Search Results for author: Scott Miller

Found 10 papers, 0 papers with code

Language Model Priming for Cross-Lingual Event Extraction

no code implementations25 Sep 2021 Steven Fincke, Shantanu Agarwal, Scott Miller, Elizabeth Boschee

We show that by enabling the language model to better compensate for the deficits of sparse and noisy training data, our approach improves both trigger and argument detection and classification significantly over the state of the art in a zero-shot cross-lingual setting.

Event Extraction Language Modelling

SEARCHER: Shared Embedding Architecture for Effective Retrieval

no code implementations LREC 2020 Joel Barry, Elizabeth Boschee, Marjorie Freedman, Scott Miller

We describe an approach to cross lingual information retrieval that does not rely on explicit translation of either document or query terms.

Information Retrieval Translation

Cross-lingual Joint Entity and Word Embedding to Improve Entity Linking and Parallel Sentence Mining

no code implementations WS 2019 Xiaoman Pan, Thamme Gowda, Heng Ji, Jonathan May, Scott Miller

Because this multilingual common space directly relates the semantics of contextual words in the source language to that of entities in the target language, we leverage it for unsupervised cross-lingual entity linking.

Cross-Lingual Entity Linking Entity Linking

SARAL: A Low-Resource Cross-Lingual Domain-Focused Information Retrieval System for Effective Rapid Document Triage

no code implementations ACL 2019 Elizabeth Boschee, Joel Barry, Jayadev Billa, Marjorie Freedman, Thamme Gowda, Constantine Lignos, Chester Palen-Michel, Michael Pust, Banriskhem Kayang Khonglah, Srikanth Madikeri, Jonathan May, Scott Miller

In this paper we present an end-to-end cross-lingual information retrieval (CLIR) and summarization system for low-resource languages that 1) enables English speakers to search foreign language repositories of text and audio using English queries, 2) summarizes the retrieved documents in English with respect to a particular information need, and 3) provides complete transcriptions and translations as needed.

Information Retrieval Machine Translation +1

Use of Modality and Negation in Semantically-Informed Syntactic MT

no code implementations5 Feb 2015 Kathryn Baker, Michael Bloodgood, Bonnie J. Dorr, Chris Callison-Burch, Nathaniel W. Filardo, Christine Piatko, Lori Levin, Scott Miller

We apply our MN annotation scheme to statistical machine translation using a syntactic framework that supports the inclusion of semantic annotations.

Machine Translation Translation

Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach

no code implementations24 Sep 2014 Kathryn Baker, Michael Bloodgood, Chris Callison-Burch, Bonnie J. Dorr, Nathaniel W. Filardo, Lori Levin, Scott Miller, Christine Piatko

We describe a unified and coherent syntactic framework for supporting a semantically-informed syntactic approach to statistical machine translation.

Machine Translation Translation

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