Papers by Arya D. McCarthy
Theory-Grounded Computational Text Analysis (2023.acl-short)
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| Challenge: | A broad space separates its two constituent disciplines—natural language processing and social science—which has to date been sidestepped rather than filled by applying increasingly complex computational models to problems in social science research. |
| Approach: | They argue that computational text analysis lacks organizing principles and requires organizing methods to solve problems. |
| Outcome: | The proposed approach is based on a review of 60 papers on computational text analysis. |
Massively Multilingual Pronunciation Modeling with WikiPron (2020.lrec-1)
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Jackson L. Lee, Lucas F.E. Ashby, M. Elizabeth Garza, Yeonju Lee-Sikka, Sean Miller, Alan Wong, Arya D. McCarthy, Kyle Gorman
| Challenge: | WikiPron is an open-source command-line tool for extracting pronunciation data from Wiktionary . the tool generates a database of 1.7 million pronunciations from 165 languages . |
| Approach: | They propose a command-line tool for extracting pronunciation data from Wiktionary . they use it to generate a database of 1.7 million pronunciations from 165 languages . |
| Outcome: | The proposed software generates a database of pronunciations for 165 languages . the proposed model is then validated by a grapheme-to-phoneme model . |
Deciphering and Characterizing Out-of-Vocabulary Words for Morphologically Rich Languages (2022.coling-1)
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| Challenge: | a detailed empirical case study of out-of-vocabulary words in modern text is presented . unfamiliar words cause trouble for machine processing or comprehension of text, authors say . |
| Approach: | They propose a detailed empirical case study of the nature of out-of-vocabulary words encountered in modern text in a moderate-resource language such as Bulgarian . they apply a multi-faceted distributional analysis of the underlying word-formation processes to characterize the residual vocabulary . |
| Outcome: | The proposed method can be used to aid in compositional translation, parsing, language modeling, and other NLP tasks. |
Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions (2020.emnlp-main)
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| Challenge: | A grammatical gender system divides a lexicon into a small number of fixed categories with fixed usage across speakers. |
| Approach: | They propose to define gender systems extensionally to reduce comparisons to cluster evaluation by comparing pairwise overlaps between gender systems. |
| Outcome: | The proposed measures are based on a phylogenetic tree over extant Indo-European languages. |
Neural Transduction for Multilingual Lexical Translation (2020.coling-main)
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| Challenge: | a method for completing multilingual translation dictionaries is proposed . a 27% relative improvement in whole-word accuracy is achieved when multilingual data is unavailable . |
| Approach: | They propose a method for completing multilingual translation dictionaries using multilingual inputs and multilingual decoding objective. |
| Outcome: | The proposed method can synthesize new word forms in multilingual translation dictionaries . it can perform in settings where correct translations have not been observed in text . |
Addressing Posterior Collapse with Mutual Information for Improved Variational Neural Machine Translation (2020.acl-main)
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| Challenge: | Existing variational inference models ignore their latent variables, a phenomenon called posterior collapse. |
| Approach: | They propose a new loss function for conditional variational autoencoders that counteracts posterior collapse by using a modified evidence lower bound objective and a factorized decoder. |
| Outcome: | The proposed model yields improved translation quality compared to existing models on WMT RoEn and DeEn. |
The Johns Hopkins University Bible Corpus: 1600+ Tongues for Typological Exploration (2020.lrec-1)
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Arya D. McCarthy, Rachel Wicks, Dylan Lewis, Aaron Mueller, Winston Wu, Oliver Adams, Garrett Nicolai, Matt Post, David Yarowsky
| Challenge: | Our corpus spans 1611 diverse written languages, with constituents of more than 90 language families. |
| Approach: | They propose to scrape and merge online resources and merge them with existing corpora to create a verse-parallel scheme for all translations. |
| Outcome: | The results show that the Bible provides high coverage of core vocabulary. |
