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View article: Terahertz oscillation of $180^{\circ}$ domain walls in ferroelectric membranes
Terahertz oscillation of $180^{\circ}$ domain walls in ferroelectric membranes Open
A fundamentally intriguing yet not well understood topic in the field of ferroelectrics is the collective excitation of domain walls (DWs), with potential applications to DW-based nanoelectronic and optoelectronic devices. Here we use dyna…
View article: Terahertz oscillation of $180^{\circ}$ domain walls in ferroelectric membranes
Terahertz oscillation of $180^{\circ}$ domain walls in ferroelectric membranes Open
A fundamentally intriguing yet not well understood topic in the field of ferroelectrics is the collective excitation of domain walls (DWs), with potential applications to DW-based nanoelectronic and optoelectronic devices. Here we use dyna…
View article: A Hybrid Physics-Driven Neural Network Force Field for Liquid Electrolytes
A Hybrid Physics-Driven Neural Network Force Field for Liquid Electrolytes Open
Electrolyte design plays an important role in the development of lithium-ion batteries and sodium-ion batteries. Battery electrolytes feature a large design space composed of different solvents, additives, and salts, which is difficult to …
View article: A Hybrid Physics-Driven Neural Network Force Field for Liquid Electrolytes
A Hybrid Physics-Driven Neural Network Force Field for Liquid Electrolytes Open
Electrolyte design plays an important role in the development of lithium-ion batteries and sodium-ion batteries. Battery electrolytes feature a large design space composed of different solvents, additives, and salts, which is difficult to …
View article: A Hybrid Physics-Driven Neural Network Force Field for Liquid Electrolytes
A Hybrid Physics-Driven Neural Network Force Field for Liquid Electrolytes Open
Electrolyte design plays an important role in the development of lithium-ion batteries and sodium-ion batteries. Battery electrolytes feature a large design space composed of different solvents, additives, and salts, which is difficult to …
View article: Fast boundary integral method for acoustic wave scattering in two-dimensional layered media
Fast boundary integral method for acoustic wave scattering in two-dimensional layered media Open
In this paper, we present a fast boundary integral method accelerated by the fast multipole method (FMM) for acoustic wave scattering governed by the scalar Helmholtz equation in multi-layered two-dimensional media. Multiple scatterers are…
View article: Fast boundary integral method for acoustic wave scattering in two-dimensional layered media
Fast boundary integral method for acoustic wave scattering in two-dimensional layered media Open
In this paper, we present a fast boundary integral method accelerated by the fast multipole method (FMM) for acoustic wave scattering governed by the scalar Helmholtz equation in multi-layered two-dimensional media. Multiple scatterers are…
View article: Fast boundary integral method for acoustic wave scattering in two-dimensional layered media
Fast boundary integral method for acoustic wave scattering in two-dimensional layered media Open
In this paper, we present a fast boundary integral method accelerated by the fast multipole method (FMM) for acoustic wave scattering governed by the scalar Helmholtz equation in multi-layered two-dimensional media. Multiple scatterers are…
View article: Design, synthesis, and evaluation of 1, 3-dioxo- <i>N-</i> phenylisoindoline-5-carboxamide derivatives as potent reversible inhibitors of human monoamine oxidase B with neuroprotective properties
Design, synthesis, and evaluation of 1, 3-dioxo- <i>N-</i> phenylisoindoline-5-carboxamide derivatives as potent reversible inhibitors of human monoamine oxidase B with neuroprotective properties Open
A series of 1, 3-dioxo-N-phenylisoindoline-5-carboxamide derivatives were designed, synthesised and evaluated as potent human monoamine oxidase B (hMAO-B) inhibitors with neuroprotective properties. The structure-activity rel…
View article: CCDC 2451884: Experimental Crystal Structure Determination
