yuz9yuz/NLPImpact huggingface dataset:
Title: Multi-Modal Representations for Improved Bilingual Lexicon Learning
Venue: ACL (2016)
Topic: information retrieval and text mining
Title: Is This Post Persuasive? Ranking Argumentative Comments in Online Forum
Venue: ACL (2016)
Topic: sentiment analysis, stylistic analysis, and argument mining
Title: The Value of Semantic Parse Labeling for Knowledge Base Question Answering
Venue: ACL (2016)
Topic: question answering
Title: Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification
Venue: ACL (2016)
Topic: machine learning for nlp
Title: The red one!: On learning to refer to things based on discriminative properties
Venue: ACL (2016)
Topic: interpretability and analysis of models for nlp
Title: Don’t Count, Predict! An Automatic Approach to Learning Sentiment Lexicons for Short Text
Venue: ACL (2016)
Topic: sentiment analysis, stylistic analysis, and argument mining
Title: Dimensional Sentiment Analysis Using a Regional CNN-LSTM Model
Venue: ACL (2016)
Topic: sentiment analysis, stylistic analysis, and argument mining
Title: Deep multi-task learning with low level tasks supervised at lower layers
Venue: ACL (2016)
Topic: machine learning for nlp
Title: Domain Specific Named Entity Recognition Referring to the Real World by Deep Neural Networks
Venue: ACL (2016)
Topic: information extraction
Title: An Entity-Focused Approach to Generating Company Descriptions
Venue: ACL (2016)
Topic: nlp applications
Title: Annotating Relation Inference in Context via Question Answering
Venue: ACL (2016)
Topic: question answering
Title: Automatic Semantic Classification of German Preposition Types: Comparing Hard and Soft Clustering Approaches across Features
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: Natural Language Generation enhances human decision-making with uncertain information
Venue: ACL (2016)
Topic: resources and evaluation
Title: Tweet2Vec: Character-Based Distributed Representations for Social Media
Venue: ACL (2016)
Topic: computational social science and cultural analytics
Title: Phrase-Level Combination of SMT and TM Using Constrained Word Lattice
Venue: ACL (2016)
Topic: machine learning for nlp
Title: A Neural Network based Approach to Automatic Post-Editing
Venue: ACL (2016)
Topic: nlp applications
Title: An Unsupervised Method for Automatic Translation Memory Cleaning
Venue: ACL (2016)
Topic: machine translation
Title: Exponentially Decaying Bag-of-Words Input Features for Feed-Forward Neural Network in Statistical Machine Translation
Venue: ACL (2016)
Topic: machine translation
Title: Syntactically Guided Neural Machine Translation
Venue: ACL (2016)
Topic: machine translation
Title: Very quaffable and great fun: Applying NLP to wine reviews
Venue: ACL (2016)
Topic: resources and evaluation
Title: Exploring Stylistic Variation with Age and Income on Twitter
Venue: ACL (2016)
Topic: computational social science and cultural analytics
Title: Finding Optimists and Pessimists on Twitter
Venue: ACL (2016)
Topic: resources and evaluation
Title: Transductive Adaptation of Black Box Predictions
Venue: ACL (2016)
Topic: interpretability and analysis of models for nlp
Title: Which Tumblr Post Should I Read Next?