Meaning to Form: Measuring Systematicity as Information (P19-1)
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| Challenge: | A longstanding debate in semiotics centers on the relationship between linguistic signs and their corresponding semantics: is there an arbitrary relationship between word forms and their meaning, or does some systematic phenomenon pervade? |
| Approach: | They propose to quantify the systematicity of the sign using mutual information and recurrent neural networks to examine 106 languages. |
| Outcome: | The proposed model reduces entropy in a word form conditioned on its semantic representation and recovers English examples of systematic affixes. |
Hong Kong: Longitudinal and Synchronic Characterisations of Protest News between 1998 and 2020 (2022.lrec-1)
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| Challenge: | This paper examines the utility and timeliness of the Hong Kong Protest News Dataset . it sheds light on whether depth and/or manner of reporting changed over time . |
| Approach: | They use the Hong Kong Protest News Dataset to investigate synchronic news characterisations of protests in Hong Kong between 1998 and 2020. |
| Outcome: | The dataset sheds light on whether depth and/or manner of reporting changed over time, and if so, in what ways, or in response to what. |
Jump-Starting Item Parameters for Adaptive Language Tests (2021.emnlp-main)
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| Challenge: | Prior work has addressed ‘cold start’ estimation of item difficulties without piloting, but a multi-task generalized linear model with BERT features is needed to jump-start new items without pilot. |
| Approach: | They propose a multi-task generalized linear model with BERT features to jump-start new item difficulties without piloting them first. |
| Outcome: | The proposed model compares test-taker proficiency, item difficulty, and language proficiency frameworks like the Common European Framework of Reference (CEFR). |
Predicting Declension Class from Form and Meaning (2020.acl-main)
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| Challenge: | phonological form and meaning of nouns can provide imperfect clues, but they can also be indicative of grammatical gender. |
| Approach: | They propose a method to measure how much information can be gleamed from knowing the form and/or meaning of nouns. |
| Outcome: | The proposed method provides additional quantitative support for a classic linguistic finding that form and meaning are relevant for the classification of nouns into declensions. |
Modeling Color Terminology Across Thousands of Languages (D19-1)
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| Challenge: | Existing studies on what constitutes a "basic" color term and its acquisition sequence are flawed . a pan-lingual approach may reveal general color trends more reliably than smaller datasets. |
| Approach: | They propose to operationalize and critique the Berlin and Kay color term hypotheses . they use 14 empirically-grounded computational linguistic metrics to analyze cross-linguistic data . |
| Outcome: | The proposed measures correlate strongly with the Berlin and Kay color term partition and their hypothesized universal acquisition sequence. |
An Analysis of Massively Multilingual Neural Machine Translation for Low-Resource Languages (2020.lrec-1)
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| Challenge: | In this study, we explore massively multilingual low-resource neural machine translation. |
| Approach: | They propose to use Bible translations to train models with up to 1,107 source languages and create multilingual corpora varying the number and relatedness of source languages. |
| Outcome: | The proposed approach is highly language-specific and can be tailored to the source language and its typology. |
UniMorph 4.0: Universal Morphology (2022.lrec-1)
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Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa, Nizar Habash, Witold Kieraś, Gábor Bella, Brian Leonard, Garrett Nicolai, Kyle Gorman, Yustinus Ghanggo Ate, Maria Ryskina, Sabrina Mielke, Elena Budianskaya, Charbel El-Khaissi, Tiago Pimentel, Michael Gasser, William Abbott Lane, Mohit Raj, Matt Coler, Jaime Rafael Montoya Samame, Delio Siticonatzi Camaiteri, Esaú Zumaeta Rojas, Didier López Francis, Arturo Oncevay, Juan López Bautista, Gema Celeste Silva Villegas, Lucas Torroba Hennigen, Adam Ek, David Guriel, Peter Dirix, Jean-Philippe Bernardy, Andrey Scherbakov, Aziyana Bayyr-ool, Antonios Anastasopoulos, Roberto Zariquiey, Karina Sheifer, Sofya Ganieva, Hilaria Cruz, Ritván Karahóǧa, Stella