# 6

- [Universal Language Model Fine-tuning for Text Classification](/iamkissg/2018/6/ulmfit.md)
- [Semi-supervised sequence tagging with bidirectional language models](/iamkissg/2018/6/semi-supervised_seq_tagging_with_bilm.md)
- [Consensus Attention-based Neural Networks for Chinese Reading Comprehension](/iamkissg/2018/6/casreader.md)
- [Attention-over-Attention Neural Networks for Reading Comprehension](/iamkissg/2018/6/aoa_reader.md)
- [Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms](/iamkissg/2018/6/swem.md)
- [Convolutional Neural Networks for Sentence Classification](/iamkissg/2018/6/cnn_for_sentence_classification.md)
- [Deep contextualized word representations](/iamkissg/2018/6/elmo.md)
- [Neural Architectures for Named Entity Recognition](/iamkissg/2018/6/neural_architectures_for_ner.md)
- [Improving Language Understanding by Generative Pre-Training](/iamkissg/2018/6/improving_language_understanding_by_generative_pre-training.md)
- [A Sensitivity Analysis of (and Practitioners’ Guide to) Convolutional Neural Networks for Sentence C](/iamkissg/2018/6/a_sensitivity_analysis_of_cnn4sc.md)
- [Teaching Machines to Read and Comprehend](/iamkissg/2018/6/teaching_machines_to_read_and_comprehend.md)