Search Results for author:
Found 10 papers, 7 papers with code
Read, Revise, Repeat: A System Demonstration for Human-in-the-loop Iterative Text Revision
Examining and evaluating the capability of large language models for making continuous revisions and collaborating with human writers is a critical step towards building effective writing assistants.
GRS: Combining Generation and Revision in Unsupervised Sentence Simplification
We propose GRS: an unsupervised approach to sentence simplification that combines text generation and text revision.
Understanding Iterative Revision from Human-Written Text
Writing is, by nature, a strategic, adaptive, and more importantly, an iterative process.
LyricJam: A system for generating lyrics for live instrumental music
We describe a real-time system that receives a live audio stream from a jam session and generates lyric lines that are congruent with the live music being played.
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics
We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics.
Ranked #1 on
Data-to-Text Generation
on WebNLG ru
Abstractive Text Summarization
Cross-Lingual Abstractive Summarization
+5
Optimizing Deeper Transformers on Small Datasets
This work shows that this does not always need to be the case: with proper initialization and optimization, the benefits of very deep transformers can carry over to challenging tasks with small datasets, including Text-to-SQL semantic parsing and logical reading comprehension.
Generation of lyrics lines conditioned on music audio clips
We present a system for generating novel lyrics lines conditioned on music audio.
Iterative Edit-Based Unsupervised Sentence Simplification
We present a novel iterative, edit-based approach to unsupervised sentence simplification.
Ranked #5 on
Text Simplification
on Newsela
Consentio: Managing Consent to Data Access using Permissioned Blockchains
The data management challenge we address is to ensure high throughput and low latency of endorsing data access requests and granting or revoking consent.
Distributed, Parallel, and Cluster Computing
Online abuse detection: the value of preprocessing and neural attention models
We propose an attention-based neural network approach to detect abusive speech in online social networks.
