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Dedicated to advancing the capability of language models to perform complex reasoning tasks, enhancing their ability to understand and generate logical, contextually appropriate responses.
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Nemotron-Cascade: Scaling Cascaded Reinforcement Learning for General-Purpose Reasoning Models Boxin Wang Chankyu Lee Nayeon Lee Sheng-Chieh Lin Wenliang Dai ...Zhuolin Yang Zihan Liu Mohammad Shoeybi Bryan Catanzaro Wei Ping | |||
Reassessing the Role of Supervised Fine-Tuning: An Empirical Study in VLM Reasoning Yongcan Yu Lingxiao He Shuo Lu Lijun Sheng Yinuo Xu ...Meng Wang Qianlong Xie Xingxing Wang Dapeng Hu Jian Liang | |||
Liquid Reasoning Transformers: A Sudoku-Based Prototype for Chess-Scale Algorithmic Tasks Shivansh Sahni Wenzhi Zhang | |||
More Than the Final Answer: Improving Visual Extraction and Logical Consistency in Vision-Language Models Hoang Anh Just Yifei Fan Handong Zhao Jiuxiang Gu Ruiyi Zhang Simon Jenni Kushal Kafle Ruoxi Jia Jing Shi | |||
V-REX: Benchmarking Exploratory Visual Reasoning via Chain-of-Questions Chenrui Fan Yijun Liang Shweta Bhardwaj Kwesi Cobbina Ming Li Tianyi Zhou | |||
 When Actions Teach You to Think: Reasoning-Action Synergy via Reinforcement Learning in Conversational Agents Mrinal Rawat Arkajyoti Chakraborty Neha Gupta Roberto Pieraccini | |||
Hold Onto That Thought: Assessing KV Cache Compression On Reasoning Minghui Liu Aadi Palnitkar Tahseen Rabbani Hyunwoo Jae Kyle Rui Sang ...Fuheng Zhao Tian Li Ce Zhang Furong Huang Kunpeng Zhang | |||
 Asynchronous Reasoning: Training-Free Interactive Thinking LLMs George Yakushev Nataliia Babina Masoud Vahid Dastgerdi Vyacheslav Zhdanovskiy Alina Shutova Denis Kuznedelev | |||
 Motif-2-12.7B-Reasoning: A Practitioner's Guide to RL Training Recipes Junghwan Lim Sungmin Lee Dongseok Kim Taehyun Kim Eunhwan Park ...Kungyu Lee Dongpin Oh Yeongjae Park Bokki Ryu Dongjoo Weon | |||
 Reasoning Models Ace the CFA Exams Jaisal Patel Yunzhe Chen Kaiwen He Keyi Wang David Li Kairong Xiao Xiao-Yang Liu | |||
 On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models Charlie Zhang Graham Neubig Xiang Yue | |||
 FRIEDA: Benchmarking Multi-Step Cartographic Reasoning in Vision-Language Models Jiyoon Pyo Yuankun Jiao Dongwon Jung Zekun Li Leeje Jang ...Junyi Xie Hadi Askari Nan Xu Muhao Chen Yao-Yi Chiang | |||
 Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning Tong Wu Yang Liu Jun Bai Zixia Jia Shuyi Zhang Ziyong Lin Yanting Wang Song-Chun Zhu Zilong Zheng | |||
 Think-While-Generating: On-the-Fly Reasoning for Personalized Long-Form Generation Chengbing Wang Yang Zhang Wenjie Wang Xiaoyan Zhao Fuli Feng Xiangnan He Tat-Seng Chua | |||
 SymPyBench: A Dynamic Benchmark for Scientific Reasoning with Executable Python Code Shima Imani Seungwhan Moon Adel Ahmadyan Lu Zhang Kirmani Ahmed Babak Damavandi | |||
 PRiSM: An Agentic Multimodal Benchmark for Scientific Reasoning via Python-Grounded Evaluation Shima Imani Seungwhan Moon Adel Ahmadyan Lu Zhang Kirmani Ahmed Babak Damavandi | |||
 LYNX: Learning Dynamic Exits for Confidence-Controlled Reasoning Ömer Faruk Akgül Yusuf Hakan Kalaycı Rajgopal Kannan Willie Neiswanger Viktor Prasanna | |||
 K2-V2: A 360-Open, Reasoning-Enhanced LLM K2 Team Zhengzhong Liu Liping Tang Linghao Jin Haonan Li ...Hongyi Wang Xuezhe Ma Yuqi Wang Mikhail Yurochkin Eric P. Xing | |||
