1 code implementation • 13 Sep 2023 • Federico Retyk, Hermenegildo Fabregat, Juan Aizpuru, Mariana Taglio, Rabih Zbib
Extracting information from r\'esum\'es is typically formulated as a two-stage problem, where the document is first segmented into sections and then each section is processed individually to extract the target entities.
no code implementations • 1 Jul 2022 • Rabih Zbib, Lucas Alvarez Lacasa, Federico Retyk, Rus Poves, Juan Aizpuru, Hermenegildo Fabregat, Vaidotas Simkus, Emilia García-Casademont
Measuring semantic similarity between job titles is an essential functionality for automatic job recommendations.
no code implementations • LREC 2020 • Damianos Karakos, Rabih Zbib, William Hartmann, Richard Schwartz, John Makhoul
In the IARPA MATERIAL program, information retrieval (IR) is treated as a hard detection problem; the system has to output a single global ranking over all queries, and apply a hard threshold on this global list to come up with all the hypothesized relevant documents.
no code implementations • WS 2019 • Lingjun Zhao, Rabih Zbib, Zhuolin Jiang, Damianos Karakos, Zhongqiang Huang
We propose a weakly supervised neural model for Ad-hoc Cross-lingual Information Retrieval (CLIR) from low-resource languages.
no code implementations • IJCNLP 2015 • Hendra Setiawan, Zhongqiang Huang, Jacob Devlin, Thomas Lamar, Rabih Zbib, Richard Schwartz, John Makhoul
We present a three-pronged approach to improving Statistical Machine Translation (SMT), building on recent success in the application of neural networks to SMT.