論文まとめ

論文まとめ
# この記事について
自分の研究に関連する論文のまとめ．あるいは学生とのシェア用．気まぐれに随時更新．

### 映像から言語
- Nguyen et al., (2017). "Translating Videos to Commands for Robotic Manipulation with Deep Recurrent Neural Networks." [[arXiv]](https://arxiv.org/abs/1710.00290)

### 言語とロボット動作の変換
##### 言語から動作
- Yamada et al., (2016/07). "Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human–Robot Interaction." [[Frontiers]](https://www.frontiersin.org/articles/10.3389/fnbot.2016.00005/full)

##### 動作から言語
- Heinrich and Wermter., (2014). "Interactive Language Understanding with Multiple Timescale Recurrent Neural Networks," *ICANN2017*, [[Springer]](https://link.springer.com/chapter/10.1007/978-3-319-11179-7_25)

##### 双方向変換
- Ogata et al., (2007). "Two-way translation of compound sentences and arm motions by recurrent neural networks," *IROS2007*. [[IEEEXplore]](http://ieeexplore.ieee.org/document/4399265/)
- Sugita and Tani., (2005). "Learning Semantic Combinatoriality from the Interaction between Linguistic and Behavioral Processes." [[SAGE]](http://journals.sagepub.com/doi/abs/10.1177/105971230501300102)

### Semantic Navigation
##### Vision-and-Language Navigation (VLN．画像と文章から)
- Das et al., (2017/12). "Embodied Question Answering." [[arXiv]](https://arxiv.org/abs/1711.11543)
- Anderson et al., (2017/11). "Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments." [[arXiv]](https://arxiv.org/abs/1711.07280)
- Hermann et al., (2017/06). "Grounded Language Learning in a Simulated 3D World." [[arXiv]](https://arxiv.org/abs/1706.06551)
- Chaplot et al., (2017/06). "Gated-Attention Architectures for Task-Oriented Language Grounding." [[arXiv]](https://arxiv.org/abs/1706.07230)

##### LRFによるSemantic Navigation
- Luo and Chen., (2017). "Recursive Neural Network Based Semantic Navigation of an Autonomous Mobile Robot through Understanding Human Verbal Instructions," *IROS2017,* No open-access file.


### 翻訳，主にneural machine translation (NMT)
- Lample et al., FAIR, (2017/11). "Unsupervised Machine Translation Using Monolingual Corpora Only." [[arXiv]](https://arxiv.org/abs/1711.00043)
- Johnson et al., Google, (2016/11). "Google's Multilingual Neural Machine Translation System : Enabling Zero-Shot Translation." [[arXiv]](https://arxiv.org/abs/1611.04558)
- Luong et al., Stanford Univ., (2015/08). "Effective Approaches to Attention-based Neural Machine Translation." [[arXiv]](https://arxiv.org/abs/1508.04025)
- Bahdanau et al., w/Bengio, (2014/09)."Neural Machine Translation by Jointly Learning to Align and Translate." [[arXiv]](https://arxiv.org/abs/1409.0473)

##### Attention関連の技術
- See et al., Stanford Univ. and Google, (2017/04). "Get To The Point: Summarization with Pointer-Generator Networks." [[arXiv]](https://arxiv.org/abs/1704.04368)
- Gu et al., (2016/03). "Incorporating Copying Mechanism in Sequence-to-Sequence Learning." [[arXiv]](https://arxiv.org/abs/1603.06393)
- Vinyals et al., Google Brain, (2015/06). "Pointer networks." [[arXiv]](https://arxiv.org/abs/1506.03134)

### 表現学習（Representation Learning)
- Tran et al., Open AI, (2017/12). "Feature-Matching Auto-Encoders." [[pdf]](http://bayesiandeeplearning.org/2017/papers/58.pdf)
 

### コミュニケーションによる記号創発
- Havrylov and Titov, (2017/05). "Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols." [[arXiv]](https://arxiv.org/abs/1705.11192)
- Mordatch and Abbeel, (2017/03). "Emergence of Grounded Compositional Language in Multi-Agent Populations." [[arXiv]](https://arxiv.org/abs/1703.04908)

### ニューラルネット，ディープラーニング基本テクニックやモデルあれこれ
- CapsNet初出．Sabour et al., (2017/11). "Dynamic Routing Between Capsules." [[arXiv]](https://arxiv.org/abs/1710.09829)
- Adam初出．Kingma and Ba, (2014/12). "Adam: A Method for Stochastic Optimization." [[arXiv]](https://arxiv.org/abs/1412.6980)
- VAE初出．Kingma and Welling, (2013/12). "Auto-Encoding Variational Bayes."
[[arXiv]](https://arxiv.org/abs/1312.6114)
- Elman型RNN. Elman, (1990). "Finding Structure in Time." [[ScienceDirect]](https://www.sciencedirect.com/science/article/pii/036402139090002E)
- BPTT初出．Rumelhart et al., (1986). "“Learning internal representations by error propagation." [[pdf]](http://www.cs.toronto.edu/~fritz/absps/pdp8.pdf)

### レビュー論文
- DLによる自然言語処理．Young et al., (2017/08). "Recent Trends in Deep Learning Based Natural Language Processing." [[arXiv]](https://arxiv.org/abs/1708.02709)
- DLによる音楽生成．Briot et al., (2017/09). "Deep Learning Techniques for Music Generation - A Survey." [[arXiv]](https://arxiv.org/abs/1709.01620)
- 記号創発ロボティクス．Taniguchi et al. (2015/09). "Symbol Emergence in Robotics: A Survey." [[arXiv]](https://arxiv.org/abs/1509.08973)

### 古典
- シンボルグラウンディング, Harnad, (1990/02). "The Symbol Grounding Problem." [[ScienceDirect]](http://www.sciencedirect.com/science/article/pii/0167278990900876)
- SHRDLU, Winograd, (1972/01). "Understanding natural language." [[ScienceDirect]](https://www.sciencedirect.com/science/article/pii/0010028572900023)