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Large, human-annotated datasets are central to the development of natural language processing models.
The Hungarian method for the assignment problem
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One billion word benchmark for measuring progress in statistical language modeling
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Rule-based information extraction is dead! Long live rule-based information extraction systems!
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Semantic parsing via paraphrasing
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Alignment-based compositional semantics for instruction following
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Neural machine translation by jointly learning to align and translate
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Wang, Y., Berant, J., and Liang, P · 2015
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Dbpal: A learned NL-interface for databases
Basik, F., Hattasch, B., Ilkhechi, A. R., Usta, A., Ramaswamy, S., Utama, P., Weir, N., Binnig, C., and Çetintemel, U · 2018
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Mapping navigation instructions to continuous control actions with position-visitation prediction
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BabyAI: A platform to study the sample efficiency of grounded language learning
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Reinforcement learning and control as probabilistic inference: Tutorial and review
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Towards adapting deep visuomotor representations from simulated to real environments
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Natural language processing for the long tail
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On Chomsky and the two cultures of statistical learning
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Domain randomization for transferring deep neural networks from simulation to the real world
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FiLM: Visual reasoning with a general conditioning layer
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Deep contextualized word representations
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Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond
Artetxe, M. and Schwenk, H · 2019
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Compositional semantic parsing across graphbanks
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A survey of reinforcement learning informed by natural language
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