Author

Nyx Iskandar

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#artificial intelligence May 2026

Eta Given Delta: Defining LLM Tool Efficiency With Marginal Tool Utility

This paper introduces tool efficiency, a new quantitative metric to evaluate the rate of useful tool calls in an LLM agent trajectory, and determines the sign of marginal tool utility for each tool call in a trajectory using LLM-as-a-Judge.

Nyx Iskandar, Perla Gamez · arXiv.org · 0 citations

Preprint Aug 2026

Projector Is All You Train

It is found that training only the projector is sufficient to achieve strong multimodal performance relative to existing baseline models and the authors' jointly trained MLLMs with the same encoder and backbone, and that joint training leads to undesirable drift in existing capabilities of the language model.

Nyx Iskandar, S. Selvan, Slater Victoroff · 0 citations