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Too important to be left to the Generals: The Politics of the Western Front (2025)
Book Chapter
Johnson, M. (in press). Too important to be left to the Generals: The Politics of the Western Front. In The Cambridge Companion to the Western Front. Cambridge University Press

‘War is too important to be left to the generals.’ This aphorism, commonly attributed to the French Premier Georges Clemenceau, captures one of the most significant dilemmas to confront the states that went to war in the summer of 1914: should the pr... Read More about Too important to be left to the Generals: The Politics of the Western Front.

Compiler support for semi-manual AoS-to-SoA conversions with data views (2025)
Presentation / Conference Contribution
Radtke, P., & Weinzierl, T. (2024, September). Compiler support for semi-manual AoS-to-SoA conversions with data views. Presented at PPAM 2024 - 15th International Conference on Parallel Processing & Applied Mathematics, Ostrava, Czech Republic

The C programming language and its cousins such as C++ stipulate the static storage of sets of structured data: Developers have to commit to one, invariant data model -- typically a structure-of-arrays (SoA) or an array-of-structs (AoS) -- unles... Read More about Compiler support for semi-manual AoS-to-SoA conversions with data views.

FineCausal: A Causal-Based Framework for Interpretable Fine-Grained Action Quality Assessment (2025)
Presentation / Conference Contribution
Han, R., Zhou, K., Atapour-Abarghouei, A., Liang, X., & Shum, H. P. H. (2025, June). FineCausal: A Causal-Based Framework for Interpretable Fine-Grained Action Quality Assessment. Presented at Proceedings of the 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025, Music City Center, Nashville TN

Action quality assessment (AQA) is critical for evaluating athletic performance, informing training strategies, and ensuring safety in competitive sports. However, existing deep learning approaches often operate as black boxes and are vulnerable to s... Read More about FineCausal: A Causal-Based Framework for Interpretable Fine-Grained Action Quality Assessment.

T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles (2025)
Journal Article
Pan, H., Zahmatkesh, M., Rekabi-Bana, F., Arvin, F., & Hu, J. (in press). T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles. IEEE Transactions on Intelligent Transportation Systems,

This paper introduces a time-optimal swarm tra-jectory planner for cooperative unmanned aerial vehicle (UAV) systems, designed to generate collision-free trajectories for flocking control in cluttered environments. To achieve this goal, model predict... Read More about T-STAR: Time-Optimal Swarm Trajectory Planning for Quadrotor Unmanned Aerial Vehicles.

BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction (2025)
Journal Article
Li, R., Katsigiannis, S., Kim, T.-K., & Shum, H. (online). BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction. IEEE Transactions on Neural Networks and Learning Systems, https://doi.org/10.1109/TNNLS.2025.3545268

Trajectory prediction allows better decision-making in applications of autonomous vehicles or surveillance by predicting the short-term future movement of traffic agents. It is classified into pedestrian or heterogeneous trajectory prediction. The fo... Read More about BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory Prediction.

Reconfigurable routing in data center networks (2025)
Journal Article
Stewart, I., & Kutner, D. (2025). Reconfigurable routing in data center networks. Theoretical Computer Science, 1038, Article 115154. https://doi.org/10.1016/j.tcs.2025.115154

A hybrid network is a static (electronic) network that is augmented with optical switches. The Reconfigurable Routing Problem (RRP) in hybrid networks is the problem of finding settings for the optical switches augmenting a static network so as to ac... Read More about Reconfigurable routing in data center networks.

Multi-modal Dynamic Point Cloud Geometric Compression Based on Bidirectional Recurrent Scene Flow* (2025)
Presentation / Conference Contribution
Nan, F., Li, F., Wang, Z., Tam, G. K. L., Jiang, Z., DongZheng, D., & Yang, B. (2025, April). Multi-modal Dynamic Point Cloud Geometric Compression Based on Bidirectional Recurrent Scene Flow*. Presented at ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India

Deep learning methods have recently shown significant promise in compressing the geometric features of point clouds. However, challenges arise when consecutive point clouds contain holes, resulting in incomplete information that complicates motion es... Read More about Multi-modal Dynamic Point Cloud Geometric Compression Based on Bidirectional Recurrent Scene Flow*.

Fg-T2M++: LLMs-Augmented Fine-Grained Text Driven Human Motion Generation (2025)
Journal Article
Wang, Y., Li, M., Liu, J., Leng, Z., Li, F. W. B., Zhang, Z., & Liang, X. (online). Fg-T2M++: LLMs-Augmented Fine-Grained Text Driven Human Motion Generation. International Journal of Computer Vision, https://doi.org/10.1007/s11263-025-02392-9

We address the challenging problem of fine-grained text-driven human motion generation. Existing works generate imprecise motions that fail to accurately capture relationships specified in text due to: (1) lack of effective text parsing for detailed... Read More about Fg-T2M++: LLMs-Augmented Fine-Grained Text Driven Human Motion Generation.

