Nvidia va acquérir Hugging Face pour 12,93 Md$
C’est désormais confirmé, Nvidia a annoncé la signature d’un accord définitif pour acquérir Hugging (...)
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C’est désormais confirmé, Nvidia a annoncé la signature d’un accord définitif pour acquérir Hugging (...)
Lire l'articlearXiv:2609.04391v1 Announce Type: new Abstract: In this work, a novel evaluation scheme built on a generalized variant of the Rand Index measure, namely, the H\"ullermeier-Rifqi Index, is proposed in order to assess how well phonetic encoding algorithms conform to word-based transcriptions in IPA (International Phonetic Alphabet) notation. For this objective, the discordance…
Lire l'articlearXiv:2609.04384v1 Announce Type: new Abstract: Chinese online comments often convey social meaning through indirect and playful language that is hard to interpret without context. Existing evaluations largely organize items around predefined phenomena or controlled pragmatic categories, leaving open whether models can distinguish plausible readings of what a naturally…
Lire l'articlearXiv:2609.04366v1 Announce Type: new Abstract: Early-onset colorectal cancer is increasing among younger adults, yet red-flag symptoms in this age group have no evidence-based guidelines for follow-up testing, and structured encounter data do not capture the detail needed to support early detection and inform follow-up, including symptom duration, context, and fam- ily…
Lire l'articlearXiv:2609.04350v1 Announce Type: new Abstract: How do people learn to become better conversationalists? This question is especially important in the context of mental-health counseling, where conversational skills are essential, yet volunteer counselors often have limited access to supervision and structured feedback. Understanding how counselors develop their ability to…
Lire l'articlearXiv:2609.04336v1 Announce Type: new Abstract: Medical visual question answering (Med-VQA) is often assumed to require medical fine-tuning, large models, or complex multi-agent pipelines. We revisit this assumption with \textbf{MedProb}, a lightweight probing framework that predicts multiple-choice Med-VQA answers from frozen VLM representations without free-text generation.…
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