T1: A Tool-Oriented Conversational Dataset for Multi-Turn Agentic Planning

Understand

Large Language Models (LLMs) have demonstrated impressive capabilities as intelligent agents capable of solving complex problems.

• However, effective planning in scenarios involving dependencies between API or tool calls-particularly in multi-turn conversations-remains a significant challenge.
• To address this, we introduce T1, a tool-augmented, multi-domain, multi-turn conversational dataset specifically designed to capture and manage inter-tool dependencies across diverse domains.
• T1 enables rigorous evaluation of agents' ability to coordinate tool use across nine distinct domains (4 single domain and 5 multi-domain) with the help of an integrated caching mechanism for both short- and long-term memory, while supporting dynamic replanning-such as deciding whether to recompute or reuse cached results.