Illinois Cognitive Computation Group UI-CCG TAC 2013 Entity Linking and Slot Filler Validation Systems. - Xiao Cheng; Bingling Chen; Rajhans Samdani; Kai-Wei Chang; Zhiye Fei; Mark Sammons; John Wieting; Subhro Roy; Chizheng Wang; Dan Roth 001 (TAC, 2013)

Tiered Clustering to Improve Lexical Entailment. - John Wieting (CoRR, 2014)

Clustering With Side Information: From a Probabilistic Model to a Deterministic Algorithm. - Daniel Khashabi; Jeffrey Yufei Liu; John Wieting; Feng Liang (CoRR, 2015)

From Paraphrase Database to Compositional Paraphrase Model and Back. - John Wieting; Mohit Bansal; Kevin Gimpel; Karen Livescu (Trans. Assoc. Comput. Linguistics, 2015)

Charagram: Embedding Words and Sentences via Character n-grams. - John Wieting; Mohit Bansal; Kevin Gimpel; Karen Livescu (EMNLP, 2016)

UMD-TTIC-UW at SemEval-2016 Task 1: Attention-Based Multi-Perspective Convolutional Neural Networks for Textual Similarity Measurement. - Hua He; John Wieting; Kevin Gimpel; Jinfeng Rao; Jimmy Lin (SemEval@NAACL-HLT, 2016)

Towards Universal Paraphrastic Sentence Embeddings. - John Wieting; Mohit Bansal; Kevin Gimpel; Karen Livescu (ICLR, 2016)

Revisiting Recurrent Networks for Paraphrastic Sentence Embeddings. - John Wieting; Kevin Gimpel (ACL (1), 2017)

Learning Paraphrastic Sentence Embeddings from Back-Translated Bitext. - John Wieting; Jonathan Mallinson; Kevin Gimpel (EMNLP, 2017)

Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations. - John Wieting; Kevin Gimpel (CoRR, 2017)

ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations. - John Wieting; Kevin Gimpel (ACL (1), 2018)

CogCompNLP: Your Swiss Army Knife for NLP. - Daniel Khashabi; Mark Sammons; Ben Zhou; Tom Redman; Christos Christodoulopoulos 001; Vivek Srikumar; Nicholas Rizzolo; Lev-Arie Ratinov; Guanheng Luo; Quang Do; Chen-Tse Tsai; Subhro Roy; et al. (LREC, 2018)

Adversarial Example Generation with Syntactically Controlled Paraphrase Networks. - Mohit Iyyer; John Wieting; Kevin Gimpel; Luke Zettlemoyer (NAACL-HLT, 2018)

Quality Signals in Generated Stories. - Manasvi Sagarkar; John Wieting; Lifu Tu; Kevin Gimpel (*SEM@NAACL-HLT, 2018)

Beyond BLEU: Training Neural Machine Translation with Semantic Similarity. - John Wieting; Taylor Berg-Kirkpatrick; Kevin Gimpel; Graham Neubig (ACL (1), 2019)

Simple and Effective Paraphrastic Similarity from Parallel Translations. - John Wieting; Kevin Gimpel; Graham Neubig; Taylor Berg-Kirkpatrick (ACL (1), 2019)

No Training Required: Exploring Random Encoders for Sentence Classification. - John Wieting; Douwe Kiela (ICLR (Poster), 2019)

Reformulating Unsupervised Style Transfer as Paraphrase Generation. - Kalpesh Krishna; John Wieting; Mohit Iyyer (EMNLP (1), 2020)

A Bilingual Generative Transformer for Semantic Sentence Embedding. - John Wieting; Graham Neubig; Taylor Berg-Kirkpatrick (EMNLP (1), 2020)

Improving Candidate Generation for Low-resource Cross-lingual Entity Linking. - Shuyan Zhou; Shruti Rijhwani; John Wieting; Jaime G. Carbonell; Graham Neubig (Trans. Assoc. Comput. Linguistics, 2020)

On Learning Text Style Transfer with Direct Rewards. - Yixin Liu 003; Graham Neubig; John Wieting (NAACL-HLT, 2021)

Improving the Diversity of Unsupervised Paraphrasing with Embedding Outputs. - Monisha Jegadeesan; Sachin Kumar 009; John Wieting; Yulia Tsvetkov (CoRR, 2021)

