arXiv subjects

Jing Teng

Publications and source records attributed to Jing Teng.

9 recordsLinked to original sources

arXiv2026

Federated Learning at the Forefront of Fairness: A Multifaceted Perspective

Fairness in Federated Learning (FL) is emerging as a critical factor driven by heterogeneous clients' constraints and balanced model performance across various scenarios. In this survey, we delineate a comprehensive classification of the state-of-the-art fairness-aware approaches from a multifaceted perspective, i.e., model performance-oriented and capability-oriented. Moreover, we provide a framework to categorize and address various fairness concerns and associated technical aspects, examining their effectiveness in balancing equity and performance within FL frameworks. We further examine several significant evaluation metrics leveraged to measure fairness quantitatively. Finally, we explore exciting open research directions and propose prospective solutions that could drive future advancements in this important area, laying a solid foundation for researchers working toward fairness in FL.

cs.LG↗

arXiv2026

Large Language Models to Enhance Multi-task Drone Operations in Simulated Environments

Benefiting from the rapid advancements in large language models (LLMs), human-drone interaction has reached unprecedented opportunities. In this paper, we propose a method that integrates a fine-tuned CodeT5 model with the Unreal Engine-based AirSim drone simulator to efficiently execute multi-task operations using natural language commands. This approach enables users to interact with simulated drones through prompts or command descriptions, allowing them to easily access and control the drone's status, significantly lowering the operational threshold. In the AirSim simulator, we can flexibly construct visually realistic dynamic environments to simulate drone applications in complex scenarios. By combining a large dataset of (natural language, program code) command-execution pairs generated by ChatGPT with developer-written drone code as training data, we fine-tune the CodeT5 to achieve automated translation from natural language to executable code for drone tasks. Experimental results demonstrate that the proposed method exhibits superior task execution efficiency and command understanding capabilities in simulated environments. In the future, we plan to extend the model functionality in a modular manner, enhancing its adaptability to complex scenarios and driving the application of drone technologies in real-world environments.

cs.RO↗

arXiv2026

Edge-Optimized Multimodal Learning for UAV Video Understanding via BLIP-2

The demand for real-time visual understanding and interaction in complex scenarios is increasingly critical for unmanned aerial vehicles. However, a significant challenge arises from the contradiction between the high computational cost of large Vision language models and the limited computing resources available on UAV edge devices. To address this challenge, this paper proposes a lightweight multimodal task platform based on BLIP-2, integrated with YOLO-World and YOLOv8-Seg models. This integration extends the multi-task capabilities of BLIP-2 for UAV applications with minimal adaptation and without requiring task-specific fine-tuning on drone data. Firstly, the deep integration of BLIP-2 with YOLO models enables it to leverage the precise perceptual results of YOLO for fundamental tasks like object detection and instance segmentation, thereby facilitating deeper visual-attention understanding and reasoning. Secondly, a content-aware key frame sampling mechanism based on K-Means clustering is designed, which incorporates intelligent frame selection and temporal feature concatenation. This equips the lightweight BLIP-2 architecture with the capability to handle video-level interactive tasks effectively. Thirdly, a unified prompt optimization scheme for multi-task adaptation is implemented. This scheme strategically injects structured event logs from the YOLO models as contextual information into BLIP-2's input. Combined with output constraints designed to filter out technical details, this approach effectively guides the model to generate accurate and contextually relevant outputs for various tasks.

cs.CV↗

arXiv2026

Hybrid Distillation with CoT Guidance for Edge-Drone Control Code Generation

With large language models demonstrating significant potential in code generation tasks, their application to onboard control of resource-constrained Unmanned Aerial Vehicles has emerged as an important research direction. However, a notable contradiction exists between the high resource consumption of large models and the real-time, lightweight requirements of UAV platforms. This paper proposes an integrated approach that combines knowledge distillation, chain-of-thought guidance, and supervised fine-tuning for UAV multi-SDK control tasks, aiming to efficiently transfer complex reasoning and code generation capabilities to smaller models. Firstly, a high-quality dataset covering various mainstream UAV SDKs is constructed, featuring instruction-code-reasoning chains, and incorporates counterfactual negative samples for data augmentation, guiding the model to learn the end-to-end logic from instruction parsing to code generation. Secondly, leveraging DeepSeek-Coder-V2-Lite quantized via QLoRA as the teacher model, and based on a hybrid black-box and white-box distillation strategy, high-quality chain-of-thought soft labels are generated. These are combined with a weighted cross-entropy loss using hard labels to transfer complex reasoning capabilities to the smaller student model. Finally, through prompt tuning engineering optimized for the UAV control scenario, the model performance on core tasks such as SDK type recognition and function call matching is enhanced. Experimental results indicate that the distilled lightweight model maintains high code generation accuracy while achieving significant improvements in deployment and inference efficiency, effectively demonstrating the feasibility and superiority of our approach in achieving precise and lightweight intelligent control for UAVs

cs.AI↗

arXiv2021

Magnetic Proximity Effect in an Antiferromagnetic Insulator/Topological Insulator Heterostructure with Sharp Interface

