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cover of episode Syntax Error-Free and Generalizable Tool Use for LLMs: Abstract and Intro

Syntax Error-Free and Generalizable Tool Use for LLMs: Abstract and Intro

2024/6/3
logo of podcast Machine Learning Tech Brief By HackerNoon

Machine Learning Tech Brief By HackerNoon

Shownotes Transcript

This story was originally published on HackerNoon at: https://hackernoon.com/syntax-error-free-and-generalizable-tool-use-for-llms-abstract-and-intro). Researchers propose TOOLDEC, a finite-state machine-guided decoding for LLMs, reducing errors and improving tool use. Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning). You can also check exclusive content about #llms), #tool-augmentation), #syntax-errors), #decoding-algorithm), #finite-state-machine), #tooldec), #tool-selection), #syntax-error-free), and more.

        This story was written by: [@textmodels](https://hackernoon.com/u/textmodels)). Learn more about this writer by checking [@textmodels's](https://hackernoon.com/about/textmodels)) about page,
        and for more stories, please visit [hackernoon.com](https://hackernoon.com)).
        
            
            
            Researchers propose TOOLDEC, a finite-state machine-guided decoding for LLMs, reducing errors and improving tool use.