Author

Martin Gubri

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#small language model Preprint Oct 2026

Agent in a Bottle: Can LLM Agents Turn Their Capabilities Into Cheap, Scalable Artifacts?

This work introduces BOTTLED, a benchmark in which agents receive an entire unlabelled workload and must complete it under fixed time, compute and LLM API budgets, and finds that strong zero-shot task performance does not reliably translate into strong bottling capabilities.

Ankit Sonthalia, Haritz Puerto, Alexander Rubinstein et al. · 0 citations

#artificial intelligence Preprint Oct 2025

Is Multilingual LLM Watermarking Truly Multilingual? Scaling Robustness to 100+ Languages via Back-Translation

STEAM, a detection method that uses Bayesian optimisation to search among 126 candidate languages for the back-translation that best recovers the watermark strength, is introduced, compatible with any watermarking method, robust across different tokenizers and languages, non-invasive, and easily extendable to new langu...

Asim Mohamed, Martin Gubri · 1 citation