Bridging Foundational and Agentic Capabilities of LLMs
Large language models (LLMs) are increasingly deployed as agents, yet it remains unclear how their foundational capabilities translate into agentic capabilities.
ProofPaper ↗
Key points
- We bridge foundational and agentic capabilities through an operation-level measurement framework.
- We represent each model with a foundational profile derived from capability benchmarks and an operation profile derived from interaction trajectories, and define capability realization gaps as deviations of observed operation performance from predictions based on foundational capabilities.
- Experiments on fifteen model services in $τ^2$-Bench show that foundational profiles only partially predict agentic operations.
- We will release our code and analysis artifacts.
Sources (1)
- [1]Bridging Foundational and Agentic Capabilities of LLMsarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 21, 01:50 PM
Large language models (LLMs) are increasingly deployed as agents, yet it remains unclear how their foundational capabilities translate into agentic capabilities.
We bridge foundational and agentic capabilities through an operation-level measurement framework.
Extractive summary: sentences quoted from the sources.
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