Fine-tuning guide

Understanding Reinforcement Learning for Model Training, and future directions with GRAPE

Evolution Fine-Tuning: Using LLMs to Learn and Transfer Knowledge Across 371 Optimization Tasks

This paper introduces "Evolution Fine-Tuning" (EFT), a novel approach that uses Large Language Models (LLMs) integrated with evolutionary se

Supervised Fine-Tuning as Reinforcement Learning: Introducing Importance-Weighted SFT

The article explores the connection between supervised fine-tuning (SFT) of large language models and reinforcement learning (RL), arguing t

Study reveals why in-context learning fails on complex specification-heavy tasks and how fine-tuning can help

This research paper investigates the limitations of in-context learning (ICL) for large language models (LLMs) when applied to specification

Unsupervised Algorithm for Language Model Fine-Tuning Introduced

The article introduces an unsupervised algorithm, Internal Coherence Maximization (ICM), to fine-tune pretrained language models without ext

Specification gaming examples in AI - master list

Specification gaming examples in AI - master list