--- title: "Other — papers, page 21" description: "Other: 743 papers of the Elamur Research library · page 21 of 30 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/other/page/21/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/other/page/21/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Other](https://md.research.elamur.ai/free/en/shelves/other/) / page 21 # 📦 Other 743 papers · page 21 of 30 · newest first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) Works whose topics fit none of the fields above yet. [← prev](https://md.research.elamur.ai/free/en/shelves/other/page/20/) [1](https://md.research.elamur.ai/free/en/shelves/other/) … [20](https://md.research.elamur.ai/free/en/shelves/other/page/20/) **21** [22](https://md.research.elamur.ai/free/en/shelves/other/page/22/) … [30](https://md.research.elamur.ai/free/en/shelves/other/page/30/) [next →](https://md.research.elamur.ai/free/en/shelves/other/page/22/) - [ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering](https://md.research.elamur.ai/free/en/papers/yu-2019-activitynet-qa-dataset-understanding-complex/) — Zhou Yu, Dejing Xu, Jun Yu, et al. · 2019 - [ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks](https://md.research.elamur.ai/free/en/papers/shridhar-2019-alfred-benchmark-interpreting-grounded-instructions/) — Mohit Shridhar; Jesse Thomason; Daniel Gordon; Yonatan Bisk; Winson Han; Roozbeh Mottaghi; Luke Zettlemoyer;, Dieter Fox · 2019 - [Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned](https://md.research.elamur.ai/free/en/papers/voita-2019-analyzing-multi-head-self-attention/) — Elena Voita, David Talbot, Fedor Moiseev, et al. · 2019 - [Analyzing the Structure of Attention in a Transformer Language Model](https://md.research.elamur.ai/free/en/papers/vig-2019-analyzing-structure-attention-transformer-language/) — Jesse Vig, Yonatan Belinkov · 2019 - [Are Sixteen Heads Really Better than One?](https://md.research.elamur.ai/free/en/papers/michel-2019-sixteen-heads-really-better-than/) — Paul Michel, Omer Levy, Graham Neubig · 2019 - [Assessing BERT's Syntactic Abilities](https://md.research.elamur.ai/free/en/papers/goldberg-2019-assessing-bert-s-syntactic-abilities/) — Yoav Goldberg · 2019 - [Automatic Detection of Generated Text is Easiest when Humans are Fooled](https://md.research.elamur.ai/free/en/papers/ippolito-2019-automatic-detection-generated-text-easiest/) — Daphne Ippolito, Daniel Duckworth, Chris Callison-Burch, et al. · 2019 - [BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model](https://md.research.elamur.ai/free/en/papers/wang-2019-bert-has-mouth-must-speak/) — Alex Wang, Kyunghyun Cho · 2019 - [BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/xu-2019-bert-post-training-review-reading/) — Hu Xu, Bing Liu, Lei Shu, et al. · 2019 - [BERTje: A Dutch BERT Model](https://md.research.elamur.ai/free/en/papers/de-2019-vries-bertje-dutch-bert-model/) — Wietse de Vries, Andreas van Cranenburgh, Arianna Bisazza, et al. · 2019 - [Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT](https://md.research.elamur.ai/free/en/papers/wu-2019-beto-bentz-becas-surprising-cross/) — Shijie Wu, Mark Dredze · 2019 - [BioBERT: a pre-trained biomedical language representation model for biomedical text mining](https://md.research.elamur.ai/free/en/papers/lee-2019-biobert-pre-trained-biomedical-language/) — Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, et al. · 2019 - [ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission](https://md.research.elamur.ai/free/en/papers/huang-2019-clinicalbert-modeling-clinical-notes-predicting/) — Kexin Huang, Jaan Altosaar, Rajesh Ranganath · 2019 - [Common Voice: A Massively-Multilingual Speech Corpus](https://md.research.elamur.ai/free/en/papers/ardila-2019-common-voice-massively-multilingual-speech/) — Rosana Ardila, Megan Branson, Kelly Davis, et al. · 2019 - [Compressive Transformers for Long-Range Sequence Modelling](https://md.research.elamur.ai/free/en/papers/rae-2019-compressive-transformers-long-range-sequence/) — Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al. · 2019 - [Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology](https://md.research.elamur.ai/free/en/papers/zmigrod-2019-counterfactual-data-augmentation-mitigating-gender/) — Ran Zmigrod, Sabrina J. Mielke, Hanna Wallach, et al. · 2019 - [CTRL: A Conditional Transformer Language Model for Controllable Generation](https://md.research.elamur.ai/free/en/papers/keskar-2019-ctrl-conditional-transformer-language-model/) — Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, et al. · 2019 - [Defending Against Neural Fake News](https://md.research.elamur.ai/free/en/papers/zellers-2019-defending-against-neural-fake-news/) — Rowan Zellers, Ari Holtzman, Hannah Rashkin, et al. · 2019 - [DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation](https://md.research.elamur.ai/free/en/papers/zhang-2019-dialogpt-large-scale-generative-pre/) — Yizhe Zhang, Siqi Sun, Michel Galley, et al. · 2019 - [Discourse-Aware Neural Extractive Text Summarization](https://md.research.elamur.ai/free/en/papers/xu-2019-discourse-aware-neural-extractive-text/) — Jiacheng Xu, Zhe Gan, Yu Cheng, et al. · 2019 - [Encode, Tag, Realize: High-Precision Text Editing](https://md.research.elamur.ai/free/en/papers/malmi-2019-encode-tag-realize-high-precision/) — Eric Malmi, Sebastian Krause, Sascha Rothe, et al. · 2019 - [ERNIE: Enhanced Representation through Knowledge Integration](https://md.research.elamur.ai/free/en/papers/sun-2019-ernie-enhanced-representation-through-knowledge/) — Yu Sun, Shuohuan Wang, Yukun Li, et al. · 2019 - [Fast Graph Representation Learning with PyTorch Geometric](https://md.research.elamur.ai/free/en/papers/fey-2019-fast-graph-representation-learning-pytorch/) — Matthias Fey, Jan Eric Lenssen · 2019 - [FreeLB: Enhanced Adversarial Training for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/zhu-2019-freelb-enhanced-adversarial-training-natural/) — Chen Zhu, Yu Cheng, Zhe Gan, et al. · 2019 - [Generative Modeling by Estimating Gradients of the Data Distribution](https://md.research.elamur.ai/free/en/papers/song-2019-generative-modeling-estimating-gradients-data/) — Yang Song, Stefano Ermon · 2019 [← prev](https://md.research.elamur.ai/free/en/shelves/other/page/20/) [1](https://md.research.elamur.ai/free/en/shelves/other/) … [20](https://md.research.elamur.ai/free/en/shelves/other/page/20/) **21** [22](https://md.research.elamur.ai/free/en/shelves/other/page/22/) … [30](https://md.research.elamur.ai/free/en/shelves/other/page/30/) [next →](https://md.research.elamur.ai/free/en/shelves/other/page/22/)