A new publication from Opto-Electronic Advances; DOI  10.29026/oea.2026.250193, discusses how electric-field-induced second-harmonic generation paves the way for next-generation nonlinear photonics.

In collaboration with international partners, researchers at the University of Stuttgart have experimentally demonstrated a previously unknown form of magnetism in atomically thin material layers. The discovery is highly relevant for future magnetic data storage technologies and advances the fundamental understanding of magnetic interactions in two-dimensional systems. The results have now been published in the renowned journal Nature Nanotechnology.

Paraphrase generation requires diverse generation of high-quality utterance by the given semantics, which is a challenge for traditional end-2-end text generation.

Inspired by the diffusion modeling for diverse image generations, a research team from Nanjing University led by Wei Zou managed to reconcile the quality and diversity for paraphrase generation via latent diffusion modeling (Latent Diffusion Paraphraser, LDP), and published their new research on 15 January 2026 in Frontiers of Computer Science co-published by Higher Education Press and Springer Nature.

Chain-of-Thought (CoT) prompting has enhanced the performance of Large Language Models (LLMs) across various reasoning tasks. However, CoT still falls short in dealing with complex math word problems, as it usually suffers from three pitfalls: semantic misunderstanding errors, calculation errors, and step-missing errors. Prior studies involve addressing the calculation errors and step-missing errors, but neglect the semantic misunderstanding errors, which is the major factor limiting the reasoning performance of LLMs.