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Found 25 papers, 3 papers with code
Noisy Text Data: Achilles’ Heel of BERT
Owing to the phenomenal success of BERT on various NLP tasks and benchmark datasets, industry practitioners are actively experimenting with fine-tuning BERT to build NLP applications for solving industry use cases.
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.
From Text to Transformation: A Comprehensive Review of Large Language Models' Versatility
This groundbreaking study explores the expanse of Large Language Models (LLMs), such as Generative Pre-Trained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) across varied domains ranging from technology, finance, healthcare to education.
A Lightweight Feature Fusion Architecture For Resource-Constrained Crowd Counting
However, most of the previous methods rely on a heavy backbone and a complex downstream architecture that restricts the deployment.
From Simulations to Reality: Enhancing Multi-Robot Exploration for Urban Search and Rescue
In this study, we present a novel hybrid algorithm, combining Levy Flight (LF) and Particle Swarm Optimization (PSO) (LF-PSO), tailored for efficient multi-robot exploration in unknown environments with limited communication and no global positioning information.
Context-aware 6D Pose Estimation of Known Objects using RGB-D data
In this paper, we present an architecture that, unlike prior work, is context-aware.
Noisy Text Data: Achilles' Heel of popular transformer based NLP models
However, for most datasets that are used by practitioners to build industrial NLP applications, it is hard to guarantee the presence of any noise in the data.
Distance Based Pattern Driven Mining for Outlier Detection in High Dimensional Big Dataset
Detection of outliers or anomalies is one of the vital issues in pattern-driven data mining.
Mondegreen: A Post-Processing Solution to Speech Recognition Error Correction for Voice Search Queries
As more and more online search queries come from voice, automatic speech recognition becomes a key component to deliver relevant search results.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Modelling the COVID-19 virus evolution with Incremental Machine Learning
We performed some experiments in which we compare state-of-the-art machine learning algorithms, such as LSTM, against online incremental machine learning algorithms to adapt them to the daily changes in the spread of the disease and predict future COVID-19 cases.
Magnetodynamic properties of dipole-coupled 1D magnonic crystals
As an alternative to experiments and/or micromagnetic simulations, we investigate the accuracy of a simple macrospin model.
Mesoscale and Nanoscale Physics
Co$_2$FeAl full Heusler compound based spintronic terahertz emitter
To achieve a large terahertz (THz) amplitude from a spintronic THz emitter (STE), materials with 100\% spin polarisation such as Co-based Heusler compounds as the ferromagnetic layer are required.
Materials Science Mesoscale and Nanoscale Physics Other Condensed Matter Optics
Large deviation principle for occupation measures of the two dimensional stochastic convective Brinkman-Forchheimer equations
The present work is concerned about the two-dimensional stochastic convective Brinkman-Forchheimer (2D SCBF) equations perturbed by a white noise (non degenerate) in smooth bounded domains in $\R^{2}$.
Probability
hinglishNorm - A Corpus of Hindi-English Code Mixed Sentences for Text Normalization
We present hinglishNorm - a human annotated corpus of Hindi-English code-mixed sentences for text normalization task.
hinglishNorm -- A Corpus of Hindi-English Code Mixed Sentences for Text Normalization
We present hinglishNorm -- a human annotated corpus of Hindi-English code-mixed sentences for text normalization task.
BigApple force and its implications to finite nuclei and astrophysical objects
The secondary component of the GW190814 event left us with a question, "whether it is a supermassive neutron star or lightest black-hole?".
Nuclear Theory High Energy Astrophysical Phenomena
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval
In light of these problems, we observed that most online content platforms have both a search and a recommender system that, while having heterogeneous input spaces, can be connected through their common output item space and a shared semantic representation.
Hands-off Model Integration in Spatial Index Structures
Spatial indexes are crucial for the analysis of the increasing amounts of spatial data, for example generated through IoT applications.
Noisy Text Data: Achilles' Heel of BERT
Owing to the phenomenal success of BERT on various NLP tasks and benchmark datasets, industry practitioners are actively experimenting with fine-tuning BERT to build NLP applications for solving industry use cases.
Application of the coherent density fluctuation model to study the nuclear matter properties of finite nuclei within the relativistic mean-field formalism
The NM parameters like incompressibility, neutron pressure, symmetry energy, and its derivatives are calculated using the acquired expression of energy per nucleon.
Nuclear Theory
Feature Assisted bi-directional LSTM Model for Protein-Protein Interaction Identification from Biomedical Texts
In this paper, we present a novel method based on deep bidirectional long short-term memory (B-LSTM) technique that exploits word sequences and dependency path related information to identify PPI information from text.
A Fuzzy Logic System to Analyze a Student's Lifestyle
A college student's life can be primarily categorized into domains such as education, health, social and other activities which may include daily chores and travelling time.
Identifying Diabetic Patients with High Risk of Readmission
Early identification of patients facing a high risk of readmission can enable healthcare providers to to conduct additional investigations and possibly prevent future readmissions.
Ask Me Anything: Dynamic Memory Networks for Natural Language Processing
Most tasks in natural language processing can be cast into question answering (QA) problems over language input.
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