6 papers
FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation
Fatema Siddika, Md Anwar Hossen, J. Pablo Muñoz +3
Parameter-efficient fine-tuning (PEFT) adapts large pre-trained models by updating only a small subset of parameters. Recently, Representation Fine-Tuning (ReFT) has emerged as an…
T^2Agent A Tool-augmented Multimodal Misinformation Detection Agent with Monte Carlo Tree Search
Xing Cui, Yueying Zou, Zekun Li +4
Real-world multimodal misinformation often arises from mixed forgery sources, requiring dynamic reasoning and adaptive verification. However, existing methods mainly rely on static…
OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
Ben Chen, Xian Guo, Siyuan Wang +25
Traditional e-commerce search systems employ multi-stage cascading architectures (MCA) that progressively filter items through recall, pre-ranking, and ranking stages. While effect…
Multiple Instance Verification
Xin Xu, Eibe Frank, Geoffrey Holmes
We explore multiple instance verification, a problem setting in which a query instance is verified against a bag of target instances with heterogeneous, unknown relevancy. We show…
EcoTransformer: Attention without Multiplication
Xin Gao, Xingming Xu, Shirin Amiraslani +1
The Transformer, with its scaled dot-product attention mechanism, has become a foundational architecture in modern AI. However, this mechanism is computationally intensive and incu…
Few-shot Classification as Multi-instance Verification: Effective Backbone-agnostic Transfer across Domains
Xin Xu, Eibe Frank, Geoffrey Holmes
We investigate cross-domain few-shot learning under the constraint that fine-tuning of backbones (i.e., feature extractors) is impossible or infeasible -- a scenario that is increa…