103 citations
- Rice UniversityUS4 papers
- University of Illinois Urbana-ChampaignUS3 papers
- The Ohio State UniversityUS2 papers
- Bellevue Hospital CenterUS1 paper
- Boston UniversityUS1 paper
- East Texas A&M UniversityUS1 paper
- Expedia Group (United States)US1 paper
- First Affiliated Hospital of Fujian Medical UniversityCN1 paper
- Fujian Medical UniversityCN1 paper
- Fuzhou UniversityCN1 paper
- Georgia Institute of TechnologyUS1 paper
- Linköping UniversitySE1 paper
26 papers
Enhancing Foundation Models in Transaction Understanding with LLM-based Sentence Embeddings
Xiran Fan, Zhimeng Jiang, Chin-Chia Michael Yeh +4
The ubiquity of payment networks generates vast transactional data encoding rich consumer and merchant behavioral patterns. Recent foundation models for transaction analysis proces…
Foundation Models for Autonomous Driving Perception: A Survey Through Core Capabilities
Rajendramayavan Sathyam, Yueqi Li
Foundation models are revolutionizing autonomous driving perception, transitioning the field from narrow, task-specific deep learning models to versatile, general-purpose architect…
CounterFace: A Synthetic Face Dataset for Fine-Grained Counterfactual Evaluation of Face Recognition Systems
Guruprasad Viswanathan Ramesh, Ashish Hooda, Shimaa Ahmed +3
Face recognition (FR) systems are widely deployed in critical applications, making their reliability and robustness across diverse populations and conditions essential. Standard ev…
Masked Graph Transformer for Large-Scale Recommendation
Huiyuan Chen, Zhe Xu, Chin-Chia Michael Yeh +4
Graph Transformers have garnered significant attention for learning graph-structured data, thanks to their superb ability to capture long-range dependencies among nodes. However, t…
Compressing and Interpreting Word Embeddings with Latent Space Regularization and Interactive Semantics Probing
Haoyu Li, Junpeng Wang, Yan Zheng +3
Word embedding, a high-dimensional (HD) numerical representation of words generated by machine learning models, has been used for different natural language processing tasks, e.g.,…
Towards Mitigating Dimensional Collapse of Representations in Collaborative Filtering
Huiyuan Chen, Vivian Lai, Hongye Jin +3
Contrastive Learning (CL) has shown promising performance in collaborative filtering. The key idea is to generate augmentation-invariant embeddings by maximizing the Mutual Informa…