Venue: ACL (2016)
Topic: nlp applications
Title: Text Simplification as Tree Labeling
Venue: ACL (2016)
Topic: generation
Title: Bootstrapped Text-level Named Entity Recognition for Literature
Venue: ACL (2016)
Topic: information extraction
Title: The Enemy in Your Own Camp: How Well Can We Detect Statistically-Generated Fake Reviews – An Adversarial Study
Venue: ACL (2016)
Topic: ethics, bias, and fairness
Title: Character-based Neural Machine Translation
Venue: ACL (2016)
Topic: machine translation
Title: Learning Monolingual Compositional Representations via Bilingual Supervision
Venue: ACL (2016)
Topic: multilinguality and language diversity
Title: Event Nugget Detection with Forward-Backward Recurrent Neural Networks
Venue: ACL (2016)
Topic: information extraction
Title: IBC-C: A Dataset for Armed Conflict Analysis
Venue: ACL (2016)
Topic: resources and evaluation
Title: A Latent Concept Topic Model for Robust Topic Inference Using Word Embeddings
Venue: ACL (2016)
Topic: information retrieval and text mining
Title: Word Embeddings with Limited Memory
Venue: ACL (2016)
Topic: interpretability and analysis of models for nlp
Title: Hawkes Processes for Continuous Time Sequence Classification: an Application to Rumour Stance Classification in Twitter
Venue: ACL (2016)
Topic: computational social science and cultural analytics
Title: Hunting for Troll Comments in News Community Forums
Venue: ACL (2016)
Topic: resources and evaluation
Title: Phrase Table Pruning via Submodular Function Maximization
Venue: ACL (2016)
Topic: low-resource methods for nlp
Title: Multilingual Part-of-Speech Tagging with Bidirectional Long Short-Term Memory Models and Auxiliary Loss
Venue: ACL (2016)
Topic: syntax: tagging, chunking and parsing
Title: Matrix Factorization using Window Sampling and Negative Sampling for Improved Word Representations
Venue: ACL (2016)
Topic: information retrieval and text mining
Title: One model, two languages: training bilingual parsers with harmonized treebanks
Venue: ACL (2016)
Topic: multilinguality and language diversity
Title: Using mention accessibility to improve coreference resolution
Venue: ACL (2016)
Topic: discourse and pragmatics
Title: Exploiting Linguistic Features for Sentence Completion
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: Convergence of Syntactic Complexity in Conversation
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: User Embedding for Scholarly Microblog Recommendation
Venue: ACL (2016)
Topic: machine learning for nlp
Title: Integrating Distributional Lexical Contrast into Word Embeddings for Antonym-Synonym Distinction
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: Machine Translation Evaluation Meets Community Question Answering
Venue: ACL (2016)
Topic: machine translation
Title: Science Question Answering using Instructional Materials
Venue: ACL (2016)
Topic: question answering
Title: Specifying and Annotating Reduced Argument Span Via QA-SRL
Venue: ACL (2016)
Topic: sentiment analysis, stylistic analysis, and argument mining
Title: Improving Argument Overlap for Proposition-Based Summarisation
Venue: ACL (2016)
Topic: summarization
Title: Machine Comprehension using Rich Semantic Representations
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: Cross-Lingual Word Representations via Spectral Graph Embeddings
Venue: ACL (2016)
Topic: multilinguality and language diversity
Title: Semantics-Driven Recognition of Collocations Using Word Embeddings
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: Incorporating Relational Knowledge into Word Representations using Subspace Regularization
Venue: ACL (2016)
Topic: interpretability and analysis of models for nlp
Title: Word Embedding Calculus in Meaningful Ultradense Subspaces
Venue: ACL (2016)
Topic: low-resource methods for nlp
Title: Is “Universal Syntax” Universally Useful for Learning Distributed Word Representations?
