Sitemap - 2023 - Ahead of AI

Ten Noteworthy AI Research Papers of 2023

Tackling Hallucinations, Boosting Reasoning Abilities, and New Insights into the Transformer Architecture

Practical Tips for Finetuning LLMs Using LoRA (Low-Rank Adaptation)

A Potential Successor to RLHF for Efficient LLM Alignment and the Resurgence of CNNs

AI and Open Source in 2023

LLM Business and Busyness: Recent Company Investments and AI Adoption, New Small Openly Available LLMs, and LoRA Research

From Self-Alignment to LongLoRA

LLM Training: RLHF and Its Alternatives

The Missing Bits: Llama 2 Weights Have Changed

New Foundation Models: CodeLlama and other highlights in Open-Source AI

Llama 2, Flash-Attention 2, and More

Large Language Models and Nearest Neighbors

Long Contexts and Scaling Transformers to 1,000,000,000 Tokens

State of Computer Vision 2023: From Vision Transformers to Neural Radiance Fields

Accelerating PyTorch Model Training

Understanding Encoder And Decoder LLMs

Direct-Preference Optimization for Human Feedback and More

LLM Tuning & Dataset Perspectives

About LayerNorm Variants in the Original Transformer Paper, and Some Other Interesting Historical Tidbits About LLMs

Finetuning LLMs Efficiently with Adapters

Transformers for Long Inputs and Less Training Data

Insights from Large-Scale LLM Training Runs

Understanding Parameter-Efficient LLM Finetuning: Prompt Tuning And Prefix Tuning

Finetuning Large Language Models

Understanding Large Language Models

Large Language Models 3.0

TrAIn Differently: Do We Need Reinforcement Learning with Human Feedback (RLHF)?

RevAIval of Ideas: From Next-Generation Convolutional Neural Networks to LLMs

Looking Back at 2022: A Big Year For AI