Error Handling And Tool Execution Recovery

via “error handling and recovery in multi-tool execution”

Framework for training LLM agents on 16K+ real APIs.

Unique: Learns error recovery patterns from DFSDT-annotated training data, enabling models to generate recovery steps when APIs fail rather than terminating, and integrates recovery into the inference loop.

vs others: Learned error recovery outperforms fixed retry strategies (exponential backoff) by adapting to specific failure modes and generating context-aware recovery steps.