Abstract MicroRNAs (miRNAs) are key post-transcriptional regulators in gene regulatory networks (GRNs). Comprehensive research on miRNAs increasingly requires the integration of large and heterogeneous datasets, together with more efficient approaches to knowledge exploration. Here, we present PmiREN3.0, a major update...
In the current era of rapid digital transformation and the increasing integration of artificial intelligence (AI) into education, pre-service teachers are required not only to use information and communication technologies but also to apply AI in educational activities ethically, responsibly, and safely. This study aim...
Boundary Genesis Omega v43 presents an executable research-governance architecture for distinguishing mathematical closure, evidentiary sufficiency, scientific uncertainty, and terminal material closure within a recoverability-constrained research system. The edition introduces a Universal Null–Void Ceiling that preven...
Noelia Sanchez· Zenodo (CERN European Organi...· 0 citations
Abstract Generative artificial intelligence (AI) can produce highly realistic dermatological images, raising concerns about clinicians’ ability to distinguish authentic pathology from synthetic representations. To assess whether dermatological expertise influences the detection of AI-generated vitiligo images, and to e...
Jonathan Shapiro, Itay Cohen, Mor Atlas et al.· Visual Computing for Industr...· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
The rapid development of Artificial Intelligence (AI) has created new opportunities and challenges for Islamic Religious Education (IRE), particularly in adapting curriculum structures to technological advancement while maintaining religious and national values. This study aims to analyze the transformation of the IRE...
Koko Adya Winata, Edy Sofyan, Djenal Suhara et al.· Bulletin of Pedagogical Rese...· 0 citations
On-Policy Distillation (OPD) has emerged as a dominant post-training paradigm for Large Language Models, especially in reasoning domains. However, OPD remains unstable in practice due to the high gradient variance of its single-sample Monte Carlo estimator, and recipes for stable training are still immature. We propose...
Minjae Oh, Sangjun Song, Gyubin Choi et al.· 0 citations
Integrated Policy Gradient is introduced, a novel, training-free framework that brings policy-based attribution into mechanistic interpretability for LLM reasoning and enables modulation of reasoning capabilities, offering a powerful and reliable framework for understanding LLM reasoning.
Chang-Ming Li, Kai-Xin Zhang, Haoyun Xu et al.· 4 citations
As backdoor attacks become more stealthy and robust, they reveal critical weaknesses in current defense strategies: detection methods often rely on coarse-grained feature statistics, and purification methods typically require full retraining or additional clean models. To address these challenges, we propose DUP (Detec...
Man Hu, Yahui Ding, Yatao Yang et al.· 0 citations
Toxicity remains a leading cause of early-stage drug development failure. Despite advances in molecular design and property prediction, the task of molecular toxicity repair, generating structurally valid molecular alternatives with reduced toxicity, has not yet been systematically defined or benchmarked. To fill this...
Fei Lin, Ziyang Gong, Cong Wang et al.· 0 citations
Advances in large language models (LLMs) have created opportunities for cross-lingual transfer of medical knowledge from high-resource to low-resource languages to support access to healthcare information. However, medical question-answering (QA) datasets for fine-tuning and evaluating LLMs remain scarce for Tetun. To...
In this paper we introduce token time continuous diffusion (TTCD), a new diffusion language model which (a) operates in continuous space, deterministically mapping Gaussian noise to a final token canvas with no further sampling, and crucially (b) incorporates a new notion of per-token times, with some tokens proceeding...
User modeling aims to use language models (LMs) to mimic an individual's behavior from a corpus of past context-action pairs (e.g., conversation turns), enabling the simulation of users in settings like behavioral science, human-AI collaboration, and market research. Recent approaches augment these corpora with synthes...
Alan Zhu, Mihran Miroyan, Carolyn Wang et al.· 0 citations