337 citations · 2.2k across the 46 of their papers we have counts for
93 papers
Melody transcription via generative pre-training
Chris Donahue, John Thickstun, Percy Liang
Despite the central role that melody plays in music perception, it remains an open challenge in music information retrieval to reliably detect the notes of the melody present in an…
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization?
Rishi Bommasani, Kathleen A. Creel, Ananya Kumar +2
As the scope of machine learning broadens, we observe a recurring theme of algorithmic monoculture: the same systems, or systems that share components (e.g. training data), are dep…
How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions?
Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer +7
How do author perceptions match up to the outcomes of the peer-review process and perceptions of others? In a top-tier computer science conference (NeurIPS 2021) with more than 23,…
Truncation Sampling as Language Model Desmoothing
John Hewitt, Christopher D. Manning, Percy Liang
Long samples of text from neural language models can be of poor quality. Truncation sampling algorithms--like top- or top- -- address this by setting some words' probabilitie…
Deep Bidirectional Language-Knowledge Graph Pretraining
Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren +4
Pretraining a language model (LM) on text has been shown to help various downstream NLP tasks. Recent works show that a knowledge graph (KG) can complement text data, offering stru…
Diffusion-LM Improves Controllable Text Generation
Xiang Lisa Li, John Thickstun, Ishaan Gulrajani +2
Controlling the behavior of language models (LMs) without re-training is a major open problem in natural language generation. While recent works have demonstrated successes on cont…