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An arXiv paper introduces Relative Transfer, a measure of how training examples at different difficulty levels affect one another, and proposes Transfer-aware Dynamic Curriculum Sampling for adapting training schedules during post-training.
An arXiv preprint describes Co-RL, a multi-agent reinforcement-learning framework in which separate models reward one another. The authors report gains across text-only and multimodal benchmarks without ground-truth labels, while acknowledging the risks of self-reinforcing errors and training collapse.
A new arXiv paper proposes Task Specialization Fine-Tuning to allocate limited fine-tuning across related task regions. It reports improved task coverage in optimization, control, and LLM experiments, but gives no numerical results or independent validation.
Accepted to the 2026 Asilomar Conference, a paper proposes SURE-Ridge, a closed-form method for causal-graph estimation in equal-variance linear Gaussian models. Authors report lower small-sample structural error and fastest tested-baseline runtime; the source does not establish performance beyond these assumptions.
Researchers describe J-Miner, a method that converts internal signals from fine-tuned language-model classifiers into inspectable rules, reporting up to 98.3% reproduction of source decisions and nearly the same average task accuracy in much smaller student models.
A single-author arXiv paper reports that giving an agent a tool to switch between specialized LoRA adapters helped it solve two synthetic coding tasks and reduced the reported capability tax by up to 18 times.
Takardar ECML PKDD 2026 tana gabatar da MultiSigBERT, haɗa rahotannin likita na ba da labari, bayanan da aka tsara da kuma bayanan haƙuri na ɗan lokaci don ƙididdige ƙimakin haɗarin cutar kansa. Yana bayar da rahoton 0.743 concordance index akan saitin gwaji mai zaman kansa; tushen ba shi da sakamakon kwatance ko shaidar tura asibiti.
Takardar arXiv ta ba da shawarar inganta ƙirar ƙira mai nau'i-nau'i da yawa ta hanyar cikakkiyar wucewar gaba, tana ba da rahoton sakamako mafi ƙarfi tsakanin hanyoyin da aka gwada a cikin saitunan saitin ƙira guda shida.
Takardar arXiv ta ba da rahoton cewa misalan ƙiyayya da aka haifar ta hanyar masu ba da izini na EEG da aka saki a bainar jama'a na iya shafar ƙirar da ba za ta iya isa ba ba tare da tambayar sigoginsu, abubuwan da aka fitar ko gradients ba.
Takardar arXiv ta gabatar da Mr.Dec, samfurin da ke haɗa sabuntawar rikodin lafiya na lantarki na yau da kullun tare da binciken X-ray na ƙirji a cikin tsari na zamani. Mawallafa sun ba da rahoton sakamako na zamani akan bayanan MIMIC guda biyu, amma rikodin da aka kawo ba ya ba da maki ko shaida na tura asibiti.
Wani sabon ma'auni yana ba da hujjar cewa masu rarraba daftarin aiki na iya bayyana daidai fiye da yadda suke lokacin da ragowar tambarin ya shiga cikin rubutu. A kan tsaftataccen takaddar sa na 16,000, BERT ya kai daidaito 89.14%, yayin da koma bayan dabaru ya ba da madadin mai rahusa.
Takardar arXiv tana gabatar da Data-DPO, wanda ke zaɓar misalan daidaitawa masu kyau ta amfani da martanin ƙirar ƙira yayin taƙaitaccen binciken horo. Marubuta suna ba da rahoton ingantattun sakamako fiye da hanyoyin zaɓin da ake da su da kuma cikakken horo na bayanai akan Vision-Flan da LLaVA-CoT, amma rikodin ba shi da girman tasiri ko ingantaccen inganci.
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