Emelitere kwa ụbọchị2400 ezi akụkọ
Akụkọ AI. Enweghị mkpọtụ.
Mkpuchi AI nyochara isi mmalite nke mmalite ngwaahịa, mgbanwe amụma, nyocha nchekwa, na mmegharị ụlọ ọrụ, nke otu agụmakwụkwọ na-anaghị akwụ ụgwọ kọwara n'asụsụ bekee dị larịị.
Isi mmalite enwetara
Akụkọ ọ bụla na-ejikọta na ihe akaebe siri ike dị: isi mmalite mgbe ọ dị, ma ọ bụghị nke akọwapụtara nke ọma.
Bekee dị larịị
Gịnị mere, ihe mere o ji dị mkpa, na ihe na-ekiri - na-enweghị jargon.
Enweghị ndochi
Mgbe mgbaàmà ahụ dị gịrịgịrị, anyị na-ebipụta ihe ọ bụla kama ịkwanye ndepụta.
Akụkọ ndị ọzọ
9 akụkọNchekwa
Ph.D. akwụkwọ edemede na-enyocha mbuso agha azụ n'asụsụ na ụdị asụsụ ọhụụ
Ph.D nke arXiv depụtara. ihe omumu ihe omumu ka mbuso agha n'azu nwere ike isi metụta ụdị asụsụ na ụdị asụsụ ọhụụ, gụnyere ụzọ maka nyocha, nchọpụta na imepụta ọgụ.arxiv.orgIhe ohuru ohuru
Preprint na-akọ ọkwa ọkwa ọkwa LLM dị elu maka ụlọ ọrụ ama ama
Mpempe akwụkwọ arXiv na-akọ na ụdị asụsụ anọ nwere ọkwa profaịlụ nke ọma karịa mgbe ejikọtara ya na ụlọ ọrụ na akwụkwọ akụkọ dị elu. Ndị ode akwụkwọ kwuru na atụmatụ ụlọ ọrụ na mpaghara nwere ike ịkpụzi nyocha, ebe ụdị anwalerela na ngalaba ọkachamara ka akọwapụtaghị ya na isi mmalite ewepụtara.arxiv.orgIhe ohuru ohuru
Ihe omumu choputara onodu nghota nwere ike igbanwe nchoputa LLM n'ihe ndapụta nke oke ọgwụ
Akwụkwọ arXiv na-akọ na atọ n'ime ụdị asụsụ anọ anwalela gbanwere ohere ikenye akụrụngwa n'ụzọ dị iche mgbe a tụlere otu ọnọdụ ahụike yana ma ọ bụ na-enweghị nzaghachi mbụ nke ihe nlereanya ahụ na gburugburu.arxiv.orgIhe ohuru ohuru
Preprint na-akọ na ngbanwe nke ahịrịokwu sitere n'ụbụrụ na-adịghị emebi emebi AI
Otu nchọcha na-akọwa Brain2Qwerty v2, ihe nlere nke na-eji ndekọ MEG n'ezie iji dekọọ ahịrị ahịrịokwu ekepụtara, na-ekwupụta ọnụego mperi okwu 39% n'ofe isiokwu itoolu.arxiv.orgIhe ohuru ohuru
Study maps 46 language models built for Portuguese
A systematic mapping study catalogs 46 Portuguese language models and compares architectures, training resources, licensing, code, data, and weights. The authors say the field is growing but difficult to assess because information is spread across papers, technical reports, repositories, and project documentation.arxiv.orgIhe ohuru ohuru
Interpretability study links Qwen3-4B’s overconfident answers to a certainty-biased mechanism
An arXiv study reports that Qwen3-4B favors certainty over uncertainty in controlled reasoning tasks and identifies model features that may drive the imbalance. The authors say targeted interventions reduced overconfident errors, but the abstract does not disclose effect sizes or testing details.arxiv.orgIhe ohuru ohuru
The Deontic Gap: Large Language Models and the Modal Language of Obligation
Modal auxiliaries such as must, should, and have to mark necessity and obligation within the contexts of speaker authority and interpersonal stance.arxiv.orgNchekwa
Paper proposes obscuring refusal signals to resist abliteration attacks
An arXiv preprint introduces a weight-editing method intended to make safety refusals harder to extract and remove. The paper reports stronger post-abliteration refusal scores on two open models, with different tradeoffs in general-purpose performance.arxiv.orgIhe ohuru ohuru
Paper reports a temporal method for detecting hallucinations at the token level
An arXiv preprint describes a hallucination detector that combines text statistics, entailment signals and language-model surprisal across sequences instead of judging tokens independently. Its BiGRU model reached an AUC of 0.840 on RAGTruth, according to the paper.arxiv.org
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