Tag: Reasoning
All the articles with the tag "Reasoning".
-
Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions
本文通过对92个开源语言模型的元分析,提出了一种超越缩放定律的性能预测框架,揭示了数据组成(如代码比例15-25%)和架构决策对下游任务性能的显著影响,预测精度相对提升3-28%。
-
Self-Tuning: Instructing LLMs to Effectively Acquire New Knowledge through Self-Teaching
本文提出SELF-TUNING框架,通过自教策略(SELF-TEACHING)显著提升大型语言模型从新文档中获取知识的能力,并在记忆、提取和推理任务上取得优异表现,同时保持较好的知识保留能力。
-
RL of Thoughts: Navigating LLM Reasoning with Inference-time Reinforcement Learning
本文提出RL-of-Thoughts (RLoT) 方法,通过强化学习训练轻量化导航模型,在推理时动态构建任务特定逻辑结构,显著提升大型语言模型在多领域推理任务中的表现,并展现出跨模型和任务的强迁移能力。
-
Is PRM Necessary? Problem-Solving RL Implicitly Induces PRM Capability in LLMs
本文通过系统性实验证明,纯强化学习(RL)训练不仅提升大型语言模型的复杂推理能力,还能隐式培养过程奖励模型(PRM)能力,提出Self-PRM框架以进一步改进性能,但也揭示了其在高难度问题上的低精度局限。
-
Talking Heads: Understanding Inter-layer Communication in Transformer Language Models
This paper investigates inter-layer communication in Transformer LMs by identifying low-rank communication channels via SVD, demonstrating their causal role in prompt sensitivity through interventions that significantly improve performance on context retrieval tasks like the Laundry List task.