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Found 20 papers, 3 papers with code
LangResearchLab_NC at FinCausal 2020, Task 1: A Knowledge Induced Neural Net for Causality Detection
Identifying causal relationships in a text is essential for achieving comprehensive natural language understanding.
LangResearchLab_NC at CMCL2021 Shared Task: Predicting Gaze Behaviour Using Linguistic Features and Tree Regressors
Analysis of gaze data behaviour has gained momentum in recent years for different NLP applications.
MTL782_IITD at CMCL 2021 Shared Task: Prediction of Eye-Tracking Features Using BERT Embeddings and Linguistic Features
The aim of the shared task is to predict five eye-tracking features for a given word of the input sentence.
Team LRL_NC at SemEval-2022 Task 4: Binary and Multi-label Classification of PCL using Fine-tuned Transformer-based Models
Among subsequently carried out experiments a variation in architecture of a system for Subtask 2 achieved a macro-average F1-Score of 0. 3527.
NARNIA at NLP4IF-2021: Identification of Misinformation in COVID-19 Tweets Using BERTweet
The spread of COVID-19 has been accompanied with widespread misinformation on social media.
Summarization of Long Input Texts Using Multi-Layer Neural Network
The proposed MLLTS system handles the difficulty by splitting the text into several parts.
QuanTaxo: A Quantum Approach to Self-Supervised Taxonomy Expansion
A taxonomy is a hierarchical graph containing knowledge to provide valuable insights for various web applications.
Can LLMs replace Neil deGrasse Tyson? Evaluating the Reliability of LLMs as Science Communicators
Large Language Models (LLMs) and AI assistants driven by these models are experiencing exponential growth in usage among both expert and amateur users.
Scrutinizing Data from Sky: An Examination of Its Veracity in Area Based Traffic Contexts
Traffic data collection has been an overwhelming task for researchers as well as authorities over the years.
FL Games: A Federated Learning Framework for Distribution Shifts
Federated learning aims to train predictive models for data that is distributed across clients, under the orchestration of a server.
FL Games: A federated learning framework for distribution shifts
Federated learning aims to train predictive models for data that is distributed across clients, under the orchestration of a server.
Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations
To close the gap, we organized the BioCreative LitCovid track to call for a community effort to tackle automated topic annotation for COVID-19 literature.
Interpretation of Black Box NLP Models: A Survey
An increasing number of machine learning models have been deployed in domains with high stakes such as finance and healthcare.
LangResearchLab NC at SemEval-2021 Task 1: Linguistic Feature Based Modelling for Lexical Complexity
The present work aims at assigning a complexity score between 0 and 1 to a target word or phrase in a given sentence.
Automatic Extraction of Agriculture Terms from Domain Text: A Survey of Tools and Techniques
RAKE, TerMine, TermRaider and compares their performance in terms of precision and recall, vis-a-vis RENT, a more recent term extractor developed by these authors for agriculture domain.
Probabilistic Random Indexing for Continuous Event Detection
The present paper explores a novel variant of Random Indexing (RI) based representations for encoding language data with a view to using them in a dynamic scenario where events are happening in a continuous fashion.
An improved Bayesian TRIE based model for SMS text normalization
Normalization of SMS text, commonly known as texting language, is being pursued for more than a decade.
Examining Lead-Lag Relationships In-Depth, With Focus On FX Market As Covid-19 Crises Unfolds
Apart from better identifying the lead-lag path, the technique also gives a measure for adjudging closeness between financial time-series.
Statistical Finance Computational Engineering, Finance, and Science 91G30, 68T10, G.3.3
Rough Set based Aggregate Rank Measure & its Application to Supervised Multi Document Summarization
Firstly, it proposes a Rough Set based measure to be utilized for numerical characterization of within class ranking of objects.
