6 citations · 6 across the 2 of their papers we have counts for
3 papers
eess.AS2022
Text-Driven Separation of Arbitrary Sounds
Kevin Kilgour, Beat Gfeller, Qingqing Huang +3
We propose a method of separating a desired sound source from a single-channel mixture, based on either a textual description or a short audio sample of the target source. This is…
cs.LG2020★ 6 cited
Superbloom: Bloom filter meets Transformer
John Anderson, Qingqing Huang, Walid Krichene +2
We extend the idea of word pieces in natural language models to machine learning tasks on opaque ids. This is achieved by applying hash functions to map each id to multiple hash to…
cs.LG2019
Gradient-based Optimization for Bayesian Preference Elicitation
Ivan Vendrov, Tyler Lu, Qingqing Huang +1
Effective techniques for eliciting user preferences have taken on added importance as recommender systems (RSs) become increasingly interactive and conversational. A common and con…