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: Claim Synthesis via Predicate Recycling
Venue: ACL (2016)
Topic: generation
Title: Modelling the Interpretation of Discourse Connectives by Bayesian Pragmatics
Venue: ACL (2016)
Topic: linguistic theories, cognitive modeling and psycholinguistics
Title: Nonparametric Spherical Topic Modeling with Word Embeddings
Venue: ACL (2016)
Topic: machine learning for nlp
Title: A Novel Measure for Coherence in Statistical Topic Models
Venue: ACL (2016)
Topic: interpretability and analysis of models for nlp
Title: Coarse-grained Argumentation Features for Scoring Persuasive Essays
Venue: ACL (2016)
Topic: sentiment analysis, stylistic analysis, and argument mining
Title: Single-Model Encoder-Decoder with Explicit Morphological Representation for Reinflection
Venue: ACL (2016)
Topic: generation
Title: Joint part-of-speech and dependency projection from multiple sources
Venue: ACL (2016)
Topic: speech processing and spoken language understanding
Title: Dependency-based Gated Recursive Neural Network for Chinese Word Segmentation
Venue: ACL (2016)
Topic: syntax: tagging, chunking and parsing
Title: Deep Neural Networks for Syntactic Parsing of Morphologically Rich Languages
Venue: ACL (2016)
Topic: syntax: tagging, chunking and parsing
Title: Weakly Supervised Part-of-speech Tagging Using Eye-tracking Data
Venue: ACL (2016)
Topic: syntax: tagging, chunking and parsing
Title: Metrics for Evaluation of Word-level Machine Translation Quality Estimation
Venue: ACL (2016)
Topic: machine translation
Title: The Social Impact of Natural Language Processing
Venue: ACL (2016)
Topic: computational social science and cultural analytics
Title: Using Sequence Similarity Networks to Identify Partial Cognates in Multilingual Wordlists
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: Controlled and Balanced Dataset for Japanese Lexical Simplification
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: Dependency Forest based Word Alignment
Venue: ACL (2016)
Topic: syntax: tagging, chunking and parsing
Title: Identifying Potential Adverse Drug Events in Tweets Using Bootstrapped Lexicons
Venue: ACL (2016)
Topic: computational social science and cultural analytics
Title: Generating Natural Language Descriptions for Semantic Representations of Human Brain Activity
Venue: ACL (2016)
Topic: linguistic theories, cognitive modeling and psycholinguistics
Title: Improving Twitter Community Detection through Contextual Sentiment Analysis
Venue: ACL (2016)
Topic: computational social science and cultural analytics
Title: Significance of an Accurate Sandhi-Splitter in Shallow Parsing of Dravidian Languages
Venue: ACL (2016)
Topic: syntax: tagging, chunking and parsing
Title: Improving Topic Model Clustering of Newspaper Comments for Summarisation
Venue: ACL (2016)
Topic: summarization
Title: Arabizi Identification in Twitter Data
Venue: ACL (2016)
Topic: resources and evaluation
Title: Robust Co-occurrence Quantification for Lexical Distributional Semantics
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: Singleton Detection using Word Embeddings and Neural Networks
Venue: ACL (2016)
Topic: interpretability and analysis of models for nlp
Title: A Dataset for Joint Noun-Noun Compound Bracketing and Interpretation
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: An Investigation on The Effectiveness of Employing Topic Modeling Techniques to Provide Topic Awareness For Conversational Agents
Venue: ACL (2016)
Topic: dialogue and interactive systems
Title: Improving Dependency Parsing Using Sentence Clause Charts
Venue: ACL (2016)
Topic: syntax: tagging, chunking and parsing
Title: Graph- and surface-level sentence chunking
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: From Extractive to Abstractive Summarization: A Journey
Venue: ACL (2016)
Topic: summarization
Title: Putting Sarcasm Detection into Context: The Effects of Class Imbalance and Manual Labelling on Supervised Machine Classification of Twitter Conversations
Venue: ACL (2016)
Topic: computational social science and cultural analytics
Title: Unsupervised Authorial Clustering Based on Syntactic Structure
Venue: ACL (2016)
Topic: phonology, morphology, and word segmentation
Title: Suggestion Mining from Opinionated Text
Venue: ACL (2016)
Topic: generation
Title: An Efficient Cross-lingual Model for Sentence Classification Using Convolutional Neural Network
Venue: ACL (2016)
Topic: low-resource methods for nlp
Title: QA-It: Classifying Non-Referential It for Question Answer Pairs
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: Building a Corpus for Japanese Wikification with Fine-Grained Entity Classes
Venue: ACL (2016)
Topic: resources and evaluation