On The Ingredients of an Effective Zero-shot Semantic Parser. - Pengcheng Yin; John Wieting; Avirup Sil; Graham Neubig (ACL (1), 2022)

Faithful to the Document or to the World? Mitigating Hallucinations via Entity-Linked Knowledge in Abstractive Summarization. - Yue Dong 002; John Wieting; Pat Verga (EMNLP (Findings), 2022)

RankGen: Improving Text Generation with Large Ranking Models. - Kalpesh Krishna; Yapei Chang; John Wieting; Mohit Iyyer (EMNLP, 2022)

Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literature. - Katherine Thai; Marzena Karpinska; Kalpesh Krishna; Bill Ray; Moira Inghilleri; John Wieting; Mohit Iyyer (EMNLP, 2022)

Paraphrastic Representations at Scale. - John Wieting; Kevin Gimpel; Graham Neubig; Taylor Berg-Kirkpatrick (EMNLP (Demos), 2022)

Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation. - Jonathan H. Clark; Dan Garrette; Iulia Turc; John Wieting (Trans. Assoc. Comput. Linguistics, 2022)

QA Is the New KR: Question-Answer Pairs as Knowledge Bases. - William W. Cohen; Wenhu Chen; Michiel de Jong; Nitish Gupta; Alessandro Presta; Pat Verga; John Wieting (AAAI, 2023)

Beyond Contrastive Learning: A Variational Generative Model for Multilingual Retrieval. - John Wieting; Jonathan H. Clark; William W. Cohen; Graham Neubig; Taylor Berg-Kirkpatrick (ACL (1), 2023)

Augmenting Pre-trained Language Models with QA-Memory for Open-Domain Question Answering. - Wenhu Chen; Pat Verga; Michiel de Jong; John Wieting; William W. Cohen (EACL, 2023)

Evaluating and Modeling Attribution for Cross-Lingual Question Answering. - Benjamin Muller; John Wieting; Jonathan H. Clark; Tom Kwiatkowski; Sebastian Ruder; Livio Soares; Roee Aharoni; Jonathan Herzig; Xinyi Wang 001 (EMNLP, 2023)

XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages. - Sebastian Ruder; Jonathan H. Clark; Alexander Gutkin; Mihir Kale; Min Ma; Massimo Nicosia; Shruti Rijhwani; Parker Riley; Jean Michel A. Sarr; Xinyi Wang 001; John Wieting; Nitish Gupta; et al. (EMNLP (Findings), 2023)

Evaluating Large Language Models on Controlled Generation Tasks. - Jiao Sun; Yufei Tian; Wangchunshu Zhou; Nan Xu; Qian Hu; Rahul Gupta 001; John Frederick Wieting; Nanyun Peng 001; Xuezhe Ma (EMNLP, 2023)

Paraphrasing evades detectors of AI-generated text, but retrieval is an effective defense. - Kalpesh Krishna; Yixiao Song; Marzena Karpinska; John Wieting; Mohit Iyyer (NeurIPS, 2023)

A Gold Standard Dataset for the Reviewer Assignment Problem. - Ivan Stelmakh; John Wieting; Graham Neubig; Nihar B. Shah (CoRR, 2023)

FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning. - Xinyi Wang 001; John Wieting; Jonathan H. Clark (CoRR, 2023)

PostMark: A Robust Blackbox Watermark for Large Language Models. - Yapei Chang; Kalpesh Krishna; Amir Houmansadr; John Wieting; Mohit Iyyer (EMNLP, 2024)

Leveraging LLMs for Synthesizing Training Data Across Many Languages in Multilingual Dense Retrieval. - Nandan Thakur; Jianmo Ni; Gustavo Hernández Ábrego; John Wieting; Jimmy Lin; Daniel Cer (NAACL-HLT, 2024)

A Watermark for Black-Box Language Models. - Dara Bahri; John Wieting; Dana Alon; Donald Metzler (CoRR, 2024)

Multiple References with Meaningful Variations Improve Literary Machine Translation. - Si Wu; John Wieting; David A. Smith (CoRR, 2024)

A Gold Standard Dataset for the Reviewer Assignment Problem. - Ivan Stelmakh; John Frederick Wieting; Yang Xi; Graham Neubig; Nihar B. Shah (Trans. Mach. Learn. Res., 2025)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)