給 AI 初學者的論文清單

這份清單來自我的指導教授易明洋（Prof. Mingyang Yi）所編寫的閱讀指南，旨在幫助電腦科學（CS）或數學系大二學生入門機器學習（ML）與強化學習（RL）。

基礎篇 (Foundations)

• Deep Residual Learning for Image Recognition

• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

• Layer Normalization

• Attention Is All You Need

AI 基礎設施 (AI Infrastructure)

• An Introduction to Variational Autoencoders

• Language Models are Unsupervised Multitask Learners

• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

• Transformers for Image Recognition at Scale

• Learning Transferable Visual Models From Natural Language Supervision

• LoRA: Low-Rank Adaptation of Large Language Models

• Let's Verify Step by Step

• Reflexion: Language Agents with Verbal Reinforcement Learning

• Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

推論加速 (Inference Acceleration)

• Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention

• Linformer: Self-Attention with Linear Complexity

• Fast Inference from Transformers via Speculative Decoding

• EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty

強化學習 (Reinforcement Learning)

• Training language models to follow instructions with human feedback

• Token-level Direct Preference Optimization

• A General Theoretical Paradigm to Understand Learning from Human Preferences

• Trust Region Policy Optimization

• Proximal Policy Optimization Algorithms

• High-Dimensional Continuous Control Using Generalized Advantage Estimation

• Asynchronous Methods for Deep Reinforcement Learning

• It Takes Two: Your GRPO Is Secretly DPO

• Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning