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View All on GitHubReplace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.
Replace an LLM agent's closed-set decisions with a cheap classifier trained from its own logs. Code for the paper TabAgent: Distilling LLM Agent Components into Cheap Classifiers.