RESEARCH

Natural Langauge Processing

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Investigate natural langugage processing shcemes private LLM development using LLMs. Our aims are to explore the state-of-the-art natural language processing algorithms using LLMs for achieving effective long-term memory and private systems(LLM/RAG) and improving performance as in:

 

Fintetuned LLM for Private LLM/RAG

작성자 관리자 날짜 2024-06-10 14:20:02 조회수 139

1.Motivation

- Using thrid-party LLMs like ChatGPT gives the best performance on open domain tasks but gives rise to the risk of exposing sensitive client data
- Using an open LLM like LLaMA2 on a privately hosted server can solve this issue but results in lower performance
- Thus, there is a need to develop private LLMs with better performance on tasks requested by clients while maintaining privacy of client data

 

2. Research Goal and Issue

- Goal : Develop a private LLM/RAG(Retrieval-Augmented Generation) system

  • Develop finetuning methods using multitask leraning to improve the response generation ability of the private LLM
  • Improve the performance of the LLM by combining it with ISPL RAG model

- Issue 

  • MoE models encompass parameter complexity and training instability
  • Hypernetworks : pose scalability challenges 

 

3. Approach

- Develop a private LLM

  • Collect and process data for building training dataset
  • Finetune LLM using multitask learning
  • Integrate finetuned LLM with RAG

 

 

4.Result

- the performance evaluation of the fine-tuned model was much better than the pre-trained model

 

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