CCDC 2451884: Experimental Crystal Structure Determination Open
An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available …
View article: FHA-MTT_data
FHA-MTT_data Open
The dataset was generated during the development of the FHA-MTT algorithm, which aims to enable automated health assessment of fish based on swimming behavior. It includes video recordings of crucian carp (Carassius auratus) exhibiting bot…
View article: FHA-MTT_data
FHA-MTT_data Open
The dataset was generated during the development of the FHA-MTT algorithm, which aims to enable automated health assessment of fish based on swimming behavior. It includes video recordings of crucian carp (Carassiu…
View article: On the Formation and Evolution of Two Meso‐β‐Scale Vortices That Act as Crucial Conditions for a Heavy Snow Event Over the Losses Plateau
On the Formation and Evolution of Two Meso‐β‐Scale Vortices That Act as Crucial Conditions for a Heavy Snow Event Over the Losses Plateau Open
This study examines the formation, evolution, and merger mechanisms of two meso‐β‐scale vortices (V1 and V2) into a meso‐α‐scale vortex (V3) that triggered a heavy snowfall event over China's Loess Plateau on December 10–11, 2023. The merg…
View article: Synergizing Multimodal Temporal Knowledge Graphs and Large Language Models for Social Relation Recognition
Synergizing Multimodal Temporal Knowledge Graphs and Large Language Models for Social Relation Recognition Open
Recent years have witnessed remarkable advances in Large Language Models (LLMs). However, in the task of social relation recognition, Large Language Models (LLMs) encounter significant challenges due to their reliance on sequential trainin…
View article: R3-RAG: Learning Step-by-Step Reasoning and Retrieval for LLMs via Reinforcement Learning
R3-RAG: Learning Step-by-Step Reasoning and Retrieval for LLMs via Reinforcement Learning Open
Retrieval-Augmented Generation (RAG) integrates external knowledge with Large Language Models (LLMs) to enhance factual correctness and mitigate hallucination. However, dense retrievers often become the bottleneck of RAG systems due to the…
View article: DecoupleSearch: Decouple Planning and Search via Hierarchical Reward Modeling
DecoupleSearch: Decouple Planning and Search via Hierarchical Reward Modeling Open
Retrieval-Augmented Generation (RAG) systems have emerged as a pivotal methodology for enhancing Large Language Models (LLMs) through the dynamic integration of external knowledge. To further improve RAG's flexibility, Agentic RAG introduc…
View article: Dynamic Expert Specialization: Towards Catastrophic Forgetting-Free Multi-Domain MoE Adaptation
Dynamic Expert Specialization: Towards Catastrophic Forgetting-Free Multi-Domain MoE Adaptation Open
Mixture-of-Experts (MoE) models offer immense capacity via sparsely gated expert subnetworks, yet adapting them to multiple domains without catastrophic forgetting remains an open challenge. Existing approaches either incur prohibitive com…
View article: Adversarial Agent Collaboration for C to Rust Translation
Adversarial Agent Collaboration for C to Rust Translation Open
Translating C to memory-safe languages, like Rust, prevents critical memory safety vulnerabilities that are prevalent in legacy C software. Existing approaches for C to safe Rust translation, including LLM-assisted ones, do not generalize …
View article: LongCat-Flash Technical Report
LongCat-Flash Technical Report Open
We introduce LongCat-Flash, a 560-billion-parameter Mixture-of-Experts (MoE) language model designed for both computational efficiency and advanced agentic capabilities. Stemming from the need for scalable efficiency, LongCat-Flash adopts …
View article: ASM-UNet: Adaptive Scan Mamba Integrating Group Commonalities and Individual Variations for Fine-Grained Segmentation
ASM-UNet: Adaptive Scan Mamba Integrating Group Commonalities and Individual Variations for Fine-Grained Segmentation Open
Precise lesion resection depends on accurately identifying fine-grained anatomical structures. While many coarse-grained segmentation (CGS) methods have been successful in large-scale segmentation (e.g., organs), they fall short in clinica…
