[NAACL 2025] The official implementation of paper "Learning From Failure: Integrating Negative Examples when Fine-tuning Large Language Models as Agents"
What is the Reason-Wang/NAT GitHub project? Description: "[NAACL 2025] The official implementation of paper "Learning From Failure: Integrating Negative Examples when Fine-tuning Large Language Models as Agents"". Written in Python. Explain what it does, its main use cases, key features, and who would benefit from using it.
Question is copied to clipboard — paste it after the AI opens.
Clone via HTTPS
Clone via SSH
Download ZIP
Download master.zipReport bugs or request features on the NAT issue tracker:
Open GitHub Issues