➗ Mathematics & statistics162 papers · page 3 of 7 · newest first · all shelvesMathematics, proofs, computational mathematics, word problems and how machines learn to solve them, statistics.← prev 1 2 3 4 5 6 7 next →Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model ParametersCharlie Snell, Jaehoon Lee, Kelvin Xu, et al.2024Scaling Synthetic Data Creation with 1,000,000,000 PersonasTao Ge, Xin Chan, Xiaoyang Wang, et al.2024Solving olympiad geometry without human demonstrationsTrieu H. Trinh, Yuhuai Wu, Quoc V. Le, et al.2024Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMsXin Lai, Zhuotao Tian, Yukang Chen, et al.2024The FineWeb Datasets: Decanting the Web for the Finest Text Data at ScaleGuilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al.2024TinyLlama: An Open-Source Small Language ModelPeiyuan Zhang, Guangtao Zeng, Tianduo Wang, et al.2024Training Language Models to Self-Correct via Reinforcement LearningAviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.2024Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingNathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024V-STaR: Training Verifiers for Self-Taught ReasonersArian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.2024Are Emergent Abilities of Large Language Models a Mirage?Rylan Schaeffer, Brando Miranda, Sanmi Koyejo2023Beyond Human Data: Scaling Self-Training for Problem-Solving with Language ModelsAvi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.2023C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation ModelsYuzhen Huang, Yuzhuo Bai, Zhihao Zhu, et al.2023Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve ThemMirac Suzgun, Nathan Scales, Nathanael Schärli, et al.2023CRITIC: Large Language Models Can Self-Correct with Tool-Interactive CritiquingZhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023Deductive Verification of Chain-of-Thought ReasoningZhan Ling, Yunhao Fang, Xuanlin Li, et al.2023Distilling Reasoning Capabilities into Smaller Language ModelsKumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan2023Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model SizesCheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.2023Faith and Fate: Limits of Transformers on CompositionalityNouha Dziri, Ximing Lu, Melanie Sclar, et al.2023Faithful Chain-of-Thought ReasoningQing Lyu, Shreya Havaldar, Adam Stein, et al.2023GPQA: A Graduate-Level Google-Proof Q&A BenchmarkDavid Rein, Betty Li Hou, Asa Cooper Stickland, et al.2023Large Language Models are Better Reasoners with Self-VerificationYixuan Weng, Minjun Zhu, Fei Xia, et al.2023Large Language Models Are Reasoning TeachersNamgyu Ho, Laura Schmid, Se-Young Yun2023Large Language Models Can Be Easily Distracted by Irrelevant ContextFreda Shi, Xinyun Chen, Kanishka Misra, et al.2023Large Language Models Cannot Self-Correct Reasoning YetJie Huang, Xinyun Chen, Swaroop Mishra, et al.2023LeanDojo: Theorem Proving with Retrieval-Augmented Language ModelsKaiyu Yang, Aidan M. Swope, Alex Gu, et al.2023← prev 1 2 3 4 5 6 7 next →