HotReRAM: A Performance-Power-Thermal Simulation Framework for ReRAM based Caches (2025)
Journal Article
Chakraborty, S., Bunnam, T., Arunruerk, J., Agarwal, S., Yu, S., Shafik, R., & Sjalander, M. (online). HotReRAM: A Performance-Power-Thermal Simulation Framework for ReRAM based Caches. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, https://doi.org/10.1109/TCAD.2025.3546855

This paper proposes a comprehensive thermal modeling and simulation framework, HotReRAM, for resistive RAM (ReRAM)-based caches that is verified against a memristor circuit-level model. The simulation is driven by power traces based on cache accesses... Read More about HotReRAM: A Performance-Power-Thermal Simulation Framework for ReRAM based Caches.

Experimental Evaluation of Multi- and Single-Drone Systems with 1D LiDAR Sensors for Stockpile Volume Estimation (2025)
Journal Article
Alsayed, A., Bana, F., Arvin, F., Quinn, M. K., & Nabawy, M. R. A. (2025). Experimental Evaluation of Multi- and Single-Drone Systems with 1D LiDAR Sensors for Stockpile Volume Estimation. Aerospace, 12(3), Article 189. https://doi.org/10.3390/aerospace12030189

This study examines the application of low-cost 1D LiDAR sensors in drone-based stockpile volume estimation, with a focus on indoor environments. Three approaches were experimentally investigated: (i) a multi-drone system equipped with static, downwa... Read More about Experimental Evaluation of Multi- and Single-Drone Systems with 1D LiDAR Sensors for Stockpile Volume Estimation.

Dynamic Calibration of Trust and Trustworthiness in AI-Enabled Systems (2025)
Journal Article
Liebherr, M., Enkel, E., Law, E. L.-C., Mousavi, M. R., Sammartino, M., & Sieberg, P. (in press). Dynamic Calibration of Trust and Trustworthiness in AI-Enabled Systems. International Journal on Software Tools for Technology Transfer,

Trust is a multi-faceted phenomenon traditionally studied in human relations and more recently in human-machine interactions. In the context of AI-enabled systems, trust is about the belief of the user that in a given scenario the system is going to... Read More about Dynamic Calibration of Trust and Trustworthiness in AI-Enabled Systems.

1-in-3 vs. Not-All-Equal: Dichotomy of a broken promise (2025)
Journal Article
Ciardo, L., Kozik, M., Krokhin, A., Nakajima, T.-V., & Živný, S. (online). 1-in-3 vs. Not-All-Equal: Dichotomy of a broken promise. ACM Transactions on Computational Logic, https://doi.org/10.1145/3719007

The 1-in-3 and Not-All-Equal satisfiability problems for Boolean CNF formulas are two well-known NP-hard problems. In contrast, the promise 1-in-3 vs. Not-All-Equal problem can be solved in polynomial time. In the present work, we investigate this co... Read More about 1-in-3 vs. Not-All-Equal: Dichotomy of a broken promise.

Coordination Mechanisms in AI Development: Practitioner Experiences on Integrating UX Activities (2025)
Presentation / Conference Contribution
Bruun, A., Van Berkel, N., Raptis, D., & Law, E. L.-C. (2025, April). Coordination Mechanisms in AI Development: Practitioner Experiences on Integrating UX Activities. Presented at CHI 2025 (Conference on Human Factors in Computing Systems), Yokohama, Japan

Software development relies on collaboration and alignment between a variety of roles, including software developers and user experience designers. The increasing focus on artificial intelligence in today's development projects has given rise to new... Read More about Coordination Mechanisms in AI Development: Practitioner Experiences on Integrating UX Activities.

SKDU at De-Factify 4.0: Natural language features for AI-Generated Text-Detection (2025)
Presentation / Conference Contribution
Maviya, S., Arnau-González, P., Arevalillo-Herráez, M., & Katsigiannis, S. (2025, February). SKDU at De-Factify 4.0: Natural language features for AI-Generated Text-Detection. Presented at De-factify 4.0 Workshop at 39th Annual AAAI Conference on Artificial Intelligence, Philadelphia, PA, USA

Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction (2025)
Journal Article
Li, R., Qiao, T., Katsigiannis, S., Zhu, Z., & Shum, H. P. (online). Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction. IEEE Transactions on Circuits and Systems for Video Technology, https://doi.org/10.1109/TCSVT.2025.3539522

Pedestrian trajectory prediction aims to forecast future movements based on historical paths. Spatial-temporal (ST) methods often separately model spatial interactions among pedestrians and temporal dependencies of individuals. They overlook the dire... Read More about Unified Spatial-Temporal Edge-Enhanced Graph Networks for Pedestrian Trajectory Prediction.

3D data augmentation and dual-branch model for robust face forgery detection (2025)
Journal Article
Zhou, C., Li, F. W., Song, C., Zheng, D., & Yang, B. (2025). 3D data augmentation and dual-branch model for robust face forgery detection. Graphical Models, 138, Article 101255. https://doi.org/10.1016/j.gmod.2025.101255

We propose Dual-Branch Network (DBNet), a novel deepfake detection framework that addresses key limitations of existing works by jointly modeling 3D-temporal and fine-grained texture representations. Specifically, we aim to investigate how to (1) cap... Read More about 3D data augmentation and dual-branch model for robust face forgery detection.