Simple notes on papers about neural language learning from arxiv, ACL, EMNLP, NAACL, and some machine/deep learning from ICLR, ICML, NIPS. This note is inspired by Denny Britz's notes. There is also dataset for neural language research [link].

• [NAACL16], [ACL16], [EMNLP16], [NIPS16], [ICML16], [ICLR16] [DLSC16, note]
• [DeepMind], [GoogleBrain], [FAIR] [AI2], [MSR]
• [CMU] [Stanford] [Berkeley] [Montreal] [UW]

• LEARNING TO COMPOSE WORDS INTO SENTENCES WITH REINFORCEMENT LEARNING [arxiv]
• NEWSQA: A MACHINE COMPREHENSION DATASET [arxiv]
• Context-aware Natural Language Generation with Recurrent Neural Networks [arxiv]
• LEARNING FEATURES OF MUSIC FROM SCRATCH [arxiv data]
• Grammar Argumented LSTM Neural Networks with Note-Level Encoding for Music Composition [arxiv]
• PIXELVAE: A LATENT VARIABLE MODEL FOR NATURAL IMAGES [arxiv]
• VARIATIONAL LOSSY AUTOENCODER [arxiv]
• Generative Deep Neural Networks for Dialogue: A Short Review [arxiv]
• Variational Graph Auto-Encoders [arxiv]
• MODULAR MULTITASK REINFORCEMENT LEARNING WITH POLICY SKETCHES [arxiv]
• Neural Machine Translation with Reconstruction [arxiv]
• TOPICRNN: A RECURRENT NEURAL NETWORK WITH LONG-RANGE SEMANTIC DEPENDENCY [arxiv]
• REFERENCE-AWARE LANGUAGE MODELS [arxiv]
• A JOINT MANY-TASK MODEL: GROWING A NEURAL NETWORK FOR MULTIPLE NLP TASKS [arxiv]
• Ordinal Common-sense Inference [arxiv]
• Dual Learning for Machine Translation [arxiv]
• Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision [arxiv]
• What’s in an Explanation? Characterizing Knowledge and Inference Requirements for Elementary Science Exams [coling]

• Cross-Modal Scene Networks [arxiv]
• IMPROVING SAMPLING FROM GENERATIVE AUTOENCODERS WITH MARKOV CHAINS [[arxiv[(https://arxiv.org/pdf/1610.09296v2.pdf)]
• Towards a continuous modeling of natural language domains [arxiv]
• Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification [arxiv]
• Socratic Learning [arxiv]
• Professor Forcing: A New Algorithm for Training Recurrent Networks [arxiv]
• A Paradigm for Situated and Goal-Driven Language Learning [arxiv]
• A Theme-Rewriting Approach for Generating Algebra Word Problems [arxiv]
• Lexicons and Minimum Risk Training for Neural Machine Translation: NAIST-CMU at WAT2016 [arxiv]
• Equilibrium Propagation: Bridging the Gap Between Energy-Based Models and Backpropagation [arxiv]
• Cross-Sentence Inference for Process Knowledge [emnlp]
• Learning to Translate in Real-time with Neural Machine Translation [arxiv]
• Recurrent Neural Network Grammars [arxiv]
• Connecting Generative Adversarial Networks and Actor-Critic Methods [arxiv]
• Semantic Parsing with Semi-Supervised Sequential Autoencoders [arxiv]
• Grounding the Lexical Sets of Causative-Inchoative Verbs with Word Embedding [arxiv]
• Learning to Translate in Real-time with Neural Machine Translation [axiv]
• A Dataset and Evaluation Metrics for Abstractive Compression of Sentences and Short Paragraphs [axiv]

• SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient [arxiv]
• ReasoNet: Learning to Stop Reading in Machine Comprehension [arxiv]
• SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity [arxiv]
• NEURAL PHOTO EDITING WITH INTROSPECTIVE ADVERSARIAL NETWORKS [arxiv]
• Language as a Latent Variable: Discrete Generative Models for Sentence Compression [arxiv]
• Annotating Derivations: A New Evaluation Strategy and Dataset for Algebra Word Problems [arxiv]
• Unsupervised Neural Hidden Markov Models [arxiv]
• Creating Causal Embeddings for Question Answering with Minimal Supervision [axiv]
• Generating Videos with Scene Dynamics [arxiv]
• On the Similarities Between Native, Non-native and Translated Texts [arxiv]
• Energy-based Generative Adversarial Network [arxiv]
• Knowledge as a Teacher: Knowledge-Guided Structural Attention Networks [arxiv]
• Episodic Exploration for Deep Deterministic Policies: An Application to StarCraft Micromanagement Tasks [arxiv]
• WAVENET: A GENERATIVE MODEL FOR RAW AUDIO [arxiv]
• Multimodal Attention for Neural Machine Translation [arxiv]
• Neural Machine Translation with Supervised Attention [arxiv]
• Formalizing Neurath's Ship: Approximate Algorithms for Online Causal Learning [arxiv]
• Factored Neural Machine Translation [arxiv]
• Discrete Variational Autoencoders [arxiv]
• Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads [arxiv]
• lamtram: A toolkit for language and translation modeling using neural networks [github]
• C++ neural network library [github]
• End-to-End Reinforcement Learning of Dialogue Agents for Information Access [arxiv]
• Citation Classification for Behavioral Analysis of a Scientific Field [arxiv]
• Reward Augmented Maximum Likelihood for Neural Structured Prediction [arxiv]
• All Fingers are not Equal: Intensity of References in Scientific Articles [emnlp]
• WAVENET: A GENERATIVE MODEL FOR RAW AUDIO [paper blog]
• Hierarchical Multiscale Recurrent Neural Networks [arxiv]

