7 papers
AutoRelAnnotator: Calibrated Model Cascades for Cost-Efficient Relevance Evaluation in Sponsored Search
Md Omar Faruk Rokon, Shasvat Desai, Hong Yao +1
How can we generate high-quality relevance annotations at scale without the cost and delays of human labeling? Relevance annotations are the backbone of search ranking systems whic…
Macro Graph of Experts for Billion-Scale Multi-Task Recommendation
Hongyu Yao, Zijin Hong, Hao Chen +6
Graph-based multi-task learning at billion-scale presents a significant challenge, as different tasks correspond to distinct billion-scale graphs. Traditional multi-task learning m…
Unified Multi-Task Relevance Modeling for E-Commerce: Comparing Task Routing Architectures Across LLMs and Cross-Encoders
Md Omar Faruk Rokon, Jhalak Nilesh Acharya, Shasvat Desai +2
How can we build a single relevance model that handles six different entity pair relationship types in e commerce from query product matching to product type similarity when each t…
Scaling Dense Retrieval with LLM-Annotated Training Data: Structured Mining and Progressive Curriculum for E-Commerce Sponsored Search
Md Omar Faruk Rokon, Shasvat Desai, Jhalak Nilesh Acharya +9
How can we generate high-quality training data for dense retrieval models at production scale, without relying on click signals or manual annotation? This question is critical for…
INSPIRE: Intent-aware Neural Sponsored Product Retrieval for E-commerce
Shasvat Desai, Hong Yao, Utkarsh Porwal +1
Walmart holds the largest share of the U.S. ecommerce grocery market, where food and beverage categories generate some of the highest search traffic and, consequently, drive a subs…
From `May' to `Is': Certainty Distortion in Language Model Rewriting
Catarina G Belem, Shang Wu, Hongyu Yao +3
Humans increasingly turn to Language Models (LMs) in ways that shape beliefs and drive decisions, including discussing, rewriting, and summarizing information from scientific artic…