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Found 29 papers, 5 papers with code
SentinelLMs: Encrypted Input Adaptation and Fine-tuning of Language Models for Private and Secure Inference
After adaptation, models are fine-tuned on encrypted versions of existing training datasets.
Can Open Domain Question Answering Systems Answer Visual Knowledge Questions?
In this work, we propose a potentially data-efficient approach that reuses existing systems for (a) image analysis, (b) question rewriting, and (c) text-based question answering to answer such visual questions.
A Survey on Using Gaze Behaviour for Natural Language Processing
Gaze behaviour has been used as a way to gather cognitive information for a number of years.
Template Controllable keywords-to-text Generation
The model takes as input a set of un-ordered keywords, and part-of-speech (POS) based template instructions.
Happy Are Those Who Grade without Seeing: A Multi-Task Learning Approach to Grade Essays Using Gaze Behaviour
To demonstrate the efficacy of this multi-task learning based approach to automatic essay grading, we collect gaze behaviour for 48 essays across 4 essay sets, and learn gaze behaviour for the rest of the essays, numbering over 7000 essays.
A Modular Architecture for Unsupervised Sarcasm Generation
In this paper, we propose a novel framework for sarcasm generation; the system takes a literal negative opinion as input and translates it into a sarcastic version.
Storytelling from Structured Data and Knowledge Graphs : An NLG Perspective
In this tutorial, we wish to cover the foundational, methodological, and system development aspects of translating structured data (such as data in tabular form) and knowledge bases (such as knowledge graphs) into natural language.
Unsupervised Neural Text Simplification
The paper presents a first attempt towards unsupervised neural text simplification that relies only on unlabeled text corpora.
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Text Simplification
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Eyes are the Windows to the Soul: Predicting the Rating of Text Quality Using Gaze Behaviour
Such subjective aspects are better handled using cognitive information.
Scalable Micro-planned Generation of Discourse from Structured Data
We present a framework for generating natural language description from structured data such as tables; the problem comes under the category of data-to-text natural language generation (NLG).
Unsupervised Controllable Text Formalization
We propose a novel framework for controllable natural language transformation.
Modeling Topical Coherence in Discourse without Supervision
Our evaluation shows that the measured coherence scores are positively correlated with the ground truth for both the datasets.
Graph Based Sentiment Aggregation using ConceptNet Ontology
The sentiment aggregation problem accounts for analyzing the sentiment of a user towards various aspects/features of a product, and meaningfully assimilating the pragmatic significance of these features/aspects from an opinionated text.
CVBed: Structuring CVs usingWord Embeddings
Automatic analysis of curriculum vitae (CVs) of applicants is of tremendous importance in recruitment scenarios.
Story Generation from Sequence of Independent Short Descriptions
Existing Natural Language Generation (NLG) systems are weak AI systems and exhibit limited capabilities when language generation tasks demand higher levels of creativity, originality and brevity.
Learning Cognitive Features from Gaze Data for Sentiment and Sarcasm Classification using Convolutional Neural Network
We contend that manual extraction of features may not be the best way to tackle text subtleties that characteristically prevail in complex classification tasks like Sentiment Analysis and Sarcasm Detection, and that even the extraction and choice of features should be delegated to the learning system.
Leveraging Cognitive Features for Sentiment Analysis
Sentiments expressed in user-generated short text and sentences are nuanced by subtleties at lexical, syntactic, semantic and pragmatic levels.
Harnessing Cognitive Features for Sarcasm Detection
In this paper, we propose a novel mechanism for enriching the feature vector, for the task of sarcasm detection, with cognitive features extracted from eye-movement patterns of human readers.
A Computational Approach to Automatic Prediction of Drunk Texting
Alcohol abuse may lead to unsociable behavior such as crime, drunk driving, or privacy leaks.
Shata-Anuvadak: Tackling Multiway Translation of Indian Languages
We present a compendium of 110 Statistical Machine Translation systems built from parallel corpora of 11 Indian languages belonging to both Indo-Aryan and Dravidian families.