• A Context-aware Natural Language Generator for Dialogue Systems [sigdial]
• Investigation Into The Effectiveness Of Long Short Term Memory Networks For Stock Price Prediction [axiv]
• HIERARCHICAL ATTENTION MODEL FOR IMPROVED MACHINE COMPREHENSION OF SPOKEN CONTENT [arxiv]
• Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks [arxiv code]
• Progressive Neural Networks [arxiv]
• Neural Variational Inference for Text Processing [arxiv]
• Generative Adversarial Text to Image Synthesis [arxiv code]
• Sequential Neural Models with Stochastic Layers [nips]
• Deep Learning without Poor Local Minima [nips]
• Actor-critic versus direct policy search: a comparison based on sample complexity [arxiv]
• Policy Networks with Two-Stage Training for Dialogue Systems [arxiv]
• Pointing the Unknown Words [acl]
• An Incremental Parser for Abstract Meaning Representation [arxiv]
• Topic Sensitive Neural Headline Generation [arxiv]
• Towards Machine Comprehension of Spoken Content: Initial TOEFL Listening Comprehension Test by Machine [interspeech]
• Face2Face: Real-time Face Capture and Reenactment of RGB Videos [demo]
• Image-Space Modal Bases for Plausible Manipulation of Objects in Video [demo]
• Decoupled neural interfaces using synthetic gradients [arxiv blog]
• Full Resolution Image Compression with Recurrent Neural Networks [arxiv]
• Who did What: A Large-Scale Person-Centered Cloze Dataset [arxiv data]
• Pixel Recurrent Neural Networks [arxiv]
• Mollifying Networks [arxiv]
• Variational Information Maximizing Exploration [arxiv]
• Does Multimodality Help Human and Machine for Translation and Image Captioning [arxiv]
• Learning values across many orders of magnitude [arxiv]
• Attend, Infer, Repeat: Fast Scene Understanding with Generative Models [[arxiv](Attend, Infer, Repeat: Fast Scene Understanding with Generative Models)]
• Architectural Complexity Measures of Recurrent Neural Network [arxiv]
• Neural Generation of Regular Expressions from Natural Language with Minimal Domain Knowledge [arxiv]
• Canonical Correlation Inference for Mapping Abstract Scenes to Text [arxiv]
• Temporal Attention Model for Neural Machine Translation [arxiv]
• Bi-directional Attention with Agreement for Dependency Parsing [arxiv]
• Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change [arxiv]
• Recurrent Highway Networks [arxiv]
• Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond [arxiv]
• WIKIREADING: A Novel Large-scale Language Understanding Task over Wikipedia [arxiv]
• Larger-Context Language Modelling with Recurrent Neural Network [acl16]
• Learning Online Alignments with Continuous Rewards Policy Gradient [arxiv]
• Issues in evaluating semantic spaces using word analogies [acl16]
• Curiosity-driven Exploration in Deep Reinforcement Learning via Bayesian Neural Networks [arxiv]
• Control of Memory, Active Perception, and Action in Minecraft [icml16]
• Dueling Network Architectures for Deep Reinforcement Learning [arxiv]
• Human-level control through deep reinforcement learning [nature]
• Reinforcement Learning in Multi-Party Trading Dialog [arxiv]
• Large-scale Simple Question Answering with Memory Network [arxiv]
• On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems [arxiv]
• A New Method to Visualize Deep Neural Networks [arxiv]
• Dreaming of names with RBMs [blog]
• Synthesizing Compound Words for Machine Translation [acl16]
• Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations [arxiv]
• Learning to Transduce with Unbounded Memory [arxiv]
• Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets [nip16]
• LEARNING LONGER MEMORY IN RECURRENT NEURAL NETWORKS [iclr15]
• Attention-based Multimodal Neural Machine Translation [acl16]
• A Two-stage Approach for Extending Event Detection to New Types via Neural Networks [acl16]
• Learning text representation using recurrent convolutional neural network with highway layers [arxiv]
• Training Very Deep Networks [arxiv]
• SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity [arxiv]
• Counter-fitting Word Vectors to Linguistic Constraints [naacl16]
• Learning Online Alignments with Continuous Rewards Policy Gradient [arxiv]
• NEURAL PROGRAMMER: INDUCING LATENT PROGRAMS WITH GRADIENT DESCENT [iclr16]
• Supervised Attentions for Neural Machine Translation [arxiv]
• A Neural Knowledge Language Model [arxiv]
• Recurrent Models of Visual Attention [cvpr]
• XGBoost: A Scalable Tree Boosting System [arxiv]
• A Corpus and Cloze Evaluation for Deeper Understanding of Commonsense Stories [naacl]
• Deep Learning Trends @ ICLR 2016 [blog]
• Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift [arxiv]
• VISUALIZING AND UNDERSTANDING RECURRENT NETWORKS [iclr]
• Net2Net: ACCELERATING LEARNING VIA KNOWLEDGE TRANSFER [iclr]
• A Latent Variable Recurrent Neural Network for Discourse Relation Language Models [arxiv]
• A Recurrent Latent Variable Model for Sequential Data [arxiv]
• ORDER-EMBEDDINGS OF IMAGES AND LANGUAGE [iclr]
• Neural Module Networks [arxiv]
• Learning to Compose Neural Networks for Question Answering [acl]
• Understanding and Improving Convolutional Neural Networks via Concatenated Rectified Linear Units [arxiv]

