Author

Rahaf Aljundi

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Preprint Sep 2026

Dissecting Training-Free Uncertainty Estimation in Multimodal Large Language Models

It is found that answer length decides which family wins: token-level entropy on short answers, verbalized methods on sentence-length responses, and semantic methods on long-form generation, and a length-aware recipe that additionally flags responses on which the model abstains outperforms every individual method on av...

Soroush Seifi, Vaggelis Dorovatas, Lin Li et al. · 0 citations

#artificial intelligence Preprint Oct 2026

Optimal Hydra: Model Heterogeneous Federated Learning for LLMs using Data-Informed Hydra-Nets

Large language models (LLMs) trained on vast amounts of data have demonstrated impressive performance over a range of tasks, but future performance gains will require increasing amounts of data and compute. Federated Learning (FL) facilitates training on decentralized private data, but client resource limitations can m...

G. Legate, Rahaf Aljundi, Eugene Belilovsky · 0 citations

#machine learning Preprint Sep 2026

Dissecting Training-Free Uncertainty Estimation in Multimodal LLMs

This work presents a systematic study of training-free uncertainty quantification strategies for MLLMs, categorizing existing approaches into three conceptual families: token-level methods, which operate directly in the text output space; ver-balized methods, which elicit uncertainty estimates or abstention signals via...

Soroush Seifi, Vaggelis Dorovatas, Lin Li et al. · 0 citations

Preprint Jul 2026

DemoBridge: A Simulation-in-the-Loop Toolkit for Single-View Human Demonstration Retargeting

We present DemoBridge, an toolkit that turns a single-view RGB stereo recording of a human hand demonstration into an executable, physics-validated robot-arm trajectory. Retargeting across the embodiment gap is hard. A robot arm reaches a target with a long, articulated body whose links carry far more collision volume...

Zehao Wang, Fabien Despinoy, Sergey Zakharov et al. · 0 citations