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09/09/2023
FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning
Learning paradigms for large language models (LLMs) currently tend to fa...
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05/23/2023
Evaluating and Modeling Attribution for Cross-Lingual Question Answering
Trustworthy answer content is abundant in many high-resource languages a...
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05/19/2023
XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages
Data scarcity is a crucial issue for the development of highly multiling...
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03/23/2023
Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense
To detect the deployment of large language models for malicious use case...
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03/23/2023
A Gold Standard Dataset for the Reviewer Assignment Problem
Many peer-review venues are either using or looking to use algorithms to...
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12/21/2022
Beyond Contrastive Learning: A Variational Generative Model for Multilingual Retrieval
Contrastive learning has been successfully used for retrieval of semanti...
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10/25/2022
Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literature
Literary translation is a culturally significant task, but it is bottlen...
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07/01/2022
QA Is the New KR: Question-Answer Pairs as Knowledge Bases
In this position paper, we propose a new approach to generating a type o...
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05/19/2022
RankGen: Improving Text Generation with Large Ranking Models
Given an input sequence (or prefix), modern language models often assign...
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04/28/2022
Faithful to the Document or to the World? Mitigating Hallucinations via Entity-linked Knowledge in Abstractive Summarization
Despite recent advances in abstractive summarization, current summarizat...
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04/10/2022
Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering
Retrieval augmented language models have recently become the standard fo...
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10/15/2021
On The Ingredients of an Effective Zero-shot Semantic Parser
Semantic parsers map natural language utterances into meaning representa...
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04/30/2021
Paraphrastic Representations at Scale
We present a system that allows users to train their own state-of-the-ar...
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03/11/2021
CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representation
Pipelined NLP systems have largely been superseded by end-to-end neural ...
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10/24/2020
On Learning Text Style Transfer with Direct Rewards
In most cases, the lack of parallel corpora makes it impossible to direc...
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10/12/2020
Reformulating Unsupervised Style Transfer as Paraphrase Generation
Modern NLP defines the task of style transfer as modifying the style of ...
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03/03/2020
Improving Candidate Generation for Low-resource Cross-lingual Entity Linking
Cross-lingual entity linking (XEL) is the task of finding referents in a...
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11/10/2019
A Bilingual Generative Transformer for Semantic Sentence Embedding
Semantic sentence embedding models encode natural language sentences int...
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09/30/2019
Simple and Effective Paraphrastic Similarity from Parallel Translations
We present a model and methodology for learning paraphrastic sentence em...
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09/14/2019
Beyond BLEU: Training Neural Machine Translation with Semantic Similarity
While most neural machine translation (NMT) systems are still trained us...
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01/29/2019
No Training Required: Exploring Random Encoders for Sentence Classification
We explore various methods for computing sentence representations from p...
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04/17/2018
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks
We propose syntactically controlled paraphrase networks (SCPNs) and use ...
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11/15/2017
Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations
We extend the work of Wieting et al. (2017), back-translating a large pa...
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06/06/2017
Learning Paraphrastic Sentence Embeddings from Back-Translated Bitext
We consider the problem of learning general-purpose, paraphrastic senten...
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04/30/2017
Revisiting Recurrent Networks for Paraphrastic Sentence Embeddings
We consider the problem of learning general-purpose, paraphrastic senten...
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07/10/2016
Charagram: Embedding Words and Sentences via Character n-grams
We present Charagram embeddings, a simple approach for learning characte...
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11/25/2015
Towards Universal Paraphrastic Sentence Embeddings
We consider the problem of learning general-purpose, paraphrastic senten...
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08/25/2015
Clustering With Side Information: From a Probabilistic Model to a Deterministic Algorithm
In this paper, we propose a model-based clustering method (TVClust) that...
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12/02/2014