Markantonatou, George Pavlidis, Matvey Plugaryov, Elena Klyachko, Ali Salehi, Candy Angulo, Jatayu Baxi, Andrew Krizhanovsky, Natalia Krizhanovskaya, Elizabeth Salesky, Clara Vania, Sardana Ivanova, Jennifer White, Rowan Hall Maudslay, Josef Valvoda, Ran Zmigrod, Paula Czarnowska, Irene Nikkarinen, Aelita Salchak, Brijesh Bhatt, Christopher Straughn, Zoey Liu, Jonathan North Washington, Yuval Pinter, Duygu Ataman, Marcin Wolinski, Totok Suhardijanto, Anna Yablonskaya, Niklas Stoehr, Hossep Dolatian, Zahroh Nuriah, Shyam Ratan, Francis M. Tyers, Edoardo M. Ponti, Grant Aiton, Aryaman Arora, Richard J. Hatcher, Ritesh Kumar, Jeremiah Young, Daria Rodionova, Anastasia Yemelina, Taras Andrushko, Igor Marchenko, Polina Mashkovtseva, Alexandra Serova, Emily Prud’hommeaux, Maria Nepomniashchaya, Fausto Giunchiglia, Eleanor Chodroff, Mans Hulden, Miikka Silfverberg, Arya D. McCarthy, David Yarowsky, Ryan Cotterell, Reut Tsarfaty, Ekaterina Vylomova
| Challenge: | The Universal Morphology project provides broad-coverage instantiated morphological inflection tables for hundreds of diverse languages. |
| Approach: | They propose a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema. |
| Outcome: | The proposed schema has added 66 new languages, including 24 endangered languages. |
Fine-grained Morphosyntactic Analysis and Generation Tools for More Than One Thousand Languages (2020.lrec-1)
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| Challenge: | Using morphosyntactic tools, we train and distribute tools for approximately one thousand languages. |
| Approach: | They train and distribute morphosyntactic tools for approximately one thousand languages. |
| Outcome: | The results show that the tools generalize well across rare and common forms alike. |
A Major Obstacle for NLP Research: Let’s Talk about Time Allocation! (2022.emnlp-main)
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| Challenge: | Subpar time allocation has been a major obstacle for natural language processing research in recent years, argues a new position paper . |
| Approach: | They propose to identify the biggest traps the NLP community falls into and suggest solutions to solve them. |
| Outcome: | The authors outline multiple concrete problems together with their negative consequences and suggest remedies to improve the status quo. |
Meeting the Needs of Low-Resource Languages: The Value of Automatic Alignments via Pretrained Models (2023.eacl-main)
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Abteen Ebrahimi, Arya D. McCarthy, Arturo Oncevay, John E. Ortega, Luis Chiruzzo, Gustavo Giménez-Lugo, Rolando Coto-Solano, Katharina Kann
| Challenge: | Large multilingual models have inspired a new class of word alignment methods, which work well for pretraining languages. |
| Approach: | They propose to use transformer-based word alignment methods to extract alignments from massive pretrained models. |
| Outcome: | The proposed methods outperform traditional methods for languages unseen to pretraining models, and are competitive with each other. |
UniMorph 3.0: Universal Morphology (2020.lrec-1)
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Arya D. McCarthy, Christo Kirov, Matteo Grella, Amrit Nidhi, Patrick Xia, Kyle Gorman, Ekaterina Vylomova, Sabrina J. Mielke, Garrett Nicolai, Miikka Silfverberg, Timofey Arkhangelskiy, Nataly Krizhanovsky, Andrew Krizhanovsky, Elena Klyachko, Alexey Sorokin, John Mansfield, Valts Ernštreits, Yuval Pinter, Cassandra L. Jacobs, Ryan Cotterell, Mans Hulden, David Yarowsky
| Challenge: | Explicit modeling of morphology has demonstrable benefits for language modeling, speech recognition, word embedding and keyword search. |
| Approach: | They propose a language-independent feature schema for rich morphological annotation and a type-level resource for annotated data in diverse languages. |
| Outcome: | The proposed schema has been improved to make it more complete and correct, and adds 66 new languages and parts of speech for 12 languages. |
LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain (2025.findings-naacl)
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Joel Niklaus, Lucia Zheng, Arya D. McCarthy, Christopher Hahn, Brian M Rosen, Peter Henderson, Daniel E. Ho, Garrett Honke, Percy Liang, Christopher D Manning
| Challenge: | In general, instruction tuning is important for direct user interaction, but the legal domain is underrepresented in typical instruction datasets. |
| Approach: | They aggregate 58 annotated legal datasets and write instructions for each to create LawInstruct. |
| Outcome: | The proposed model improves on LegalBench across all model sizes, but no drop in MMLU. |