Joaquín Cos Delgado

Oct 4, 2024 | amazon.science | Siddharth Sharma |Tarun Sharma |Joaquin A. Delgado |Joaquín Cos Delgado |Geetha Aluri

Improving search functionality poses challenges such as data scarcity for model training, metadata enrichment for comprehensive document indexing, and the labor-intensive manual annotation for evaluation. Traditionally, iterative methods relying on human annotators and customer feedback have been used. However, recent advancements in Large Language Models (LLMs) offer new solutions. This paper focuses on applying LLMs to playlist search.

Aug 4, 2023 | arxiv.org | Joaquín Cos Delgado

[Submitted on 4 Aug 2023] Title:Federated Learning: Organizational Opportunities, Challenges, and Adoption Strategies Download a PDF of the paper titled Federated Learning: Organizational Opportunities, Challenges, and Adoption Strategies, by Joaquin Delgado Fernandez and 4 other authors Download PDF Abstract: Restrictive rules for data sharing in many industries have led to thedevelopment of \ac{FL}.

Mar 10, 2023 | amazon.science | Eddie Huang |Jong Park |Joaquín Cos Delgado

Information retrieval engines like the one that helps Amazon customers find products in the Amazon Store commonly rely on bipartite graphs that map queries to products. The graphs are typically based on customer behaviors: if enough customers executing the same query click the link to a product or buy that product, the graph will include an edge between query and product. A graph neural network (GNN) can then ingest the graph and predict edges corresponding to new queries.

Mar 8, 2023 | amazon.science | William Brannon |Yogesh Virkar |Joaquín Cos Delgado |Brian Thompson

We investigate how humans perform the task of dubbing video content from one language into another, leveraging a novel corpus of 319.57 hours of video from 54 professionally produced titles. This is the first such largescale study we are aware of.