--- title: "Gabriel Stanovsky — papers and cards" description: "Gabriel Stanovsky: 6 paper cards in the Research library (2018–2026), with what each paper is about, the ideas Mova took from it, and the co-authors." canonical: "https://research.elamur.ai/free/en/authors/gabriel-stanovsky/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/gabriel-stanovsky/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Gabriel Stanovsky # Gabriel Stanovsky 6 paper cards in the Research library · 2018–2026 Gabriel Stanovsky wrote 6 of the papers Mova reads, in 2018–2026, most of them on [Semantic role labeling](https://md.research.elamur.ai/free/en/topics/semantic-role-labeling/), [Akkadian and cuneiform NLP](https://md.research.elamur.ai/free/en/topics/akkadian-cuneiform-nlp/); often with [Ido Dagan](https://md.research.elamur.ai/free/en/authors/ido-dagan/), [Julian Michael](https://md.research.elamur.ai/free/en/authors/julian-michael/), [Luke Zettlemoyer](https://md.research.elamur.ai/free/en/authors/luke-zettlemoyer/). [OpenAlex](https://openalex.org/A5082136238) · [ORCID](https://orcid.org/0000-0002-2420-8979) · [**h-index 21**](https://openalex.org/authors/A5082136238) · [2331 citations](https://openalex.org/authors/A5082136238) · [140 works](https://openalex.org/works?filter=author.id:A5082136238) — openalex-snapshot, 2026-10-14 The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Gabriel+Stanovsky) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Gabriel+Stanovsky) · [dblp](https://dblp.org/search?q=Gabriel+Stanovsky) · [ACL Anthology](https://aclanthology.org/search/?q=Gabriel+Stanovsky) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Gabriel+Stanovsky) Topics: [Semantic role labeling](https://md.research.elamur.ai/free/en/topics/semantic-role-labeling/) 2 · [Akkadian and cuneiform NLP](https://md.research.elamur.ai/free/en/topics/akkadian-cuneiform-nlp/) 1 ## Papers 1. **[Leveraging Digitized Newspapers to Collect Summarization Data in Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/aclbulk-2026-dahan-leveraging-digitized-newspapers-collect-summarization/)** *(2026)* Front-page teasers are short blurbs that a newspaper's editors write on the first page to point to full articles inside the issue. 2. **[Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach](https://md.research.elamur.ai/free/en/papers/emnlp-2021-lazar-filling-gaps-ancient-akkadian-texts/)** *(2021)* Editors of damaged cuneiform tablets fill broken parts from context, and the authors treat this as masked language modelling over Oracc transliterations (about 1M words, 2.3M signs). 3. **[Automated Extraction of Sentencing Decisions from Court Cases in the Hebrew Language](https://md.research.elamur.ai/free/en/papers/aclbulk-2021-wenger-automated-extraction-sentencing-decisions-court/)** *(2021)* The paper defines Automated Punishment Extraction (APE): from an Israeli court sentencing decision in a sexual-offence case, find the sentence that states the actual imprisonment and give its length in months. 4. **[Controlled Crowdsourcing for High-Quality QA-SRL Annotation](https://md.research.elamur.ai/free/en/papers/roit-2020-controlled-crowdsourcing-high-quality-qa/)** *(2020)* The paper shows that the crowdsourced QA-SRL data of 2018 has low coverage, with an estimated recall in the low 70s, and proposes a controlled protocol to fix it. 5. **[DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs](https://md.research.elamur.ai/free/en/papers/dua-2019-drop-reading-comprehension-benchmark-requiring/)** *(2019)* DROP has 96,567 questions on about 7,000 Wikipedia passages rich in numbers (American-football game summaries, history), written adversarially against a reading model so that answering needs discrete operations over several places in the text. 6. **[Crowdsourcing Question-Answer Meaning Representations](https://md.research.elamur.ai/free/en/papers/michael-2018-crowdsourcing-question-answer-meaning-representations/)** *(2018)* A QAMR represents a sentence's predicate-argument structure as a set of free-form wh-question / answer-span pairs about all its content words, not only verbs («How old is Pierre Vinken? – 61 years old», «What will he join the board as? – nonexecutive director»). ## Co-authors (25) - [Ido Dagan](https://md.research.elamur.ai/free/en/authors/ido-dagan/) ×2 - [Julian Michael](https://md.research.elamur.ai/free/en/authors/julian-michael/) ×2 - [Luke Zettlemoyer](https://md.research.elamur.ai/free/en/authors/luke-zettlemoyer/) ×2 - Asaf Yehudai - [Ayal Klein](https://md.research.elamur.ai/free/en/authors/ayal-klein/) - Benny Saret - Carmit Klar Chalamish - [Daniela Stepanov](https://md.research.elamur.ai/free/en/authors/daniela-stepanov/) - [Dheeru Dua](https://md.research.elamur.ai/free/en/authors/dheeru-dua/) - [Jonathan Mamou](https://md.research.elamur.ai/free/en/authors/jonathan-mamou/) - Koren Lazar - [Luheng He](https://md.research.elamur.ai/free/en/authors/luheng-he/) - [Matt Gardner](https://md.research.elamur.ai/free/en/authors/matt-gardner/) - Mohr Wenger - Nathan Wasserman - Noam Dahan - Noga Berger - Omer Kidron - Paul Roit - [Pradeep Dasigi](https://md.research.elamur.ai/free/en/authors/pradeep-dasigi/) - Renana Keydar - [Sameer Singh](https://md.research.elamur.ai/free/en/authors/sameer-singh/) - Tom Kalir - Wayne Horowitz - Yizhong Wang ## More papers in the library (5) Pages of the Research library: our summary, the ideas, references and who cites each. - [Collecting a Large-Scale Gender Bias Dataset for Coreference Resolution and Machine Translation](https://md.research.elamur.ai/free/en/papers/levy-2021-collecting-large-scale-gender-bias/) — Shahar Levy, Koren Lazar, Gabriel Stanovsky · 2021 - [Cross-document Coreference Resolution over Predicted Mentions](https://md.research.elamur.ai/free/en/papers/cattan-2021-cross-document-coreference-resolution-over/) — Arie Cattan, Alon Eirew, Gabriel Stanovsky, et al. · 2021 - [Realistic Evaluation Principles for Cross-document Coreference Resolution](https://md.research.elamur.ai/free/en/papers/cattan-2021-realistic-evaluation-principles-cross-document/) — Arie Cattan, Alon Eirew, Gabriel Stanovsky, et al. · 2021 - [Active Learning for Coreference Resolution using Discrete Annotation](https://md.research.elamur.ai/free/en/papers/li-2020-active-learning-coreference-resolution-discrete/) — Belinda Z. Li, Gabriel Stanovsky, Luke Zettlemoyer · 2020 - [Evaluating Gender Bias in Machine Translation](https://md.research.elamur.ai/free/en/papers/stanovsky-2019-evaluating-gender-bias-machine-translation/) — Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer · 2019