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3Arxiv Sanity Preserver
http://www.arxiv-sanity.com/
2 years ago by @hotho
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2NLP's Clever Hans Moment has Arrived
https://thegradient.pub/nlps-clever-hans-moment-has-arrived/
3 years ago by @hotho
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1Bridging Relational and Deep Learning
https://people.cs.kuleuven.be/~sebastijan.dumancic/RelationalDeepLearning/index.html
4 years ago by @hotho
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1Using Provenance to Debug Training Data for Software 2.0 · Stanford DAWN
https://dawn.cs.stanford.edu//2018/06/21/debugging/
5 years ago by @hotho
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1Learning to Learn Concept Descriptions
https://dkm-static.fbk.eu/resources/phdthesis/GiulioPetrucci_PhD-Thesis.pdf
5 years ago by @hotho
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1Artificial intelligence is about to transform science journalism – here’s how to prepare for it. - Public Understanding of Science Blog
The rise of artificial intelligence has recently led to bots writing real news stories about sports, finance and politics. As yet, bots have not turned their attention to science, but the changes AI bots could unleash in science writing are remarkable.
5 years ago by @hotho
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1Gary King instrumental in developing new model for academic collaboration with industry | Harvard Institute for Quantitative Social Science
IQSS Director Gary King and Nate Persily of Stanford Law School have developed a new model for academic collaboration with industry.
5 years ago by @hotho
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1Activity Inequality
http://activityinequality.stanford.edu/
5 years ago by @hotho
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1The NarrativeQA Reading Comprehension Challenge – Arxiv Vanity
https://www.arxiv-vanity.com/papers/1712.07040v1/
5 years ago by @hotho
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2rasbt/python-machine-learning-book-2nd-edition: The "Python Machine Learning (2nd edition)" book code repository and info resource
python-machine-learning-book-2nd-edition - The "Python Machine Learning (2nd edition)" book code repository and info resource
6 years ago by @hotho
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1Reading List « Deep Learning
taught learni
7 years ago by @hotho
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4Deep Learning for NLP - NAACL 2013 Tutorial
Deep Learning for Natural Language Processing (without Magic)
7 years ago by @hotho
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1Paper über Vergleichbarkeit von 15$ PPD42NS mit "professioneller" Hardware · Issue #12 · opendata-stuttgart/meta · GitHub
https://github.com/opendata-stuttgart/meta/issues/12
7 years ago by @hotho
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1word2vec, LDA, and introducing a new hybrid algorithm: lda2vec
Available with notes: http://de.slideshare.net/ChristopherMoody3/word2vec-lda-and-introducing-a-new-hybrid-algorithm-lda2vec (Data Day 2016) Standard natural …
7 years ago by @hotho
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2GitHub - millecker/senti-storm: SentiStorm - Real-time Twitter Sentiment Classification based on Apache Storm
senti-storm - SentiStorm - Real-time Twitter Sentiment Classification based on Apache Storm
7 years ago by @hotho
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8The Unreasonable Effectiveness of Recurrent Neural Networks
http://karpathy.github.io/2015/05/21/rnn-effectiveness/
8 years ago by @hotho
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1What's in this paper? Combining Rhetorical Entities with Linked Open Data for Semantic Literature Querying - sateli-savesd2015.pdf
http://cs.unibo.it/save-sd/2015/papers/pdf/sateli-savesd2015.pdf
8 years ago by @hotho
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2RohitParimi2010.pdf
http://krex.k-state.edu/dspace/bitstream/handle/2097/4624/RohitParimi2010.pdf?sequence=5
10 years ago by @hotho
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9babelnet.org
babelnet, dictionary, ontology, lexicon, multilingual, multilinguality, wikipedia, wordnet, multilingual wordnet
10 years ago by @hotho
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2Geographical Analysis, Urban Modeling, Spatial Statisticss Präsentationen bei SlideShare
Präsentationen von Geographical Analysis, Urban Modeling, Spatial Statistics anschauen und herunterladen
10 years ago by @hotho
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1Tuning computer vision models with task rewards
A. Pinto, A. Kolesnikov, Y. Shi, L. Beyer, and X. Zhai. (2023)cite arxiv:2302.08242Comment: 11 pages.
3 months ago by @hotho
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1Training language models to follow instructions with human feedback
L. Ouyang, J. Wu, X. Jiang, D. Almeida, C. Wainwright, P. Mishkin, C. Zhang, S. Agarwal, K. Slama, A. Ray, J. Schulman, J. Hilton, F. Kelton, L. Miller, M. Simens, A. Askell, P. Welinder, P. Christiano, J. Leike, and R. Lowe. (2022)cite arxiv:2203.02155.
