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Found 9 papers, 1 papers with code
Résumé Parsing as Hierarchical Sequence Labeling: An Empirical Study
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.
Learning Job Titles Similarity from Noisy Skill Labels
Measuring semantic similarity between job titles is an essential functionality for automatic job recommendations.
Reformulating Information Retrieval from Speech and Text as a Detection Problem
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.
Weakly Supervised Attentional Model for Low Resource Ad-hoc Cross-lingual Information Retrieval
We propose a weakly supervised neural model for Ad-hoc Cross-lingual Information Retrieval (CLIR) from low-resource languages.
Statistical Machine Translation Features with Multitask Tensor Networks
We present a three-pronged approach to improving Statistical Machine Translation (SMT), building on recent success in the application of neural networks to SMT.