Title: A Personalized Markov Clustering and Deep Learning Approach for Arabic Text Categorization
Venue: ACL (2016)
Topic: low-resource methods for nlp
Title: POLYGLOT: Multilingual Semantic Role Labeling with Unified Labels
Venue: ACL (2016)
Topic: multilinguality and language diversity
Title: Online Information Retrieval for Language Learning
Venue: ACL (2016)
Topic: information retrieval and text mining
Title: Terminology Extraction with Term Variant Detection
Venue: ACL (2016)
Topic: information extraction
Title: DeepLife: An Entity-aware Search, Analytics and Exploration Platform for Health and Life Sciences
Venue: ACL (2016)
Topic: nlp applications
Title: Visualizing and Curating Knowledge Graphs over Time and Space
Venue: ACL (2016)
Topic: resources and evaluation
Title: A Web-framework for ODIN Annotation
Venue: ACL (2016)
Topic: nlp applications
Title: Real-Time Discovery and Geospatial Visualization of Mobility and Industry Events from Large-Scale, Heterogeneous Data Streams
Venue: ACL (2016)
Topic: information extraction
Title: TranscRater: a Tool for Automatic Speech Recognition Quality Estimation
Venue: ACL (2016)
Topic: speech processing and spoken language understanding
Title: TMop: a Tool for Unsupervised Translation Memory Cleaning
Venue: ACL (2016)
Topic: machine translation
Title: MMFeat: A Toolkit for Extracting Multi-Modal Features
Venue: ACL (2016)
Topic: language modeling
Title: JEDI: Joint Entity and Relation Detection using Type Inference
Venue: ACL (2016)
Topic: information extraction
Title: OpenDial: A Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules
Venue: ACL (2016)
Topic: speech processing and spoken language understanding
Title: MUSEEC: A Multilingual Text Summarization Tool
Venue: ACL (2016)
Topic: multilinguality and language diversity
Title: Language Muse: Automated Linguistic Activity Generation for English Language Learners
Venue: ACL (2016)
Topic: multilinguality and language diversity
Title: ccg2lambda: A Compositional Semantics System
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Title: MeTA: A Unified Toolkit for Text Retrieval and Analysis
Venue: ACL (2016)
Topic: information retrieval and text mining
Title: MDSWriter: Annotation Tool for Creating High-Quality Multi-Document Summarization Corpora
Venue: ACL (2016)
Topic: summarization
Title: Jigg: A Framework for an Easy Natural Language Processing Pipeline
Venue: ACL (2016)
Topic: resources and evaluation
Title: An Advanced Press Review System Combining Deep News Analysis and Machine Learning Algorithms
Venue: ACL (2016)
Topic: summarization
Title: Personalized Exercises for Preposition Learning
Venue: ACL (2016)
Topic: generation
Title: My Science Tutor—Learning Science with a Conversational Virtual Tutor
Venue: ACL (2016)
Topic: dialogue and interactive systems
Title: pigeo: A Python Geotagging Tool
Venue: ACL (2016)
Topic: resources and evaluation
Title: Creating Interactive Macaronic Interfaces for Language Learning
Venue: ACL (2016)
Topic: nlp applications
Title: Roleo: Visualising Thematic Fit Spaces on the Web
Venue: ACL (2016)
Topic: resources and evaluation
Title: MediaGist: A Cross-lingual Analyser of Aggregated News and Commentaries
Venue: ACL (2016)
Topic: computational social science and cultural analytics
Title: GoWvis: A Web Application for Graph-of-Words-based Text Visualization and Summarization
Venue: ACL (2016)
Topic: nlp applications
Title: LiMoSINe Pipeline: Multilingual UIMA-based NLP Platform
Venue: ACL (2016)
Topic: multilinguality and language diversity
Title: new/s/leak – Information Extraction and Visualization for Investigative Data Journalists
Venue: ACL (2016)
Topic: resources and evaluation
Title: Semantic Representations of Word Senses and Concepts
Venue: ACL (2016)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Abstract: Representing the semantics of linguistic items in a machine ­interpretable form has been a major goal of Natural Language Processing since its earliest days. Among the range of different linguistic items, words have attracted the most research attention. However, word representations have an important limitation: they conflate different meanings of a word into a single vector. Representations of word senses have the potential to overcome this inherent limitation. Indeed, the representation of individual word senses and concepts has recently gained in popularity with several experimental results showing that a considerable performance improvement can be achieved across different NLP applications upon moving from word level to the deeper sense and concept levels. Another interesting point regarding the representation of concepts and word senses is that these models can be seamlessly applied to other linguistic items, such as words, phrases, sentences, etc.