3 months ago by @hotho
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4Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers
L. Wu, S. Li, C. Hsieh, and J. Sharpnack. (2019)cite arxiv:1905.10630Comment: Accepted to 2019 Conference on Neural Information Processing Systems.
3 years ago by @hotho
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3K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters
R. Wang, D. Tang, N. Duan, Z. Wei, X. Huang, J. ji, G. Cao, D. Jiang, and M. Zhou. (2020)cite arxiv:2002.01808.
3 years ago by @hotho
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2Inducing Relational Knowledge from BERT.
Z. Bouraoui, J. Camacho-Collados, and S. Schockaert. CoRR (2019)
3 years ago by @hotho
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3Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games
A. Adhikari, X. Yuan, M. Côté, M. Zelinka, M. Rondeau, R. Laroche, P. Poupart, J. Tang, A. Trischler, and W. Hamilton. (2020)cite arxiv:2002.09127.
3 years ago by @hotho
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2Learning Robotic Manipulation through Visual Planning and Acting
A. Wang, T. Kurutach, K. Liu, P. Abbeel, and A. Tamar. (2019)cite arxiv:1905.04411Comment: RSS 2019. Website at https://sites.google.com/berkeley.edu/vpa/home.
4 years ago by @hotho
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4Do Massively Pretrained Language Models Make Better Storytellers?
A. See, A. Pappu, R. Saxena, A. Yerukola, and C. Manning. (2019)cite arxiv:1909.10705Comment: Accepted to CoNLL 2019.
4 years ago by @hotho
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1Deep Reinforcement Learning That Matters
P. Henderson, R. Islam, P. Bachman, J. Pineau, D. Precup, and D. Meger. (2018, 2017)
4 years ago by @hotho
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1Social reference managers and their users: A survey of demographics and ideologies
P. Chen, E. Hayes, V. Larivière, and C. Sugimoto. PLOS ONE 13 (7): 1-22 (July 2018)
4 years ago by @hotho
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1Music Transformer
C. Huang, A. Vaswani, J. Uszkoreit, N. Shazeer, I. Simon, C. Hawthorne, A. Dai, M. Hoffman, M. Dinculescu, and D. Eck. (2018)cite arxiv:1809.04281Comment: Improved skewing section and accompanying figures. Previous titles are Än Improved Relative Self-Attention Mechanism for Transformer with Application to Music Generation" and "Music Transformer".
4 years ago by @hotho
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4Benchmark of Deep Learning Models on Large Healthcare MIMIC Datasets
S. Purushotham, C. Meng, Z. Che, and Y. Liu. (2017)cite arxiv:1710.08531Comment: Submitted to Journal of Biomedical Informatics (JBI). First two authors have equal contributions.
4 years ago by @hotho
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3Monitoring of swarming sounds in bee hives for early detection of the swarming period
S. Ferrari, M. Silva, M. Guarino, and D. Berckmans. Computers and Electronics in Agriculture 64 (1): 72 - 77 (2008)Smart Sensors in precision livestock farming.
4 years ago by @hotho
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2Authorship Verification based on Compression-Models
O. Halvani, C. Winter, and L. Graner. (2017)cite arxiv:1706.00516.
4 years ago by @hotho
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6Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters
E. Kim, and R. Klinger. (2019)cite arxiv:1903.12453Comment: Accepted for publication at NAACL 2019.
4 years ago by @hotho
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3Analogies Explained: Towards Understanding Word Embeddings
C. Allen, and T. Hospedales. (2019)cite arxiv:1901.09813.
4 years ago by @hotho
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3A Survey on Sentiment and Emotion Analysis for Computational Literary Studies
E. Kim, and R. Klinger. (2018)cite arxiv:1808.03137Comment: Submitted for review to DHQ (http://www.digitalhumanities.org/dhq/).
4 years ago by @hotho
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3Representing Meaning with a Combination of Logical and Distributional Models.
I. Beltagy, S. Roller, P. Cheng, K. Erk, and R. Mooney. Computational Linguistics 42 (4): 763-808 (2016)
5 years ago by @hotho
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1The Odyssey’s mythological network
P. Miranda, M. Baptista, and S. de Souza Pinto. PLOS ONE 13 (7): 1-22 (July 2018)
5 years ago by @hotho
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5The Natural Language Decathlon: Multitask Learning as Question Answering
B. McCann, N. Keskar, C. Xiong, and R. Socher. (2018)cite arxiv:1806.08730.
5 years ago by @hotho
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