Author

Adrian Bulat

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#machine learning Preprint Oct 2026

What Matters for Latent Reasoning with Flow Matching

Latent reasoning lets a large language model (LLM) think in a continuous space and verbalize only the answer. We argue that an effective latent thought must meet five requirements: it should be useful, helping produce the correct answer rather than merely changing it, diverse, so that resampling yields different reason...

Yassine Ouali, Adrian Bulat, G. Tzimiropoulos · 0 citations

Jul 2026

UltraViT: Latency-Optimized On-device Vision Encoder for Large Vision-Language Models

Extensive experiments demonstrate that the on-device latency-informed design combined with the tailored training strategy establishes a new state-of-the-art for efficient LVLM encoding, significantly outperforming existing encoder-centric baselines while operating on-device at nearly 1.7xthe speed.

Ioannis Maniadis Metaxas, Adrian Bulat, Alberto Baldrati et al. · arXiv.org · 0 citations