View article: Multi-Treatment-DML: Causal Estimation for Multi-Dimensional Continuous Treatments with Monotonicity Constraints in Personal Loan Risk Optimization
Multi-Treatment-DML: Causal Estimation for Multi-Dimensional Continuous Treatments with Monotonicity Constraints in Personal Loan Risk Optimization Open
Optimizing credit limits, interest rates, and loan terms is crucial for managing borrower risk and lifetime value (LTV) in personal loan platform. However, counterfactual estimation of these continuous, multi-dimensional treatments faces s…
View article: xDeepServe: Model-as-a-Service on Huawei CloudMatrix384
xDeepServe: Model-as-a-Service on Huawei CloudMatrix384 Open
The rise of scaled-out LLMs and scaled-up SuperPods signals a new era in large-scale AI infrastructure. LLMs continue to scale out via MoE, as seen in recent models like DeepSeek, Kimi, and Qwen. In parallel, AI hardware is scaling up, wit…
View article: Coflex: Enhancing HW-NAS with Sparse Gaussian Processes for Efficient and Scalable DNN Accelerator Design
Coflex: Enhancing HW-NAS with Sparse Gaussian Processes for Efficient and Scalable DNN Accelerator Design Open
Hardware-Aware Neural Architecture Search (HW-NAS) is an efficient approach to automatically co-optimizing neural network performance and hardware energy efficiency, making it particularly useful for the development of Deep Neural Network …
View article: MindSpeed RL: Distributed Dataflow for Scalable and Efficient RL Training on Ascend NPU Cluster
MindSpeed RL: Distributed Dataflow for Scalable and Efficient RL Training on Ascend NPU Cluster Open
Reinforcement learning (RL) is a paradigm increasingly used to align large language models. Popular RL algorithms utilize multiple workers and can be modeled as a graph, where each node is the status of a worker and each edge represents da…
View article: Mut4All: Fuzzing Compilers via LLM-Synthesized Mutators Learned from Bug Reports
Mut4All: Fuzzing Compilers via LLM-Synthesized Mutators Learned from Bug Reports Open
Mutation-based fuzzing is effective for uncovering compiler bugs, but designing high-quality mutators for modern languages with complex constructs (e.g., templates, macros) remains challenging. Existing methods rely heavily on manual desig…
View article: Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation
Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation Open
View article: LightBSR: Towards Lightweight Blind Super-Resolution via Discriminative Implicit Degradation Representation Learning
LightBSR: Towards Lightweight Blind Super-Resolution via Discriminative Implicit Degradation Representation Learning Open
Implicit degradation estimation-based blind super-resolution (IDE-BSR) hinges on extracting the implicit degradation representation (IDR) of the LR image and adapting it to LR image features to guide HR detail restoration. Although IDE-BSR…
View article: Diversity by Design: Addressing Mode Collapse Improves scRNA-seq Perturbation Modeling on Well-Calibrated Metrics
Diversity by Design: Addressing Mode Collapse Improves scRNA-seq Perturbation Modeling on Well-Calibrated Metrics Open
Recent benchmarks reveal that models for single-cell perturbation response are often outperformed by simply predicting the dataset mean. We trace this anomaly to a metric artifact: control-referenced deltas and unweighted error metrics rew…
View article: Gravitational effects on Hong-Ou-Mandel interference in terrestrial laboratory
Gravitational effects on Hong-Ou-Mandel interference in terrestrial laboratory Open
In this study, we investigate how Earth's gravitational field affects Hong-Ou-Mandel (HOM) interference experiments conducted in a terrestrial laboratory. To second order, we calculate the relativistic time delay from the null geodesic equ…
View article: How Far Are We from Generating Missing Modalities with Foundation Models?
How Far Are We from Generating Missing Modalities with Foundation Models? Open
Multimodal foundation models have demonstrated impressive capabilities across diverse tasks. However, their potential as plug-and-play solutions for missing modality reconstruction remains underexplored. To bridge this gap, we identify and…