1 citations · 2 across the 13 of their papers we have counts for
14 papers
Agents as Knowledge Integrator and Utilizer in Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +9
Online platforms increasingly rely on multimodal recommender systems to rank products, media, and other Web content. Existing methods usually inject visual and textual features int…
Well Begun is Half Done: Training-Free and Model-Agnostic Semantically Guaranteed User Representation Initialization for Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +6
Recent advancements in multimodal recommendations, which leverage diverse modality information to mitigate data sparsity and improve recommendation accuracy, have gained significan…
CAMMSR: Category-Guided Attentive Mixture of Experts for Multimodal Sequential Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +6
The explosion of multimedia data in information-rich environments has intensified the challenges of personalized content discovery, positioning recommendation systems as an essenti…
DeepAFL: Deep Analytic Federated Learning
Jianheng Tang, Yajiang Huang, Kejia Fan +8
Federated Learning (FL) is a popular distributed learning paradigm to break down data silo. Traditional FL approaches largely rely on gradient-based updates, facing significant iss…
FilDeep: Learning Large Deformations of Elastic-Plastic Solids with Multi-Fidelity Data
Jianheng Tang, Shilong Tao, Zhe Feng +4
The scientific computation of large deformations in elastic-plastic solids is crucial in various manufacturing applications. Traditional numerical methods exhibit several inherent…
APFL: Analytic Personalized Federated Learning via Dual-Stream Least Squares
Kejia Fan, Jianheng Tang, Zhirui Yang +8
Personalized Federated Learning (PFL) has presented a significant challenge to deliver personalized models to individual clients through collaborative training. Existing PFL method…
FedHiP: Heterogeneity-Invariant Personalized Federated Learning Through Closed-Form Solutions
Jianheng Tang, Zhirui Yang, Jingchao Wang +7
Lately, Personalized Federated Learning (PFL) has emerged as a prevalent paradigm to deliver personalized models by collaboratively training while simultaneously adapting to each c…
AFCL: Analytic Federated Continual Learning for Spatio-Temporal Invariance of Non-IID Data
Jianheng Tang, Huiping Zhuang, Jingyu He +10
Federated Continual Learning (FCL) enables distributed clients to collaboratively train a global model from online task streams in dynamic real-world scenarios. However, existing F…
Towards Efficient and Exact Forgetting Services in Pre-Trained-Model-based Continual Learning
Yajiang Huang, Jianheng Tang, Kejia Fan +6
In Continual Learning (CL), using a Pre-Trained Model (PTM) as the feature extractor has become a popular practice. Accompanied by analytic classifiers, the PTM-based methods have…
ZeroTuning: Unlocking the Initial Token's Power to Enhance Large Language Models Without Training
Feijiang Han, Xiaodong Yu, Jianheng Tang +3
Token-level attention tuning, a class of training-free methods including Post-hoc Attention Steering (PASTA) and Attention Calibration (ACT), has emerged as a promising approach fo…
Can LLMs Handle WebShell Detection? Overcoming Detection Challenges with Behavioral Function-Aware Framework
Feijiang Han, Jiaming Zhang, Chuyi Deng +2
WebShell attacks - where adversaries implant malicious scripts on web servers - remain a persistent threat. Prior machine-learning and deep-learning detectors typically depend on t…
CFSSeg: Closed-Form Solution for Class-Incremental Semantic Segmentation of 2D Images and 3D Point Clouds
Jiaxu Li, Rui Li, Jianyu Qi +8
2D images and 3D point clouds are foundational data types for multimedia applications, including real-time video analysis, augmented reality (AR), and 3D scene understanding. Class…
Learning New Concepts, Remembering the Old: Continual Learning for Multimodal Concept Bottleneck Models
Songning Lai, Mingqian Liao, Zhangyi Hu +6
Concept Bottleneck Models (CBMs) enhance the interpretability of AI systems, particularly by bridging visual input with human-understandable concepts, effectively acting as a form…
TS-ACL: Closed-Form Solution for Time Series-oriented Continual Learning
Jiaxu Li, Kejia Fan, Songning Lai +8
Time series classification underpins critical applications such as healthcare diagnostics and gesture-driven interactive systems in multimedia scenarios. However, time series class…