaluating Strategy Diversity in LLM Mathematical Reasoning
Xia Yang, Xuanyi Zhang, Hao Hu +1
Large language models now achieve high final-answer accuracy on mathematical reasoning benchmarks, but accuracy alone does not capture reasoning flexibility. We introduce a strateg…
cs.AI2025
StepHint: Multi-level Stepwise Hints Enhance Reinforcement Learning to Reason
Kaiyi Zhang, Ang Lv, Jinpeng Li +4
Reinforcement learning with verifiable rewards (RLVR) is a promising approach for improving the complex reasoning abilities of large language models (LLMs). However, current RLVR m…
cs.AI2025★ 12 cited
Kimi k1.5: Scaling Reinforcement Learning with LLMs
Kimi Team, Angang Du, Bofei Gao +93
Language model pretraining with next token prediction has proved effective for scaling compute but is limited to the amount of available training data. Scaling reinforcement learni…