Tag: Supervised Learning
All the articles with the tag "Supervised Learning".
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RL in Name Only? Analyzing the Structural Assumptions in RL post-training for LLMs
本文通过理论和实验分析,揭示了当前RL(如GRPO)在LLM后训练中的MDP结构假设使其退化为过滤迭代监督微调,并指出响应长度增加源于奖励分配偏差,而非推理能力提升。
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Deep Learning for On-Street Parking Violation Prediction
This paper develops a Deep Learning model with a novel data smoothing technique to predict fine-grained on-street parking violation rates in Thessaloniki, Greece, using indirect features like weather and time, achieving improved accuracy (MAE of 0.146) over baseline methods.
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Large Language Models are Miscalibrated In-Context Learners
本文通过对大型语言模型在低资源场景下的校准问题进行深入分析,揭示上下文学习(ICL)未一致改善校准效果,并提出自集成方法显著提升校准性能(平均降低ECE 43%),同时维持或略提升任务性能。
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Nonparametric learning of covariate-based Markov jump processes using RKHS techniques
本文提出了一种基于再生核希尔伯特空间(RKHS)的非参数化方法,通过频率学和贝叶斯框架建模连续时间马尔可夫链(CTMC)中协变量驱动的非线性转移率,显著提升了个体化状态转移预测的准确性。
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Making Small Language Models Efficient Reasoners: Intervention, Supervision, Reinforcement
This paper introduces Temperature Scaling (TS) and Trace Length Control for Dynamic Reasoning (TLDR) to enhance token efficiency in small language models, achieving up to 50% reduction in response length with minimal accuracy loss across multiple reasoning benchmarks.