• Constructing a Natural Language Inference Dataset using Generative Neural Networks [arxiv]
• ADVERSARIAL EXAMPLES IN THE PHYSICAL WORLD [arxiv]
• An Actor-Critic Algorithm for Sequence Prediction [arxiv]
• Enriching Word Vectors with Subword Information [arxiv]
• each word is represented as a bag of character n-grams in skip-gram
• Neural Machine Translation with Recurrent Attention Modeling [arxiv]
• The Role of Discourse Units in Near-Extractive Summarization [arxiv]
• Bag of Tricks for Efficient Text Classification [arxiv]
• Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks [arxiv]
• Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes [arxiv]
• STransE: a novel embedding model of entities and relationships in knowledge bases [naacl16]
• Layer Normalization [arxiv]
• Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question Answering [arxiv]
• Imitation Learning with Recurrent Neural Networks [arxiv]
• Neural Name Translation Improves Neural Machine Translation [arxiv]
• query-regression networks for machine comprehension [arxiv]
• Bag of Tricks for Efficient Text Classification [arxiv]
• Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks [arxiv]
• Sort Story: Sorting Jumbled Images and Captions into Stories [arxiv]
• Separating Answers from Queries for Neural Reading Comprehension [arxiv]
• Recurrent Highway Networks [arxiv]
• Charagram: Embedding Words and Sentences via Character n-grams [arxiv]
• ADVERSARIAL EXAMPLES IN THE PHYSICAL WORLD [arxiv]
• Syntax-based Attention Model for Natural Language Inference [arxiv]
• Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge [arxiv]
• Layer Normalization [arxiv]
• Neural Sentence Ordering [arxiv code]
• Distilling Word Embeddings: An Encoding Approach [arxiv]
• Target-Side Context for Discriminative Models in Statistical Machine Translation [arxiv]
• Domain Adaptation for Neural Networks by Parameter Augmentation [arxiv]
• Towards Abstraction from Extraction: Multiple Timescale Gated Recurrent Unit for Summarization [arxiv]
• Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes [arxiv]
• Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question Answering [arxiv]
• Imitation Learning with Recurrent Neural Networks [arxiv]
• Attention-over-Attention Neural Networks for Reading Comprehension [arxiv]
• Neural Tree Indexers for Text Understanding [arxiv]
• Generating Images Part by Part with Composite Generative Adversarial Networks [arxiv]

• Neural Summarization by Extracting Sentences and Words [arxiv]
• Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks [arxiv]
• Sequence-Level Knowledge Distillation [arxiv]
• Text Understanding with the Attention Sum Reader Network [arxiv]
• Query-Regression Networks for Machine Comprehension [arxiv]
• A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation [arxiv]
• Smart Reply: Automated Response Suggestion for Email [arxiv]
• Minimum Risk Training for Neural Machine Translation [arxiv]
• Compression of Neural Machine Translation Models via Pruning [arxiv]
• Sort Story: Sorting Jumbled Images and Captions into Stories [arxiv]
• Dialog state tracking, a machine reading approach using a memory-enhanced neural network [arxiv]
• Predicting the Relative Difficulty of Single Sentences With and Without Surrounding Context [arxiv]
• Learning Generative ConvNet with Continuous Latent Factors by Alternating Back-Propagation [arxiv]
• Topic Augmented Neural Response Generation with a Joint Attention Mechanism [arxiv]
• STransE: a novel embedding model of entities and relationships in knowledge bases [arxiv]
• Functional Distributional Semantics [arxiv]
• Sequence-Level Knowledge Distillation [arxiv]
• The LAMBADA dataset: Word prediction requiring a broad discourse context [arxiv]
• DenseCap: Fully Convolutional Localization Networks for Dense Captioning [link]
• Visualizing Dynamics: from t-SNE to SEMI-MDPs [arxiv]
• Algorithmic Composition of Melodies with Deep Recurrent Neural Networks [arxiv]
• InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets [arxiv]
• Deep Reinforcement Learning for Dialogue Generation [arxiv]
• Key-Value Memory Networks for Directly Reading Documents [arxiv]
• A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation [arxiv]
• The Word Entropy of Natural Languages [arxiv]
• Semantic Parsing to Probabilistic Programs for Situated Question Answering [arxiv]
• Critical Behavior from Deep Dynamics: A Hidden Dimension in Natural Language [arxiv]
• Inferring Logical Forms From Denotations [arxiv]
• some notes from NAACL'16 Deep Learning panel discussion
• Jacob Eisenstein made an observation, "In NLP, the things we do well on are things where context doesn't matter."
• Rationalizing Neural Predictions [arxiv]
• DeepMath - Deep Sequence Models for Premise Selection [arxiv]
• A Fast Unified Model for Parsing and Sentence Understanding [arxiv]
• A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues [arxiv]
• Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation [arxiv]
• Sequence-to-Sequence Learning as Beam-Search Optimization [arxiv]
• Tables as Semi-structured Knowledge for Question Answering [arxiv]
• Ask Me Anything: Dynamic Memory Networks for Natural Language Processing [arxiv]
• Dynamic Memory Networks for Visual and Textual Question Answering [arxiv]
• http://homes.cs.washington.edu/~nasmith/papers/flanigan+dyer+smith+carbonell.naacl16.pdf [arxiv]
• Iterative Alternating Neural Attention for Machine Reading [arxiv]
• Vector-based Models of Semantic Composition [arxiv]
• Generating Natural Language Inference Chains [arxiv]
• Learning to Compose Neural Networks for Question Answering [arxiv]
• A Latent Variable Recurrent Neural Network for Discourse Relation Language Models [arxiv]
• Data Recombination for Neural Semantic Parsing [arxiv]
• Natural Language Generation in Dialogue using Lexicalized and Delexicalized Data [arxiv]
• Deep Reinforcement Learning with a Combinatorial Action Space for Predicting and Tracking Popular Discussion Threads [arxiv]
• InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets [arxiv]
• A Diversity-Promoting Objective Function for Neural Conversation Models [arxiv]
• Neural Associative Memory for Dual-Sequence Modeling [arxiv]
• Key-Value Memory Networks for Directly Reading Documents [arxiv]
• Simple Question Answering by Attentive Convolutional Neural Network [arxiv]
• Neural Network-Based Abstract Generation for Opinions and Arguments [arxiv]
• A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task [arxiv]
• Generating Natural Questions About an Image [arxiv]
• Continuously Learning Neural Dialogue Management [arxiv]
• A Persona-Based Neural Conversation Model [arxiv]
• Deep Reinforcement Learning for Dialogue Generation [arxiv]
• A Decomposable Attention Model for Natural Language Inference [arxiv]
• attention matrixs to decompose the problem into subproblems that can be solved separately
• Memory-enhanced Decoder for Neural Machine Translation [arxiv]
• Incorporating Discrete Translation Lexicons into Neural Machine [arxiv]
• Can neural machine translation do simultaneous translation? [arxiv]
• Language to Logical Form with Neural Attention [arxiv]
• Neural Summarization by Extracting Sentences and Words [arxiv]
• Generalizing and Hybridizing Count-based and Neural Language Models [arxiv]

