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The AFRL IWSLT 2020 Systems: Work-From-Home Edition0
The AIP-Tohoku System at the BEA-2019 Shared Task0
The Alaskan Athabascan Grammar Database0
The Benefit of Pseudo-Reference Translations in Quality Estimation of MT Output0
The BioScope corpus: biomedical texts annotated for uncertainty, negation and their scopes0
``The Boating Store Had Its Best Sail Ever'': Pronunciation-attentive Contextualized Pun Recognition0
The BQ Corpus: A Large-scale Domain-specific Chinese Corpus For Sentence Semantic Equivalence Identification0
The BURCHAK corpus: a Challenge Data Set for Interactive Learning of Visually Grounded Word Meanings0
The Challenge of Composition in Distributional and Formal Semantics0
The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error0
The Color of the Cat is Gray: 1 Million Full-Sentences Visual Question Answering (FSVQA)0
The CUHK Discourse TreeBank for Chinese: Annotating Explicit Discourse Connectives for the Chinese TreeBank0
The Daunting Dilemma with Sentence Encoders: Success on Standard Benchmarks, Failure in Capturing Basic Semantic Properties0
The DeepMind Chinese–English Document Translation System at WMT20200
The DeepZen Speech Synthesis System for Blizzard Challenge 20230
The Dependency-Parsed FrameNet Corpus0
The design and implementation of Language Learning Chatbot with XAI using Ontology and Transfer Learning0
The Development of a Labelled te reo Māori-English Bilingual Database for Language Technology0
The Devil is in the Details: On the Pitfalls of Vocabulary Selection in Neural Machine Translation0
Scaling up Multi-domain Semantic Segmentation with Sentence Embeddings0
The Devil is in the Prompts: Retrieval-Augmented Prompt Optimization for Text-to-Video Generation0
The Distribution of Dependency Distance and Hierarchical Distance in Contemporary Written Japanese and Its Influencing Factors0
The distribution of information content in English sentences0
The DKU-DUKEECE System for the Manipulation Region Location Task of ADD 20230
The Dots Have Their Values: Exploiting the Node-Edge Connections in Graph-based Neural Models for Document-level Relation Extraction0
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