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Found 54 papers, 1 papers with code
A Study of Latent Structured Prediction Approaches to Passage Reranking
The structured output framework provides a helpful tool for learning to rank problems.
Semantic Linking in Convolutional Neural Networks for Answer Sentence Selection
State-of-the-art networks that model relations between two pieces of text often use complex architectures and attention.
Supervised Clustering of Questions into Intents for Dialog System Applications
Modern automated dialog systems require complex dialog managers able to deal with user intent triggered by high-level semantic questions.
Cross-Pair Text Representations for Answer Sentence Selection
High-level semantics tasks, e. g., paraphrasing, textual entailment or question answering, involve modeling of text pairs.
Natural Language Inference
Open-Domain Question Answering
+1
Learning to Progressively Recognize New Named Entities with Sequence to Sequence Models
In this paper, we propose to use a sequence to sequence model for Named Entity Recognition (NER) and we explore the effectiveness of such model in a progressive NER setting {--} a Transfer Learning (TL) setting.
A Flexible, Efficient and Accurate Framework for Community Question Answering Pipelines
Although deep neural networks have been proving to be excellent tools to deliver state-of-the-art results, when data is scarce and the tackled tasks involve complex semantic inference, deep linguistic processing and traditional structure-based approaches, such as tree kernel methods, are an alternative solution.
Ranking Kernels for Structures and Embeddings: A Hybrid Preference and Classification Model
Recent work has shown that Tree Kernels (TKs) and Convolutional Neural Networks (CNNs) obtain the state of the art in answer sentence reranking.
Learning Contextual Embeddings for Structural Semantic Similarity using Categorical Information
In this paper, we combine them by modeling context word similarity in semantic TKs.
KeLP at SemEval-2017 Task 3: Learning Pairwise Patterns in Community Question Answering
This paper describes the KeLP system participating in the SemEval-2017 community Question Answering (cQA) task.
Collaborative Partitioning for Coreference Resolution
This paper presents a collaborative partitioning algorithm{---}a novel ensemble-based approach to coreference resolution.
Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures
An interesting aspect of structured prediction is the evaluation of an output structure against the gold standard.
Self-Crowdsourcing Training for Relation Extraction
In this paper we introduce a self-training strategy for crowdsourcing.
A Practical Perspective on Latent Structured Prediction for Coreference Resolution
Latent structured prediction theory proposes powerful methods such as Latent Structural SVM (LSSVM), which can potentially be very appealing for coreference resolution (CR).
Effective shared representations with Multitask Learning for Community Question Answering
An important asset of using Deep Neural Networks (DNNs) for text applications is their ability to automatically engineering features.
Selecting Sentences versus Selecting Tree Constituents for Automatic Question Ranking
Community question answering (cQA) websites are focused on users who query questions onto an online forum, expecting for other users to provide them answers or suggestions.
An Interactive System for Exploring Community Question Answering Forums
We present an interactive system to provide effective and efficient search capabilities in Community Question Answering (cQA) forums.
Neural Attention for Learning to Rank Questions in Community Question Answering
In real-world data, e. g., from Web forums, text is often contaminated with redundant or irrelevant content, which leads to introducing noise in machine learning algorithms.
SenTube: A Corpus for Sentiment Analysis on YouTube Social Media
In this paper we present SenTube -- a dataset of user-generated comments on YouTube videos annotated for information content and sentiment polarity.
