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Found 20 papers, 5 papers with code
Grounding Counterfactual Explanation of Image Classifiers to Textual Concept Space
In this paper, we propose counterfactual explanation with text-driven concepts (CounTEX), where the concepts are defined only from text by leveraging a pre-trained multi-modal joint embedding space without additional concept-annotated datasets.
Weakly Supervised Referring Image Segmentation with Intra-Chunk and Inter-Chunk Consistency
Referring image segmentation (RIS) aims to localize the object in an image referred by a natural language expression.
Interpretable Propaganda Detection in News Articles
Online users today are exposed to misleading and propagandistic news articles and media posts on a daily basis.
Cooperative Self-training of Machine Reading Comprehension
Pretrained language models have significantly improved the performance of downstream language understanding tasks, including extractive question answering, by providing high-quality contextualized word embeddings.
Ranked #1 on
Question Answering
on MRQA out-of-domain
Extractive Question-Answering
Machine Reading Comprehension
+6
AutoKG: Constructing Virtual Knowledge Graphs from Unstructured Documents for Question Answering
Knowledge graphs (KGs) have the advantage of providing fine-grained detail for question-answering systems.
A Survey on Computational Propaganda Detection
Propaganda campaigns aim at influencing people's mindset with the purpose of advancing a specific agenda.
Prta: A System to Support the Analysis of Propaganda Techniques in the News
However, little attention has been paid to the specific rhetorical and psychological techniques used to convey propaganda messages.
Experiments in Detecting Persuasion Techniques in the News
Many recent political events, like the 2016 US Presidential elections or the 2018 Brazilian elections have raised the attention of institutions and of the general public on the role of Internet and social media in influencing the outcome of these events.
Fine-Grained Analysis of Propaganda in News Article
Propaganda aims at influencing people{'}s mindset with the purpose of advancing a specific agenda.
Fine-Grained Analysis of Propaganda in News Articles
Propaganda aims at influencing people's mindset with the purpose of advancing a specific agenda.
Ensemble-Based Deep Reinforcement Learning for Chatbots
Experimental results using chitchat data reveal that (1) near human-like dialogue policies can be induced, (2) generalisation to unseen data is a difficult problem, and (3) training an ensemble of chatbot agents is essential for improved performance over using a single agent.
Factor Graph Attention
We address this issue and develop a general attention mechanism for visual dialog which operates on any number of data utilities.
Ranked #1 on
Visual Dialog
on VisDial v0.9 val
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.
MemoReader: Large-Scale Reading Comprehension through Neural Memory Controller
Machine reading comprehension helps machines learn to utilize most of the human knowledge written in the form of text.
Ranked #27 on
Question Answering
on TriviaQA
(using extra training data)
Cut to the Chase: A Context Zoom-in Network for Reading Comprehension
In recent years many deep neural networks have been proposed to solve Reading Comprehension (RC) tasks.
Ranked #4 on
Question Answering
on NarrativeQA
On-Device Neural Language Model Based Word Prediction
Recent developments in deep learning with application to language modeling have led to success in tasks of text processing, summarizing and machine translation.
A Multi-Stage Memory Augmented Neural Network for Machine Reading Comprehension
Reading Comprehension (RC) of text is one of the fundamental tasks in natural language processing.
Ranked #69 on
Question Answering
on SQuAD1.1
Syllable-level Neural Language Model for Agglutinative Language
Language models for agglutinative languages have always been hindered in past due to myriad of agglutinations possible to any given word through various affixes.
An Embedded Deep Learning based Word Prediction
Recent developments in deep learning with application to language modeling have led to success in tasks of text processing, summarizing and machine translation.
Deep Reinforcement Learning for Multi-Domain Dialogue Systems
Standard deep reinforcement learning methods such as Deep Q-Networks (DQN) for multiple tasks (domains) face scalability problems.
