143 citations
- Technion – Israel Institute of TechnologyIL3 papers
- University of Illinois Urbana-ChampaignUS3 papers
- University of Wisconsin–MadisonUS3 papers
- Amazon (United States)US2 papers
- Institut de recherche mathématique de RennesFR2 papers
- Santa Clara UniversityUS2 papers
- SMART ReadingUS2 papers
- University of California, RiversideUS2 papers
- University of Illinois ChicagoUS2 papers
- University of VirginiaUS2 papers
- Arizona State UniversityUS1 paper
- Carnegie Mellon UniversityUS1 paper
58 papers
Scaling and Stabilizing Large-Scale Embedding-Based Retrieval
Zhen Yang, Juexin Lin, Hongwei Shang +8
Embedding-based retrieval (EBR) is foundational to large-scale e-commerce search, yet its effectiveness is often constrained by the quality of training signals and the representati…
Selection Bias Correction in Retail Intelligence
Spandan Ghose Chowdhury
Retail intelligence often relies on monitoring popular, high-velocity products, potentially biasing economic indicators by ignoring the "long tail" of niche items. This simulation…
LEAP: Layer-wise Exit-Aware Pretraining for Efficient Transformer Inference
Shashank Kapadia, Deep Naryan Mishra, Sujal Reddy Alugubelli +4
Layer-aligned distillation and convergence-based early exit represent two predominant computational efficiency paradigms for transformer inference; yet we establish that they exhib…
Monodense Deep Neural Model for Determining Item Price Elasticity
Lakshya Garg, Sai Yaswanth, Deep Narayan Mishra +3
Item Price Elasticity is used to quantify the responsiveness of consumer demand to changes in item prices, enabling businesses to create pricing strategies and optimize revenue man…
Latent Customer Segmentation and Value-Based Recommendation Leveraging a Two-Stage Model with Missing Labels
Keerthi Gopalakrishnan, Tianning Dong, Chia-Yen Ho +5
The success of businesses depends on their ability to convert consumers into loyal customers. A customer's value proposition is a primary determinant in this process, requiring a b…
A Mechanistic Perspective and Circuit-Guided Difficulty Metric for Unlearning
Jiali Cheng, Ziheng Chen, Chirag Agarwal +1
Machine unlearning is becoming essential for building trustworthy and compliant language models. Yet unlearning success varies considerably across individual samples: some are reli…