12 citations · 13 across the 6 of their papers we have counts for
8 papers
Multimedia Asset Personalization via Multimodal Embeddings at Netflix
Emma Yanyang Kong, Aditya Deshpande, Bowei Yan +5
Personalized promotional assets, namely artwork images and video preview clips, are critical to content discovery on Netflix. Traditional models for asset selection rely on ID-base…
CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models
Santiago Castro, Amir Ziai, Avneesh Saluja +2
Recent years have witnessed a significant increase in the performance of Vision and Language tasks. Foundational Vision-Language Models (VLMs), such as CLIP, have been leveraged in…
Simplify-then-Translate: Automatic Preprocessing for Black-Box Machine Translation
Sneha Mehta, Bahareh Azarnoush, Boris Chen +4
Black-box machine translation systems have proven incredibly useful for a variety of applications yet by design are hard to adapt, tune to a specific domain, or build on top of. In…
Hierarchical Encoders for Modeling and Interpreting Screenplays
Gayatri Bhat, Avneesh Saluja, Melody Dye +1
While natural language understanding of long-form documents is still an open challenge, such documents often contain structural information that can inform the design of models for…
Using Aspect Extraction Approaches to Generate Review Summaries and User Profiles
Christopher Mitcheltree, Skyler Wharton, Avneesh Saluja
Reviews of products or services on Internet marketplace websites contain a rich amount of information. Users often wish to survey reviews or review snippets from the perspective of…
Paraphrase-Supervised Models of Compositionality
Avneesh Saluja, Chris Dyer, Jean-David Ruvini
Compositional vector space models of meaning promise new solutions to stubborn language understanding problems. This paper makes two contributions toward this end: (i) it uses auto…
Infinite Mixed Membership Matrix Factorization
Avneesh Saluja, Mahdi Pakdaman, Dongzhen Piao +1
Rating and recommendation systems have become a popular application area for applying a suite of machine learning techniques. Current approaches rely primarily on probabilistic int…
Language Modeling with Power Low Rank Ensembles
Ankur P. Parikh, Avneesh Saluja, Chris Dyer +1
We present power low rank ensembles (PLRE), a flexible framework for n-gram language modeling where ensembles of low rank matrices and tensors are used to obtain smoothed probabili…