 Semantic Soft Bootstrapping: Long Context Reasoning in LLMs without Reinforcement Learning Purbesh Mitra Sennur Ulukus | |||
 Visual Reasoning Tracer: Object-Level Grounded Reasoning Benchmark Haobo Yuan Yueyi Sun Yanwei Li Tao Zhang Xueqing Deng Henghui Ding Lu Qi Anran Wang Xiangtai Li Ming-Hsuan Yang | |||
 SkillFactory: Self-Distillation For Learning Cognitive Behaviors Zayne Sprague Jack Lu Manya Wadhwa Sedrick Keh Mengye Ren Greg Durrett | |||
 Guided Self-Evolving LLMs with Minimal Human Supervision Wenhao Yu Zhenwen Liang Chengsong Huang Kishan Panaganti Tianqing Fang Haitao Mi Dong Yu | |||
 Plantain: Plan-Answer Interleaved Reasoning Anthony Liang Jonathan Berant Adam Fisch Abhimanyu Goyal Kalpesh Krishna Jacob Eisenstein | |||
 Think in Parallel, Answer as One: Logit Averaging for Open-Ended Reasoning Haonan Wang Chao Du Kenji Kawaguchi Tianyu Pang | |||
 See, Think, Learn: A Self-Taught Multimodal Reasoner Sourabh Sharma Sonam Gupta Sadbhawna | |||
 When Do Symbolic Solvers Enhance Reasoning in Large Language Models? Zhiyuan He Dingmin Wang | |||
Beyond SFT: Reinforcement Learning for Safer Large Reasoning Models with Better Reasoning Ability Jinghan Jia Nathalie Baracaldo Sijia Liu | |||
 Think Before You Prune: Self-Reflective Structured Pruning for Reasoning Language Models Ziyan Wang Enmao Diao Qi Le Pu Wang Guanchu Wang Minwoo Lee Shu-ping Yeh Li Yang | |||
CauSight: Learning to Supersense for Visual Causal Discovery Yize Zhang Meiqi Chen Sirui Chen Bo Peng Yanxi Zhang Tianyu Li Chaochao Lu | |||
SUPERChem: A Multimodal Reasoning Benchmark in Chemistry Zehua Zhao Zhixian Huang Junren Li Siyu Lin Junting Zhou ...Zuo Zhang Tong Yang Hao Ma Zhen Gao Jian Pei | |||
 Accelerating Large-Scale Reasoning Model Inference with Sparse Self-Speculative Decoding Yilong Zhao Jiaming Tang Kan Zhu Zihao Ye Chi-Chih Chang ...Mohamed S. Abdelfattah Mingyu Gao Baris Kasikci Song Han Ion Stoica | |||
 ORION: Teaching Language Models to Reason Efficiently in the Language of Thought Kumar Tanmay Kriti Aggarwal Paul Pu Liang Subhabrata Mukherjee | |||
Generating Verifiable CoT from Execution-Traces Shailja Thakur Vaibhav Saxena Rohan Kulkarni Shivdeep Singh Parameswaran Selvam Hima Patel Hiroshi Kanayama | |||
 AgriCoT: A Chain-of-Thought Benchmark for Evaluating Reasoning in Vision-Language Models for Agriculture Yibin Wen Qingmei Li Zi Ye Jiarui Zhang Jing Wu ...Yang Zhang Lingyuan Zhao Haohuan Fu Huang Jianxi Juepeng Zheng | |||
 Visual Puns from Idioms: An Iterative LLM-T2IM-MLLM Framework Kelaiti Xiao Liang Yang Dongyu Zhang Paerhati Tulajiang Hongfei Lin | |||
 DeepSeekMath-V2: Towards Self-Verifiable Mathematical Reasoning Zhihong Shao Yuxiang Luo Chengda Lu Z.Z. Ren Jiewen Hu Tian Ye Zhibin Gou Shirong Ma Xiaokang Zhang | |||
 RefineBench: Evaluating Refinement Capability of Language Models via Checklists Young-Jun Lee Seungone Kim Byung-Kwan Lee Minkyeong Moon Yechan Hwang Jong Myoung Kim Graham Neubig Sean Welleck Ho-Jin Choi | |||
Reinforcement Learning for Latent-Space Thinking in LLMs Enes Özeren Matthias Aßenmacher | |||
 Scaling Competence, Shrinking Reasoning: Cognitive Signatures in Language Model Learning Mukul Singh Ananya Singha Arjun Radhakrishna Sumit Gulwani | |||
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