NLP Highlights
Ein Podcast von Allen Institute for Artificial Intelligence
145 Folgen
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84 - Large Teams Develop, Small Groups Disrupt, with Lingfei Wu
Vom: 26.3.2019 -
83 - Knowledge Base Construction, with Sebastian Riedel
Vom: 13.3.2019 -
82 - Visual Reasoning, with Yoav Artzi
Vom: 6.3.2019 -
81 - BlackboxNLP, with Afra Alishahi and Tal Linzen
Vom: 6.2.2019 -
80 - Leaderboards and Science, with Siva Reddy
Vom: 29.1.2019 -
79 - The glass ceiling in NLP, with Natalie Schluter
Vom: 21.1.2019 -
78. Where do corpora come from?, with Matt Honnibal and Ines Montani
Vom: 15.1.2019 -
77. On Writing Quality Peer Reviews, with Noah A. Smith
Vom: 7.1.2019 -
76 - Increasing In-Class Similarity by Retrofitting Embeddings with Demographics, with Dirk Hovy
Vom: 27.11.2018 -
75 - Reinforcement / Imitation Learning in NLP, with Hal Daumé III
Vom: 21.11.2018 -
74 - Deep Reinforcement Learning Doesn't Work Yet, with Alex Irpan
Vom: 16.11.2018 -
73 - Supersense Disambiguation of English Prepositions and Possessives, with Nathan Schneider
Vom: 13.11.2018 -
72 - The Anatomy Question Answering Task, with Jordan Boyd-Graber
Vom: 16.10.2018 -
71 - DuoRC: Complex Language Understanding with Paraphrased Reading Comprehension, with Amrita Saha
Vom: 12.10.2018 -
70 - Measuring the Evolution of a Scientific Field through Citation Frames, with David Jurgens
Vom: 18.9.2018 -
69 - Second language acquisition modeling, with Burr Settles
Vom: 10.9.2018 -
68 - Neural models of factuality, with Rachel Rudinger
Vom: 4.9.2018 -
67 - GLUE: A Multi-Task Benchmark and Analysis Platform, with Sam Bowman
Vom: 27.8.2018 -
66 - Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods, with Jieyu Zhao
Vom: 20.8.2018 -
65 - Event Representations with Tensor-based Compositions, with Niranjan Balasubramanian
Vom: 13.8.2018
**The podcast is currently on hiatus. For more active NLP content, check out the Holistic Intelligence Podcast linked below.** Welcome to the NLP highlights podcast, where we invite researchers to talk about their work in various areas in natural language processing. All views expressed belong to the hosts/guests, and do not represent their employers.