NEURIPS 2025 "reasoning benchmarks" Papers
10 papers found
Accelerated Sampling from Masked Diffusion Models via Entropy Bounded Unmasking
Heli Ben-Hamu, Itai Gat, Daniel Severo et al.
NEURIPS 2025posterarXiv:2505.24857
40
citations
Activation Control for Efficiently Eliciting Long Chain-of-thought Ability of Language Models
Zekai Zhao, Qi Liu, Kun Zhou et al.
NEURIPS 2025spotlightarXiv:2505.17697
4
citations
HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts
Neil He, Rishabh Anand, Hiren Madhu et al.
NEURIPS 2025posterarXiv:2505.24722
8
citations
KLASS: KL-Guided Fast Inference in Masked Diffusion Models
Seo Hyun Kim, Sunwoo Hong, Hojung Jung et al.
NEURIPS 2025spotlightarXiv:2511.05664
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
Jonas Geiping, Sean McLeish, Neel Jain et al.
NEURIPS 2025spotlightarXiv:2502.05171
138
citations
SCOUT: Teaching Pre-trained Language Models to Enhance Reasoning via Flow Chain-of-Thought
Guanghao Li, Wenhao Jiang, Mingfeng Chen et al.
NEURIPS 2025posterarXiv:2505.24181
2
citations
SeRL: Self-play Reinforcement Learning for Large Language Models with Limited Data
Wenkai Fang, Shunyu Liu, Yang Zhou et al.
NEURIPS 2025posterarXiv:2505.20347
19
citations
SpecReason: Fast and Accurate Inference-Time Compute via Speculative Reasoning
Rui Pan, Yinwei Dai, Zhihao Zhang et al.
NEURIPS 2025posterarXiv:2504.07891
35
citations
SPMDM: Enhancing Masked Diffusion Models through Simplifing Sampling Path
Yichen Zhu, Weiyu Chen, James Kwok et al.
NEURIPS 2025poster
SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning
Xiao Liang, Zhong-Zhi Li, Yeyun Gong et al.
NEURIPS 2025posterarXiv:2506.08989
14
citations