Yongkang Li

Yongkang Li

Deep Learning, Foundation Model, Biomedicine

[PaperReading] BioMANIA: a Pipeline for Bioinformatics

less than 1 minute read

Published:

Using LLM to properly choose and precisely use biomedical apis.

Brief Summary

This paper provide a pipeline for choosing and using biomedical functions/apis. The pipeline combines

  • a BERT-based API retriever. It will take a task instruction and return a short list of API candidates.
  • a GPT-4-based API predictor. It will (with in-context learning) choose the most relevant API.
  • a GPT-4-based generation pipeline of api calling that takes several steps to give the final script and show the result.

Limitation

The backend of API calling (and prediction) is completely gpt4-based, which leads to unavoidable hallucination and limits the performance this work can possibly attain.

One possible direction is to finetune the backend of the API calling.

Paper link:BioMANIA

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[PaperReading] ToolDec: Using Finite-State-Machine to Eliminate Hallucinations in LLM Decoding

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Using FSM to enhance tool-augmented LLM.

Key intuition and motivation:

the generation of api calls can be explicitly represented using states. By eliminating tokens outside the predefined states vocabulary, we can greatly reduce hallucinations. Core contribution: beyond a extensible method in augmented LLM, it provides a general method of incorporating domain-knowledge to eliminate hallucinations.