activity
20192021
most citedDExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts

11 citations · 18 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL202111 cited

DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts

Alisa Liu, Maarten Sap, Ximing Lu +4

Despite recent advances in natural language generation, it remains challenging to control attributes of generated text. We propose DExperts: Decoding-time Experts, a decoding-time…

cs.SD20201 cited

Incorporating Music Knowledge in Continual Dataset Augmentation for Music Generation

Alisa Liu, Alexander Fang, Gaëtan Hadjeres +2

Deep learning has rapidly become the state-of-the-art approach for music generation. However, training a deep model typically requires a large training set, which is often not avai…

cs.SD20206 cited

Bach or Mock? A Grading Function for Chorales in the Style of J.S. Bach

Alexander Fang, Alisa Liu, Prem Seetharaman +1

Deep generative systems that learn probabilistic models from a corpus of existing music do not explicitly encode knowledge of a musical style, compared to traditional rule-based sy…

eess.AS2019

Model selection for deep audio source separation via clustering analysis

Alisa Liu, Prem Seetharaman, Bryan Pardo

Audio source separation is the process of separating a mixture (e.g. a pop band recording) into isolated sounds from individual sources (e.g. just the lead vocals). Deep learning m…

cs.CL2019

Multi-sense Definition Modeling using Word Sense Decompositions

Ruimin Zhu, Thanapon Noraset, Alisa Liu +2

Word embeddings capture syntactic and semantic information about words. Definition modeling aims to make the semantic content in each embedding explicit, by outputting a natural la…