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Etching-free dual-lift-off for direct patterning of epitaxial oxide thin films
Jiayi Qin, Josephine Si Yu See, Yanran Liu, Xueyan Wang, Wenhai Zhao, Yang He, Jianbo Ding, Yilin Wu, Shanhu Wang, Huiping Han, Afzal Khan, Shuya Liu, Sheng'an Yang, Hui Zhang, Jiangnan Li, Qingming Chen, Jiyang Xie, Ji Ma, Wanbiao Hu, Jianhong Yi, Liang Wu, X. Renshaw Wang
https…

Etching-free dual-lift-off for direct patterning of epitaxial oxide thin films
Although monocrystalline oxide films offer broad functional capabilities, their practical use is hampered by challenges in patterning. Traditional patterning relies on etching, which can be costly and prone to issues like film or substrate damage, under-etching, over-etching, and lateral etching. In this study, we introduce a dual-lift-off method for direct patterning of oxide films, circumventing the etching process and associated issues. Our method involves an initial lift-off of amorphous Sr…

Generalizable Audio Deepfake Detection via Hierarchical Structure Learning and Feature Whitening in Poincar\'e sphere
Mingru Yang, Yanmei Gu, Qianhua He, Yanxiong Li, Peirong Zhang, Yongqiang Chen, Zhiming Wang, Huijia Zhu, Jian Liu, Weiqiang Wang
https://arxiv.org/abs/2508.01897

Generalizable Audio Deepfake Detection via Hierarchical Structure Learning and Feature Whitening in Poincaré sphere
Audio deepfake detection (ADD) faces critical generalization challenges due to diverse real-world spoofing attacks and domain variations. However, existing methods primarily rely on Euclidean distances, failing to adequately capture the intrinsic hierarchical structures associated with attack categories and domain factors. To address these issues, we design a novel framework Poin-HierNet to construct domain-invariant hierarchical representations in the Poincaré sphere. Poin-HierNet includes th…

UniAPL: A Unified Adversarial Preference Learning Framework for Instruct-Following
FaQiang Qian, WeiKun Zhang, Ziliang Wang, Kang An, Xuhui Zheng, Liangjian Wen, Mengya Gao, Yong Dai, Yichao Wu
https://arxiv.org/abs/2509.25148

UniAPL: A Unified Adversarial Preference Learning Framework for Instruct-Following
Shaping powerful LLMs to be beneficial and safe is central to AI alignment. We argue that post-training alignment is fundamentally a unified Preference Learning problem, involving two modalities: demonstrated preferences (e.g., Supervised Fine-Tuning, SFT) and comparative preferences (e.g., Reinforcement Learning, RL).The standard sequential pipeline-SFT followed by RL-is flawed due to a critical distributional mismatch: SFT uses static expert data, but as the policy evolves, its generation dis…

Sliced Space-filling Design with Mixtures
Zikang Xiong, Hong Qin, Yuning Huang, Jianhui Ning
https://arxiv.org/abs/2509.21827 https://arxiv.org/pdf/2509.21…

Sliced Space-filling Design with Mixtures
In this paper, we proposes the construction methods of sliced space-filling design when the quantitative factors are mixture components. Leveraging the representative points framework for distribution and energy distance decomposition theory, this paper proposes three methods for constructing sliced representative points and establishes their distributional convergence. Furthermore, one-shot and sequential algorithms for generating sliced space-filling mixture design for experiments with proces…

HC Dan Quinn | 'Be aggressive and bold and take our chances' https://www.commanders.com/video/hc-dan-quinn-be-aggressive-and-bold-and-take-our-chances

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[3/3]:
- Incentivizing Reasoning for Advanced Instruction-Following of Large Language Models
Yulei Qin, Gang Li, Zongyi Li, Zihan Xu, Yuchen Shi, Zhekai Lin, Xiao Cui, Ke Li, Xing Sun

Signless Laplacian characterization of cones over disjoint unions of cycles, edges and isolated vertices
Jiachang Ye, Jianguo Qian, Zoran Stanic
https://arxiv.org/abs/2509.25925

Signless Laplacian characterization of cones over disjoint unions of cycles, edges and isolated vertices
Two graphs are said to be $Q$-cospectral if they share the same signless Laplacian spectrum. A simple graph is said to be determined by its signless Laplacian spectrum (abbreviated as DQS) if there exists no other non-isomorphic simple graph with the same signless Laplacian spectrum. In this paper, we establish the following results: (1) Let$G \cong K_{1} \vee \bigl(C_{k} \cup qK_{2} \cup sK_{1}\bigr),$ with $q,s \geq 1$, $k \geq 4$, and at least $21$ vertices. If $k$ is odd, then $G$ is DQS.…

Ultrafast giant enhancement of second harmonic generation in a strongly correlated cobaltite YbBaCo4O7
Yuchen Cui, Qiaomei Liu, Qiong Wu, Shuxiang Xu, Junhan Huang, Hao Wang, Rongsheng Li, Shanshan Han, Wei Xu, Li Du, Ming Lu, Chunmei Zhang, Shangfei Wu, Xinbo Wang, Tao Dong, Li Yue, Dong Wu, Nanlin Wang
https://arxiv.org/abs/2510.01826

Ultrafast giant enhancement of second harmonic generation in a strongly correlated cobaltite YbBaCo4O7
We report the observation of ultrafast photoinduced giant enhancement of optical second harmonic generation (SHG) efficiency in cobaltite YbBaCo4O7. Upon femtosecond pumping at energies above the band gap, the system exhibits an ultrafast enhancement in SHG intensity, reaching up to 60% higher than the initial value, then decays into a metastable state maintaining the enhancement. The enhancement scales linearly with pump fluence but shows no dependence on pump polarization. A pure electronic p…

Hybrid Particle Swarm Optimization for Fast and Reliable Parameter Extraction in Thermoreflectance
Bingjia Xiao, Tao Chen, Wenbin Zhang, Xin Qian, Puqing Jiang
https://arxiv.org/abs/2507.22960

Hybrid Particle Swarm Optimization for Fast and Reliable Parameter Extraction in Thermoreflectance
Frequency-domain thermoreflectance (FDTR) is a widely used technique for characterizing thermal properties of multilayer thin films. However, extracting multiple parameters from FDTR measurements presents a nonlinear inverse problem due to its high dimensionality and multimodal, non-convex solution space. This study evaluates four popular global optimization algorithms: Genetic Algorithm (GA), Quantum Genetic Algorithm (QGA), Particle Swarm Optimization (PSO), and Fireworks Algorithm (FWA), for…

Strain-Gradient-Driven Decoupling of Thermal Suppression from Anisotropy in \b{eta}-Ga2O3
Guangwu Zhang, Xing Xiang, Ziyan Qian, Yixin Xu, Shengying Yue, Hyejin Jang, Lin Yang, Yanguang Zhou, Xinyu Wang, Qiye Zheng
https://arxiv.org/abs/2509.26412

Strain-Gradient-Driven Decoupling of Thermal Suppression from Anisotropy in \b{eta}-Ga2O3
Strain gradients, ubiquitous in flexible devices and epitaxial nanostructures, are a major blind spot for thermal transport in \b{eta}-Ga2O3. We establish that strain gradient unlocks a thermal conductivity (k) suppression mechanism fundamentally more potent than uniform strain: moderate uniaxial gradients (0.6%/nm) suppress k by 32-37% (27-30%) in thin films (nanowires), intensifying to 43.3% with biaxial gradients. This reduction far exceeds that from equivalent uniform strain and surpasses b…