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title: "Other — papers, page 22"
description: "Other: 743 papers of the Elamur Research library · page 22 of 30 — our summary of each, its ideas, references and who cites it."
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# 📦 Other

743 papers · page 22 of 30 · newest first · [all shelves](https://md.research.elamur.ai/free/en/shelves/)

Works whose topics fit none of the fields above yet.

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- [GLTR: Statistical Detection and Visualization of Generated Text](https://md.research.elamur.ai/free/en/papers/gehrmann-2019-gltr-statistical-detection-visualization-generated/) — Sebastian Gehrmann, Hendrik Strobelt, Alexander M. Rush · 2019
- [GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering](https://md.research.elamur.ai/free/en/papers/hudson-2019-gqa-new-dataset-real-world/) — Drew A. Hudson, Christopher D. Manning · 2019
- [Green AI](https://md.research.elamur.ai/free/en/papers/schwartz-2019-green-ai/) — Roy Schwartz, Jesse Dodge, Noah A. Smith, et al. · 2019
- [How to Fine-Tune BERT for Text Classification?](https://md.research.elamur.ai/free/en/papers/sun-2019-fine-tune-bert-text-classification/) — Chi Sun, Xipeng Qiu, Yige Xu, et al. · 2019
- [Identifying and Reducing Gender Bias in Word-Level Language Models](https://md.research.elamur.ai/free/en/papers/bordia-2019-identifying-reducing-gender-bias-word/) — Shikha Bordia, Samuel R. Bowman · 2019
- [Improved Knowledge Distillation via Teacher Assistant](https://md.research.elamur.ai/free/en/papers/mirzadeh-2019-improved-knowledge-distillation-teacher-assistant/) — Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, et al. · 2019
- [Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment](https://md.research.elamur.ai/free/en/papers/jin-2019-bert-really-robust-strong-baseline/) — Di Jin, Zhijing Jin, Joey Tianyi Zhou, et al. · 2019
- [K-BERT: Enabling Language Representation with Knowledge Graph](https://md.research.elamur.ai/free/en/papers/liu-2019-k-bert-enabling-language-representation/) — Weijie Liu, Peng Zhou, Zhe Zhao, et al. · 2019
- [LayoutLM: Pre-training of Text and Layout for Document Image Understanding](https://md.research.elamur.ai/free/en/papers/xu-2019-layoutlm-pre-training-text-layout/) — Yiheng Xu, Minghao Li, Lei Cui, et al. · 2019
- [Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering](https://md.research.elamur.ai/free/en/papers/asai-2019-learning-retrieve-reasoning-paths-over/) — Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, et al. · 2019
- [Leveraging Pre-trained Checkpoints for Sequence Generation Tasks](https://md.research.elamur.ai/free/en/papers/rothe-2019-leveraging-pre-trained-checkpoints-sequence/) — Sascha Rothe, Shashi Narayan, Aliaksei Severyn · 2019
- [LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech](https://md.research.elamur.ai/free/en/papers/zen-2019-libritts-corpus-derived-librispeech-text/) — Heiga Zen, Viet Dang, Rob Clark, et al. · 2019
- [MASS: Masked Sequence to Sequence Pre-training for Language Generation](https://md.research.elamur.ai/free/en/papers/song-2019-mass-masked-sequence-sequence-pre/) — Kaitao Song, Xu Tan, Tao Qin, et al. · 2019
- [Massively Multilingual Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/aharoni-2019-massively-multilingual-neural-machine-translation/) — Roee Aharoni, Melvin Johnson, Orhan Firat · 2019
- [MLQA: Evaluating Cross-lingual Extractive Question Answering](https://md.research.elamur.ai/free/en/papers/lewis-2019-mlqa-evaluating-cross-lingual-extractive/) — Patrick Lewis, Barlas Oğuz, Ruty Rinott, et al. · 2019
- [Momentum Contrast for Unsupervised Visual Representation Learning](https://md.research.elamur.ai/free/en/papers/he-2019-momentum-contrast-unsupervised-visual-representation/) — Kaiming He, Haoqi Fan, Yuxin Wu, et al. · 2019
- [Multilingual is not enough: BERT for Finnish](https://md.research.elamur.ai/free/en/papers/virtanen-2019-multilingual-enough-bert-finnish/) — Antti Virtanen, Jenna Kanerva, Rami Ilo, et al. · 2019
- [Neural Text Generation with Unlikelihood Training](https://md.research.elamur.ai/free/en/papers/welleck-2019-neural-text-generation-unlikelihood-training/) — Sean Welleck, Ilia Kulikov, Stephen Roller, et al. · 2019
- [oLMpics -- On what Language Model Pre-training Captures](https://md.research.elamur.ai/free/en/papers/talmor-2019-olmpics-language-model-pre-training/) — Alon Talmor, Yanai Elazar, Yoav Goldberg, et al. · 2019
- [Optuna: A Next-generation Hyperparameter Optimization Framework](https://md.research.elamur.ai/free/en/papers/akiba-2019-optuna-next-generation-hyperparameter-optimization/) — Takuya Akiba, Shotaro Sano, Toshihiko Yanase, et al. · 2019
- [Passage Re-ranking with BERT](https://md.research.elamur.ai/free/en/papers/nogueira-2019-passage-re-ranking-bert/) — Rodrigo Nogueira, Kyunghyun Cho · 2019
- [Patient Knowledge Distillation for BERT Model Compression](https://md.research.elamur.ai/free/en/papers/sun-2019-patient-knowledge-distillation-bert-model/) — Siqi Sun, Yu Cheng, Zhe Gan, et al. · 2019
- [Pay Less Attention with Lightweight and Dynamic Convolutions](https://md.research.elamur.ai/free/en/papers/wu-2019-pay-less-attention-lightweight-dynamic/) — Felix Wu, Angela Fan, Alexei Baevski, et al. · 2019
- [Plug and Play Language Models: A Simple Approach to Controlled Text Generation](https://md.research.elamur.ai/free/en/papers/dathathri-2019-plug-play-language-models-simple/) — Sumanth Dathathri, Andrea Madotto, Janice Lan, et al. · 2019
- [Publicly Available Clinical BERT Embeddings](https://md.research.elamur.ai/free/en/papers/alsentzer-2019-publicly-available-clinical-bert-embeddings/) — Emily Alsentzer, John R. Murphy, Willie Boag, et al. · 2019

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