We report an experimental study of electron transport properties of MnSe/(Bi,Sb)2Te3 heterostructures, in which MnSe is an antiferromagnetic insulator, and (Bi,Sb)2Te3 is a three-dimensional topological insulator (TI). Strong magnetic proximity effect is manifested in the measurements of the Hall effect and longitudinal resistances. Our analysis shows that the gate voltage can substantially modify the anomalous Hall conductance, which exceeds 0.1 e2/h at temperature of 1.6 K and magnetic field of 5 T, even though only the top TI surface is in proximity to MnSe. This work suggests that heterostructures based on antiferromagnetic insulators provide a promising platform for investigating a wide range of topological spintronic phenomena.

cond-mat.mes-hall↗

arXiv2020

The anomalous Hall Effect in a Magnetically Extended Topological Insulator Heterostructure

Constructing heterostructures of a topological insulator (TI) with an undoped magnetic insulator (MI) is a clean and versatile approach to break the time-reversible symmetry in the TI surface states. Despite a lot of efforts, the strength of interfacial magnetic proximity effect (MPE) is still too weak to achieve the quantum anomalous Hall effect and many other topological quantum phenomena. Recently, a new approach based on intercalation of atomic layers of MI, referred to as magnetic extension, was proposed to realize strong MPE [2D Mater. 4, 025082(2017)]. Motivated by this proposal, here, we study a magnetic extension system prepared by molecular beam epitaxy growth of MnSe thin films on topological insulator (Bi,Sb)2Te3. Direct evidence is obtained for intercalation of MnSe atomic layer into a few quintuple layers of (Bi,Sb)2Te3, forming either a double magnetic septuple layer (SL) or an isolated single SL at the interface, where one SL denotes a van der Waals building block consisting of B-A-B-Mn-B-A-B (A=Bi1-xSbx, B= Te1-ySey). The two types of interfaces (namely TI/mono-SL and TI/bi-SL) have different MPE, which is manifested as distinctively different transport behaviors. Specifically, the mono-SL induces a spinflip transition with a sharp change at small magnetic field in the anomalous Hall effect of TI layers, while the bi-SL induces a spin-flop transition with a slow change at large field. Our work demonstrates a useful platform to realize the full potential of the magnetic extension approach for pursuing novel topological physics and related device applications.

physics.app-ph↗

arXiv2016

Hidden Phases Revealed at the Surface of Double-Layered Sr3(Ru1-xMnx)2O7

Double-layered Sr3Ru2O7 has received phenomenal consideration because it exhibits a plethora of exotic phases when perturbed. New phases emerge with the application of pressure, magnetic field, or doping. Here we show that creating a surface is an alternative and effective way to reveal hidden phases that are different from those seen in the bulk by investigating the surface properties of Sr3(Ru1-xMnx)2O7. Driven by the tilt distortion of RuO6 octahedra, the surface of Sr3Ru2O7 is less metallic than the bulk. In contrast, because of the vanishing of tilt and enhanced rotation with Mn-doping, the surface of Sr3(Ru0.84Mn0.16)2O7 is metallic while the bulk is insulating. Our result demonstrates that the electronic and structural properties at the surface are intimately coupled and consistent with quasi two-dimensional character.

cond-mat.str-el↗

arXiv2015

Proximity effect between a topological insulator and a magnetic insulator with large perpendicular anisotropy

We report that thin films of a prototype topological insulator, Bi$_{2}$Se$_{3}$, can be epitaxially grown onto the (0001) surface of BaFe$_{12}$O$_{19}$(BaM), a magnetic insulator with high Curie temperature and large perpendicular anisotropy. In the Bi$_2$Se$_3$ thin films grown on non-magnetic substrates, classic weak antilocalization (WAL) is manifested as cusp-shaped positive magnetoresistance (MR) in perpendicular magnetic fields and parabola-shaped positive MR in parallel fields, whereas in Bi$_{2}$Se$_{3}$/BaM heterostructures the low field MR is parabola-shaped, which is positive in perpendicular fields and negative in parallel fields. The magnetic field and temperature dependence of the MR is explained as a consequence of the suppression of WAL due to strong magnetic interactions at the Bi$_{2}$Se$_{3}$/BaM interface.

cond-mat.mes-hall↗

arXiv2009

Quintuple-layer epitaxy of high-quality Bi2Se3 thin films for topological insulator

We report the growth of atomically smooth, single crystalline Bi2Se3 thin films on Si(111) by using molecular beam epitaxy. Scanning tunneling microscopy, low-energy electron diffraction, X-ray photoelectron emission spectroscopy and Raman spectroscopy were used to characterize the stoichiometry and crystallinity of the film. The film grows in a self-organized quintuple-layer by quintuple-layer mode, and atomically smooth film can be obtained with the thickness down to one quintuple-layer (~1nm).

cond-mat.mes-hall↗