学部3年 第一回:商品の属性値抽出タスクにおけるエラー分析 [ pdf][ slide] 第二回:Web 情報からの罹患検出を対象とした事実性解析・主体解析の誤り分析 [ pdf][ slide]
学部4年 第二回:意味集約における相対的特徴を考慮した評価視点の構造化 [ pdf][ slide] 第三回:Building_a_Monolingual_Parallel_Corpus_for_Text_Simplification_Using [ pdf][ slide] 第四回:An Analysis of Crowdsourced Text Simplifications [ pdf][ slide] 第五回:The Language Demographics of Amazon Mechanical Turk [ pdf][ slide] 第六回:What Substitutes Tell Us-Analysis of an “All-Words” Lexical Substitution Corpus [ pdf][ slide]
修士1年 第一回: Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging [pdf] [slide]第二回:End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF [pdf] [slide] 第三回:Understanding the Lexical Simplification Needs of Non-Native Speakers of English [ pdf] [ slide] 第四回:Dict2vec: Learning Word Embeddings using Lexical Dictionaries [pdf] [slide]第五回: Deep contextualized word representations [pdf] [slide]第六回:The Importance of Subword Embeddings in Sentence Pair Modeling [ pdf] [ slide] 第七回:Segmentation-Free Word Embedding for Unsegmented Languages ∗ [ pdf] [ slide] 第八回: When and Why are Pre-trained Word Embeddings Useful for Neural Machine Translation? [pdf] [slide]第九回:Intrinsic Evaluation of Word Vectors Fails to Predict Extrinsic Performance [pdf] [slide] 第十回:Split and Rephrase: Better Evaluation and a Stronger Baseline [pdf] [slide] 第十一回:How Transferable are Neural Networks in NLP Applications? [pdf] [slide] 第十二回:Phrase-level Self-Attention Networks for Universal Sentence Encoding [ pdf] [ slide] 第十三回:Named Entity Recognition With Parallel Recurrent Neural Networks [ pdf] [ slide] 第十四回: Unsupervised Statistical Machine Translation [pdf] [slide]第十五回:Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms [pdf] [slide] 第十六回: DSGAN: Generative Adversarial Training for Distant Supervision
Relation Extraction [pdf] [slide]第十七回:A robust self-learning method for
fully unsupervised cross-lingual mappings of word embeddings [pdf] [slide] 第十八回: Rotational Unit of Memory: A Novel Representation
Unit for RNNs with Scalable Applications [pdf] [slide]第十九回: Better Word Embeddings by Disentangling Contextual n-Gram Information [pdf] [slide]第二〇回:Improving Word Embeddings Using Kernel PCA [ pdf] [ slide] 第二一回:Character Eyes: Seeing Language through Character-Level Taggers [ pdf] [ slide] 第二二回: Retrofitting Contextualized Word Embeddings with Paraphrases [pdf] [slide]第二三回: Simple task-specific bilingual word embeddings [pdf] [slide]第二四回:Simple and Effective Paraphrastic Similarity from Parallel Translations [pdf] [slide] 第二五回: What does BERT learn about the structure of language? [pdf] [slide]
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