Customer-obsessed science
Research areas
-
November 20, 20254 min readA new evaluation pipeline called FiSCo uncovers hidden biases and offers an assessment framework that evolves alongside language models.
-
October 2, 20253 min read
-
-
-
September 2, 20253 min read
Featured news
-
RecSys 2023 Industry Talk2023Personalization plays a critical role in helping customers discover the products and contents they prefer for e-commerce stores. Personalized recommendations differ in contents, target customers, and UI. However, they require a common core capability - the ability to deeply understand customers’ preferences and shopping intents. In this paper, we introduce the MCM (Multi-task pre-trained Customer Model)
-
Interspeech 20232023Audio privacy has been undertaken using adversarial task training or adversarial models based on GANs, where the models also suppress scoring of other attributes (e.g., emotion, etc.), but embeddings still retain enough information to bypass speaker privacy. We use methods for feature importance from the explainability literature to modify embeddings from adversarial task training, providing a simple and
-
IEEE 2023 Workshop on Machine Learning for Signal Processing (MLSP)2023Speech super-resolution is the process of estimating the missing frequency content of a speech signal from its existing band-limited frequency content. The loss of frequency components is a common occurrence that can be because of a low sampling rate, low-quality microphones, or various transmission factors, and it is an increasingly common problem as bandwidth for high-quality communications is generally
-
ACL 20232023We present a new task setting for attribute mining on e-commerce products, serving as a practical solution to extract open-world attributes without extensive human intervention. Our supervision comes from a high-quality seed attribute set bootstrapped from existing resources, and we aim to expand the attribute vocabulary of existing seed types, and also to discover any new attribute types automatically.
-
KDD 2023 Workshop on Mining and Learning with Graphs2023A hypergraph is a generalization of a graph that arises naturally when we consider attribute-sharing among entities. Although a hypergraph can be converted into a graph by expanding its hyperedges into fully connected subgraphs, going the reverse way is computationally complex and NP-complete. We hence hypothesize that a hypergraph contains more information than a graph. Moreover, it is more convenient
Collaborations
View allWhether you're a faculty member or student, there are number of ways you can engage with Amazon.
View all