Search Results for author:
Found 12 papers, 6 papers with code
Robust Speech Recognition via Large-Scale Weak Supervision
We study the capabilities of speech processing systems trained simply to predict large amounts of transcripts of audio on the internet.
Ranked #1 on
Speech Recognition
on Common Voice English
(using extra training data)
Text and Code Embeddings by Contrastive Pre-Training
Similarly to text embeddings, we train code embedding models on (text, code) pairs, obtaining a 20. 8% relative improvement over prior best work on code search.
Ranked #1 on
Code Search
on CodeSearchNet
Robust fine-tuning of zero-shot models
Compared to standard fine-tuning, WiSE-FT provides large accuracy improvements under distribution shift, while preserving high accuracy on the target distribution.
Ranked #10 on
Image Classification
on ObjectNet
(using extra training data)
Evaluating CLIP: Towards Characterization of Broader Capabilities and Downstream Implications
Recently, there have been breakthroughs in computer vision ("CV") models that are more generalizable with the advent of models such as CLIP and ALIGN.
Learning Transferable Visual Models From Natural Language Supervision
State-of-the-art computer vision systems are trained to predict a fixed set of predetermined object categories.
Ranked #1 on
Zero-Shot Learning
on COCO-MLT
(using extra training data)
Reliability Check via Weight Similarity in Privacy-Preserving Multi-Party Machine Learning
Multi-party machine learning is a paradigm in which multiple participants collaboratively train a machine learning model to achieve a common learning objective without sharing their privately owned data.
Jukebox: A Generative Model for Music
We introduce Jukebox, a model that generates music with singing in the raw audio domain.
Successive Point-of-Interest Recommendation with Local Differential Privacy
A point-of-interest (POI) recommendation system performs an important role in location-based services because it can help people to explore new locations and promote advertisers to launch advertisements at appropriate locations.
Release Strategies and the Social Impacts of Language Models
Large language models have a range of beneficial uses: they can assist in prose, poetry, and programming; analyze dataset biases; and more.
Adversarial Learning for Improved Onsets and Frames Music Transcription
Automatic music transcription is considered to be one of the hardest problems in music information retrieval, yet recent deep learning approaches have achieved substantial improvements on transcription performance.
Neural Music Synthesis for Flexible Timbre Control
The recent success of raw audio waveform synthesis models like WaveNet motivates a new approach for music synthesis, in which the entire process --- creating audio samples from a score and instrument information --- is modeled using generative neural networks.
CREPE: A Convolutional Representation for Pitch Estimation
To date, the best performing techniques, such as the pYIN algorithm, are based on a combination of DSP pipelines and heuristics.