This tutorial will first provide a brief overview of the recent literature concerning word representation (both count based and neural network based). It will then describe the advantages of moving from the word level to the deeper level of word senses and concepts, providing an extensive review of state ­of ­the ­art systems. Approaches covered will not only include those which draw upon knowledge resources such as WordNet, Wikipedia, BabelNet or FreeBase as reference, but also the so ­called multi ­prototype approaches which learn sense distinctions by using different clustering techniques. Our tutorial will discuss the advantages and potential limitations of all approaches, showing their most successful applications to date. We will conclude by presenting current open problems and lines of future work.
Title: Adversarial Multi-task Learning for Text Classification
Venue: ACL (2017)
Topic: low-resource methods for nlp
Abstract: Neural network models have shown their promising opportunities for multi-task learning, which focus on learning the shared layers to extract the common and task-invariant features. However, in most existing approaches, the extracted shared features are prone to be contaminated by task-specific features or the noise brought by other tasks. In this paper, we propose an adversarial multi-task learning framework, alleviating the shared and private latent feature spaces from interfering with each other. We conduct extensive experiments on 16 different text classification tasks, which demonstrates the benefits of our approach. Besides, we show that the shared knowledge learned by our proposed model can be regarded as off-the-shelf knowledge and easily transferred to new tasks. The datasets of all 16 tasks are publicly available at http://nlp.fudan.edu.cn/data/.
Title: Neural End-to-End Learning for Computational Argumentation Mining
Venue: ACL (2017)
Topic: syntax: tagging, chunking and parsing
Abstract: We investigate neural techniques for end-to-end computational argumentation mining (AM). We frame AM both as a token-based dependency parsing and as a token-based sequence tagging problem, including a multi-task learning setup. Contrary to models that operate on the argument component level, we find that framing AM as dependency parsing leads to subpar performance results. In contrast, less complex (local) tagging models based on BiLSTMs perform robustly across classification scenarios, being able to catch long-range dependencies inherent to the AM problem. Moreover, we find that jointly learning ‘natural’ subtasks, in a multi-task learning setup, improves performance.
Title: Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision
Venue: ACL (2017)
Topic: semantics: lexical, sentence-level semantics, textual inference and other areas
Abstract: Harnessing the statistical power of neural networks to perform language understanding and symbolic reasoning is difficult, when it requires executing efficient discrete operations against a large knowledge-base. In this work, we introduce a Neural Symbolic Machine, which contains (a) a neural “programmer”, i.e., a sequence-to-sequence model that maps language utterances to programs and utilizes a key-variable memory to handle compositionality (b) a symbolic “computer”, i.e., a Lisp interpreter that performs program execution, and helps find good programs by pruning the search space. We apply REINFORCE to directly optimize the task reward of this structured prediction problem. To train with weak supervision and improve the stability of REINFORCE, we augment it with an iterative maximum-likelihood training process. NSM outperforms the state-of-the-art on the WebQuestionsSP dataset when trained from question-answer pairs only, without requiring any feature engineering or domain-specific knowledge.
Title: Neural Relation Extraction with Multi-lingual Attention
Venue: ACL (2017)
Topic: information extraction
Abstract: Relation extraction has been widely used for finding unknown relational facts from plain text. Most existing methods focus on exploiting mono-lingual data for relation extraction, ignoring massive information from the texts in various languages. To address this issue, we introduce a multi-lingual neural relation extraction framework, which employs mono-lingual attention to utilize the information within mono-lingual texts and further proposes cross-lingual attention to consider the information consistency and complementarity among cross-lingual texts. Experimental results on real-world datasets show that, our model can take advantage of multi-lingual texts and consistently achieve significant improvements on relation extraction as compared with baselines.
Title: Learning Structured Natural Language Representations for Semantic Parsing
Venue: ACL (2017)
Topic: syntax: tagging, chunking and parsing
Abstract: We introduce a neural semantic parser which is interpretable and scalable. Our model converts natural language utterances to intermediate, domain-general natural language representations in the form of predicate-argument structures, which are induced with a transition system and subsequently mapped to target domains. The semantic parser is trained end-to-end using annotated logical forms or their denotations. We achieve the state of the art on SPADES and GRAPHQUESTIONS and obtain competitive results on GEOQUERY and WEBQUESTIONS. The induced predicate-argument structures shed light on the types of representations useful for semantic parsing and how these are different from linguistically motivated ones.