• Variational Neural Machine Translation [arxiv]
• Deep Generative Models with Stick-Breaking Priors [arxiv]
• A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues [arxiv]
• One-shot Learning with Memory-Augmented Neural Networks [arxiv]
• Residual Networks are Exponential Ensembles of Relatively Shallow Networks [arxiv code]
• Modelling Interaction of Sentence Pair with coupled-LSTMs [arxiv]
• Functional Hashing for Compressing Neural Networks [arxiv]
• Combining Recurrent and Convolutional Neural Networks for Relation Classification [arxiv]
• Learning End-to-End Goal-Oriented Dialog [arxiv]
• Variational Neural Machine Translation [arxiv]
• BattRAE: Bidimensional Attention-Based Recursive Autoencoders for Learning Bilingual Phrase Embeddings [arxiv]
• Encode, Review, and Decode: Reviewer Module for Caption Generation [arxiv]
• Automatic Extraction of Causal Relations from Natural Language Texts: A Comprehensive Survey [arxiv]
• A Convolutional Attention Network for Extreme Summarization of Source Code [arxiv]
• Data recombination for neural semantic parsing.
• Inferring logical forms from denotations
• How much is 131 million dollars? putting numbers in perspective with compositional descriptions
• Learning to Generate with Memory [arxiv]
• Attention Correctness in Neural Image Captioning [arxiv]
• Contextual LSTM (CLSTM) models for Large scale NLP tasks [arxiv]
• Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations [arxiv]
• Generative Adversarial Text to Image Synthesis [arxiv]
• Query-Efficient Imitation Learning for End-to-End Autonomous Driving [arxiv]
• Hierarchical Memory Networks [arxiv]
• odelling Interaction of Sentence Pair with coupled-LSTMs [arsiv]
• Recurrent Neural Network for Text Classification with Multi-Task Learning [arxiv]
• Rationale-Augmented Convolutional Neural Networks for Text Classification [arxiv]
• Joint Event Extraction via Recurrent Neural Networks [paper]
• Noisy Parallel Approximate Decoding for Conditional Recurrent Language Model [paper]
• Natural Language Semantics and Computability [arxiv]
• Natural Language Inference by Tree-Based Convolution and Heuristic Matching [arxiv]
• Generating Sentences from a Continuous Space [arxiv]
• Vocabulary Manipulation for Neural Machine Translation [arxiv]
• Chained Predictions Using Convolutional Neural Networks [arxiv]
• Modeling Rich Contexts for Sentiment Classification with LSTM [arxiv]
• Incorporating Selectional Preferences in Multi-hop Relation Extraction [naacl16]
• Word Ordering Without Syntax [arxiv]
• Compositional Sentence Representation from Character within Large Context Text [arxiv]
• Abstractive Sentence Summarization with Attentive Recurrent Neural Networks [arxiv]
• Mixed Incremental Cross-Entropy REINFORCE ICLR 2016 [github]

