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Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph
TLDR
The task of Complex Sequential QA is introduced which combines the two tasks of answering factual questions through complex inferencing over a realistic-sized KG of millions of entities, and learning to converse through a series of coherently linked QA pairs.
Diversity driven attention model for query-based abstractive summarization
TLDR
This work proposes a model for the query-based summarization task based on the encode-attend-decode paradigm with two key additions: a query attention model which learns to focus on different portions of the query at different time steps and a new diversity based Attention model which aims to alleviate the problem of repeating phrases in the summary.
Show Me Your Evidence - an Automatic Method for Context Dependent Evidence Detection
TLDR
This work proposes the task of automatically detecting evidences from unstructured text that support a given claim and suggests a system architecture based on supervised learning to address the evidence detection task.
An Autoencoder Approach to Learning Bilingual Word Representations
TLDR
This work explores the use of autoencoder-based methods for cross-language learning of vectorial word representations that are coherent between two languages, while not relying on word-level alignments, and achieves state-of-the-art performance.
iNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages
TLDR
This paper introduces NLP resources for 11 major Indian languages from two major language families, and creates datasets for the following tasks: Article Genre Classification, Headline Prediction, Wikipedia Section-Title Prediction, Cloze-style Multiple choice QA, Winograd NLI and COPA.
Towards Exploiting Background Knowledge for Building Conversation Systems
TLDR
This work creates a new dataset containing movie chats wherein each response is explicitly generated by copying and/or modifying sentences from unstructured background knowledge such as plots, comments and reviews about the movie.
Towards Building Large Scale Multimodal Domain-Aware Conversation Systems
TLDR
This paper introduces the task of multimodal, domain-aware conversations, and proposes the MMD benchmark dataset, and presents a `per-state evaluation' of 9 most significant dialog states, which would enable more focused research into understanding the challenges and complexities involved in each of these states.
Correlational Neural Networks
TLDR
This work proposes an AE-based approach, correlational neural network (CorrNet), that explicitly maximizes correlation among the views when projected to the common subspace and shows that the representations learned using it perform better than the ones learned using other state-of-the-art approaches.
DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension
TLDR
DuoRC is proposed, a novel dataset for Reading Comprehension (RC) that motivates several new challenges for neural approaches in language understanding beyond those offered by existing RC datasets and could complement other RC datasets to explore novel neural approaches for studying language understanding.
Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks
TLDR
Counter-intuitive results wherein by randomly pruning 25-50% filters from deep CNNs the authors are able to obtain the same performance as obtained by using state of the art pruning methods are shown.
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