RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response

Junyu Luo, Xiao Luo, Kaize Ding, Jingyang Yuan, Zhiping Xiao, Ming Zhang·December 19, 2024

Summary

ROBUSTFT is a robust supervised fine-tuning framework for large language models (LLMs) designed to handle noisy data in practical applications. It employs a multi-expert collaborative system with inference-enhanced models for superior noise detection and a context-enhanced strategy for reliable annotation generation. An effective data selection mechanism based on response entropy ensures high-quality samples for fine-tuning. Extensive experiments on multiple LLMs across five datasets demonstrate ROBUSTFT's exceptional performance in noisy scenarios.

Key findings

5

Introduction
Background
Overview of large language models (LLMs)
Challenges in practical applications with noisy data
Objective
To present ROBUSTFT, a framework designed to enhance the robustness of LLMs in noisy data environments
Method
Multi-Expert Collaborative System
Description of the multi-expert model architecture
Inference-enhanced models for noise detection
Context-Enhanced Strategy
Explanation of the context-aware annotation generation process
Effective Data Selection Mechanism
Description of the response entropy-based data selection method
Importance of high-quality samples for fine-tuning
Implementation
Data Collection
Overview of data sources and collection methods
Data Preprocessing
Techniques for handling noisy data
Preparation steps for model training
Evaluation
Experimental Setup
Description of the experimental environment and datasets used
Performance Metrics
Metrics for evaluating ROBUSTFT's effectiveness
Results
Presentation of experimental results across multiple LLMs and datasets
Comparison with baseline models
Conclusion
Summary of ROBUSTFT's Contributions
Future Work
Potential areas for further research and development
Implications
Impact on the field of large language model fine-tuning
Basic info
papers
computation and language
artificial intelligence
Advanced features