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9 故事创新
Study proposes transfer-aware curriculum sampling for language-model training
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.arxiv.org创新
Co-RL paper reports label-free reasoning gains from diverse model cohorts
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.arxiv.org创新
A proposed fine-tuning method allocates training effort across related tasks
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.arxiv.org创新
SURE-Ridge proposes a faster way to infer causal graphs from limited data
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.arxiv.org创新
J-Miner paper reports executable decision rules extracted from language-model classifiers
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.arxiv.org创新
Paper tests letting AI agents switch specialized LoRA adapters mid-task
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.arxiv.org创新
MultiSigBERT combines medical text and patient timelines for cancer survival prediction
An ECML PKDD 2026 paper presents MultiSigBERT, combining narrative medical reports, structured records and temporal patient data to estimate individualized oncology risk scores. It reports a 0.743 concordance index on an independent test set; the source has no comparator results or clinical-deployment evidence.arxiv.org创新
DOW-KE proposes direct optimization for editing knowledge across AI model layers
An arXiv paper proposes optimizing multi-layer model edits through the complete forward pass, reporting the strongest combined results among tested methods in five of six model-dataset settings.arxiv.org安全
Study Finds Public EEG Encoders Can Transfer Adversarial Attacks to Private Models
An arXiv paper reports that adversarial examples generated through publicly released EEG encoders can affect inaccessible downstream models without queries to their parameters, outputs, or gradients.arxiv.org