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Deep Learning
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Transformers
9294 directly classified papers
Papers per year
2011: 1
2014: 2
2015: 6
2016: 17
2017: 67
2018: 156
2019: 404
2020: 769
2021: 1217
2022: 1446
2023: 1628
2024: 1574
2025: 1647
2026: 360
Papers
Generating the Future With Adversarial Transformers
CVPR 2017
Visual Reference Resolution using Attention Memory for Visual Dialog
NIPS 2017
Semi-supervised sequence tagging with bidirectional language models
ACL 2017
Doubly-Attentive Decoder for Multi-modal Neural Machine Translation
ACL 2017
Diversity driven attention model for query-based abstractive summarization
ACL 2017
Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search
ACL 2017
Learning to Parse and Translate Improves Neural Machine Translation
ACL 2017
Pay Attention to the Ending:Strong Neural Baselines for the ROC Story Cloze Task
ACL 2017
Attention Strategies for Multi-Source Sequence-to-Sequence Learning
ACL 2017
Multi-Attention Network for One Shot Learning
CVPR 2017
Learning What’s Easy: Fully Differentiable Neural Easy-First Taggers
EMNLP 2017
Capturing User and Product Information for Document Level Sentiment Analysis with Deep Memory Network
EMNLP 2017
Hierarchically-Attentive RNN for Album Summarization and Storytelling
EMNLP 2017
Learning to Rank Semantic Coherence for Topic Segmentation
EMNLP 2017
Here’s My Point: Joint Pointer Architecture for Argument Mining
EMNLP 2017
Learning Hierarchical Information Flow with Recurrent Neural Modules
NIPS 2017
Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
NIPS 2017
Cortical microcircuits as gated-recurrent neural networks
NIPS 2017
Latent Attention For If-Then Program Synthesis
NIPS 2016
User Classification with Multiple Textual Perspectives
COLING 2016
Generating Natural Video Descriptions via Multimodal Processing
INTERSPEECH 2016
Generating Video Description using Sequence-to-sequence Model with Temporal Attention
COLING 2016
Incorporating Label Dependency for Answer Quality Tagging in Community Question Answering via CNN-LSTM-CRF
COLING 2016
AttSum: Joint Learning of Focusing and Summarization with Neural Attention
COLING 2016
Still not there? Comparing Traditional Sequence-to-Sequence Models to Encoder-Decoder Neural Networks on Monotone String Translation Tasks
COLING 2016
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