Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Zmigrod, Ran"'
Language models are capable of memorizing detailed patterns and information, leading to a double-edged effect: they achieve impressive modeling performance on downstream tasks with the stored knowledge but also raise significant privacy concerns. Tra
Externí odkaz:
http://arxiv.org/abs/2410.02912
Autor:
Zmigrod, Ran, Wang, Dongsheng, Sibue, Mathieu, Pei, Yulong, Babkin, Petr, Brugere, Ivan, Liu, Xiaomo, Navarro, Nacho, Papadimitriou, Antony, Watson, William, Ma, Zhiqiang, Nourbakhsh, Armineh, Shah, Sameena
The field of visually rich document understanding (VRDU) aims to solve a multitude of well-researched NLP tasks in a multi-modal domain. Several datasets exist for research on specific tasks of VRDU such as document classification (DC), key entity ex
Externí odkaz:
http://arxiv.org/abs/2404.04003
Migrations of systems from on-site premises to the cloud has been a fundamental endeavor by many industrial institutions. A crucial component of such cloud migrations is the transition of databases to be hosted online. In this work, we consider the d
Externí odkaz:
http://arxiv.org/abs/2403.08375
Log analysis and monitoring are essential aspects in software maintenance and identifying defects. In particular, the temporal nature and vast size of log data leads to an interesting and important research question: How can logs be summarised and mo
Externí odkaz:
http://arxiv.org/abs/2403.08358
Visually Rich Form Understanding (VRFU) poses a complex research problem due to the documents' highly structured nature and yet highly variable style and content. Current annotation schemes decompose form understanding and omit key hierarchical struc
Externí odkaz:
http://arxiv.org/abs/2402.05282
This paper provides a reference description, in the form of a deduction system, of Earley's (1970) context-free parsing algorithm with various speed-ups. Our presentation includes a known worst-case runtime improvement from Earley's $O (N^3|G||R|)$,
Externí odkaz:
http://arxiv.org/abs/2307.02982
Autor:
Batsuren, Khuyagbaatar, Goldman, Omer, Khalifa, Salam, Habash, Nizar, Kieraś, Witold, Bella, Gábor, Leonard, Brian, Nicolai, Garrett, Gorman, Kyle, Ate, Yustinus Ghanggo, Ryskina, Maria, Mielke, Sabrina J., Budianskaya, Elena, El-Khaissi, Charbel, Pimentel, Tiago, Gasser, Michael, Lane, William, Raj, Mohit, Coler, Matt, Samame, Jaime Rafael Montoya, Camaiteri, Delio Siticonatzi, Sagot, Benoît, Rojas, Esaú Zumaeta, Francis, Didier López, Oncevay, Arturo, Bautista, Juan López, Villegas, Gema Celeste Silva, Hennigen, Lucas Torroba, Ek, Adam, Guriel, David, Dirix, Peter, Bernardy, Jean-Philippe, Scherbakov, Andrey, Bayyr-ool, Aziyana, Anastasopoulos, Antonios, Zariquiey, Roberto, Sheifer, Karina, Ganieva, Sofya, Cruz, Hilaria, Karahóǧa, Ritván, Markantonatou, Stella, Pavlidis, George, Plugaryov, Matvey, Klyachko, Elena, Salehi, Ali, Angulo, Candy, Baxi, Jatayu, Krizhanovsky, Andrew, Krizhanovskaya, Natalia, Salesky, Elizabeth, Vania, Clara, Ivanova, Sardana, White, Jennifer, Maudslay, Rowan Hall, Valvoda, Josef, Zmigrod, Ran, Czarnowska, Paula, Nikkarinen, Irene, Salchak, Aelita, Bhatt, Brijesh, Straughn, Christopher, Liu, Zoey, Washington, Jonathan North, Pinter, Yuval, Ataman, Duygu, Wolinski, Marcin, Suhardijanto, Totok, Yablonskaya, Anna, Stoehr, Niklas, Dolatian, Hossep, Nuriah, Zahroh, Ratan, Shyam, Tyers, Francis M., Ponti, Edoardo M., Aiton, Grant, Arora, Aryaman, Hatcher, Richard J., Kumar, Ritesh, Young, Jeremiah, Rodionova, Daria, Yemelina, Anastasia, Andrushko, Taras, Marchenko, Igor, Mashkovtseva, Polina, Serova, Alexandra, Prud'hommeaux, Emily, Nepomniashchaya, Maria, Giunchiglia, Fausto, Chodroff, Eleanor, Hulden, Mans, Silfverberg, Miikka, McCarthy, Arya D., Yarowsky, David, Cotterell, Ryan, Tsarfaty, Reut, Vylomova, Ekaterina
The Universal Morphology (UniMorph) project is a collaborative effort providing broad-coverage instantiated normalized morphological inflection tables for hundreds of diverse world languages. The project comprises two major thrusts: a language-indepe
Externí odkaz:
http://arxiv.org/abs/2205.03608
Significance testing -- especially the paired-permutation test -- has played a vital role in developing NLP systems to provide confidence that the difference in performance between two systems (i.e., the test statistic) is not due to luck. However, p
Externí odkaz:
http://arxiv.org/abs/2205.01416
Probabilistic distributions over spanning trees in directed graphs are a fundamental model of dependency structure in natural language processing, syntactic dependency trees. In NLP, dependency trees often have an additional root constraint: only one
Externí odkaz:
http://arxiv.org/abs/2109.06521
The connection between the maximum spanning tree in a directed graph and the best dependency tree of a sentence has been exploited by the NLP community. However, for many dependency parsing schemes, an important detail of this approach is that the sp
Externí odkaz:
http://arxiv.org/abs/2106.00780