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05/23/2023
QLoRA: Efficient Finetuning of Quantized LLMs
We present QLoRA, an efficient finetuning approach that reduces memory u...
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12/20/2022
Socratic Pretraining: Question-Driven Pretraining for Controllable Summarization
In long document controllable summarization, where labeled data is scarc...
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04/27/2021
Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics
Modern summarization models generate highly fluent but often factually u...
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03/01/2020
StructSum: Incorporating Latent and Explicit Sentence Dependencies for Single Document Summarization
Traditional preneural approaches to single document summarization relied...
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06/10/2019
Making Classical Machine Learning Pipelines Differentiable: A Neural Translation Approach
Classical Machine Learning (ML) pipelines often comprise of multiple ML ...
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05/14/2019
Machine Learning at Microsoft with ML .NET
Machine Learning is transitioning from an art and science into a technol...
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01/21/2019
Analyzing Branch-and-Bound Algorithms for the Multiprocessor Scheduling Problem
The Multiprocessor Scheduling Problem (MSP) is an NP-Complete problem wi...
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12/16/2018
PAC Learning Guarantees Under Covariate Shift
We consider the Domain Adaptation problem, also known as the covariate s...
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12/11/2018
Conditional Variational Autoencoder for Neural Machine Translation
We explore the performance of latent variable models for conditional tex...
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07/22/2018
