论文标题：Propagation Tree Is Not Deep: Adaptive Graph Contrastive Learning A...

一、概述 大语言模型（LLMs）在预训练的过程中通常会捕捉数据的特征，而这些训练数据通常既包含高质量的也包含低质量的，因此模型有时会产生不被期望...

论文标题：LoRA: Low-Rank Adaptation of Large Language Models论文链接：https://arxi...

论文标题：Megatron-LM: Training Multi-Billion Parameter Language Models Using...

论文标题：Tree of Thoughts: Deliberate Problem Solving with Large Language Mo...

论文标题：LIMA: Less Is More for Alignment论文链接：https://arxiv.org/abs/2305.112...

论文标题：Self-Consistency Improves Chain of Thought Reasoning in Language Mo...

论文标题：GPipe: Easy Scaling with Micro-Batch Pipeline Parallelism论文链接：https...