Chris Callison-Burch
7 papers in the PaperMetrix corpus
Papers by this author
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Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification
2019 · arXiv (Cornell University)
Sentence simplification is the task of rewriting texts so they are easier to understand. Recent research has applied sequence-to-sequence (Seq2Seq) models to this task, focusing largely on training-time improvements via reinforcement learning and memory augmentation. …
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Intent Detection with WikiHow
2020 · arXiv (Cornell University)
Modern task-oriented dialog systems need to reliably understand users' intents. Intent detection is most challenging when moving to new domains or new languages, since there is little annotated data. To address this challenge, we present …
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A Recipe For Arbitrary Text Style Transfer with Large Language Models
2021 · arXiv (Cornell University)
In this paper, we leverage large language models (LMs) to perform zero-shot text style transfer. We present a prompting method that we call augmented zero-shot learning, which frames style transfer as a sentence rewriting task …
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Human-in-the-loop Schema Induction
2023
Tianyi Zhang, Isaac Tham, Zhaoyi Hou, Jiaxuan Ren, Leon Zhou, Hainiu Xu, Li Zhang, Lara J. Martin, Rotem Dror, Sha Li, Heng Ji, Martha Palmer, Susan Windisch Brown, Reece Suchocki, Chris Callison-Burch. Proceedings of the …
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SemEval-2015 Task 1: Paraphrase and Semantic Similarity in Twitter (PIT)
2015
In this shared task, we present evaluations on two related tasks Paraphrase Identification (PI) and Semantic Textual Similarity (SS) systems for the Twitter data. Given a pair of sentences, participants are asked to produce a …
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Optimizing Statistical Machine Translation for Text Simplification
2016 · Transactions of the Association for Computational Linguistics
Most recent sentence simplification systems use basic machine translation models to learn lexical and syntactic paraphrases from a manually simplified parallel corpus. These methods are limited by the quality and quantity of manually simplified corpora, …
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Deduplicating Training Data Makes Language Models Better
2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Katherine Lee, Daphne Ippolito, Andrew Nystrom, Chiyuan Zhang, Douglas Eck, Chris Callison-Burch, Nicholas Carlini. Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2022.