• Towards Conceptual Compression [arxiv]]
• Teaching natural language to computers [arxiv]
• Attend, Infer, Repeat Fast Scene Understanding with Generative Models
• How NOT To Evaluate Your Dialogue System An Empirical Study of
• Revisiting Semi-Supervised Learning with Graph Embeddings
• Neural Summarization by Extracting Sentences and Words
• Learning-Based Single-Document Summarization with Compression and Anaphoricity Constraints
• LSTM-BASED DEEP LEARNING MODELS FOR NONFACTOID
• Generating Visual Explanations
• A Compositional Approach to Language Modeling [arxiv]
• Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems [arxiv]
• Building Machines That Learn and Think Like People [[arxiv](Building Machines That Learn and Think Like People)]
• A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Stories [arxiv]
• Revisiting Summarization Evaluation for Scientific Articles [arxiv]
• Reasoning About Pragmatics with Neural Listeners and Speakers [arxiv]
• Character-Level Question Answering with Attention [arxiv]
• Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks [arxiv]
• Recurrent Neural Network Grammars [arxiv]

• Neural Programmer: Inducing Latent Programs with Gradient Descent [arxiv]
• Adversarial Autoencoders
• Listen, Attend and Spell: A Neural Network for Large Vocabulary Conversational Speech Recognition
• Net2Net: Accelerating Learning via Knowledge Transfer
• Neural Programmer: Inducing Latent Programs with Gradient Descent
• A Neural Conversational Model
• Neural Language Correction with Character-Based Attention [arxiv]
• Modeling Relational Information in Question-Answer Pairs with Convolutional Neural Networks [arxiv]
• Building Machines That Learn and Think Like People [arxiv]
• LARGER-CONTEXT LANGUAGE MODELLING WITH RECURRENT NEURAL NETWORK [arxiv]
• A Diversity-Promoting Objective Function for Neural Conversation Model [arxiv]
• Hierarchical Attention Networks for Document Classification [arxiv]
• Visual Storytelling [arxiv]
• Using Sentence-Level LSTM Language Models for Script Inference [arxiv]
• ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs [arxiv]
• Character-Level Question Answering with Attention [arxiv]
• Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond [arxiv]
• Sentence Compression by Deletion with LSTMs [link]
• A Simple Way to Initialize Recurrent Networks of Rectified Linear Units [arxiv]
• DenseCap: Fully Convolutional Localization Networks for Dense Captioning [arxiv]
• Nonextensive information theoretical machine [arxiv]
• What we write about when we write about causality: Features of causal statements across large-scale social discourse [arxiv]
• Question Answering via Integer Programming over Semi-Structured Knowledge [arxiv]
• Dialog-based Language Learning [arxiv]
• Bridging LSTM Architecture and the Neural Dynamics during Reading [arxiv]
• Neural Generative Question Answering [arxiv]
• Recurrent Memory Networks for Language Modeling [arxiv]
• Colorful Image Colorization [paper] [code] [note]

• votes for papers (e.g., 👍)
• automatic crawler for citation and search counts (e.g., cite+51, tweets+42, search+523 ) like this