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Syntax Error-Free and Generalizable Tool Use for LLMs: Abstract and Intro
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. Learn more about this writer by checking @textmodels's about page,
and for more stories, please visit hackernoon.com.
Researchers propose TOOLDEC, a finite-state machine-guided decoding for LLMs, reducing errors and improving tool use.
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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. Learn more about this writer by checking @textmodels's about page,
and for more stories, please visit hackernoon.com.
Researchers propose TOOLDEC, a finite-state machine-guided decoding for LLMs, reducing errors and improving tool use.