no code implementations • 11 Apr 2024 • Vigneshwaran Shankaran, Rajesh Sharma
This anonymity has also made social media prone to harmful content, which requires moderation to ensure responsible and productive use.
no code implementations • 31 Mar 2024 • Orchid Chetia Phukan, Ankita Das, Arun Balaji Buduru, Rajesh Sharma
Stress recognition through physiological signals such as Electrocardiogram (ECG) signals has garnered significant attention.
1 code implementation • 31 Mar 2024 • Orchid Chetia Phukan, Gautam Siddharth Kashyap, Arun Balaji Buduru, Rajesh Sharma
To validate our hypothesis, we extract representations from state-of-the-art (SOTA) PTMs including monolingual, multilingual as well as PTMs trained for speaker and emotion recognition, and evaluated them on ASVSpoof 2019 (ASV), In-the-Wild (ITW), and DECRO benchmark databases.
no code implementations • 18 Mar 2024 • Aditya Narayan Sankaran, Vigneshwaran Shankaran, Sampath Lonka, Rajesh Sharma
To summarize, this work highlights the pervasive nature of gender stereotypes in literary works and reveals the potential of LLMs to rectify gender stereotypes.
no code implementations • 2 Feb 2024 • Orchid Chetia Phukan, Gautam Siddharth Kashyap, Arun Balaji Buduru, Rajesh Sharma
We also show that downstream models using TRILLsson representations achieve SOTA performance in terms of accuracy across various multi-lingual datasets.
no code implementations • 15 Nov 2023 • Swapnil Mane, Suman Kundu, Rajesh Sharma
Recognizing the societal risks associated with unchecked aggressive content, this paper delves into the field of Aggression Content Detection and Behavioral Analysis of Aggressive Users, aiming to bridge the gap between disparate studies.
no code implementations • 29 Oct 2023 • Shakshi Sharma, Anwitaman Datta, Rajesh Sharma
While the ideas herein can be generalized and reapplied in the broader context of misinformation mitigation using a multitude of information sources and catering to the spectrum of social media platforms, this work serves as a proof of concept, and as such, it is confined in its scope to only rebuttal of tweets, and in the specific context of misinformation regarding COVID-19.
no code implementations • 11 Oct 2023 • Gustav Nikopensius, Mohit Mayank, Orchid Chetia Phukan, Rajesh Sharma
Extensive experiments on FB15K-277 and NELL-995 datasets reveal that reasoning over a KG is an effective way of producing human-readable explanations in the form of paths and classifications for fact claims.
no code implementations • 25 Aug 2023 • Shakshi Sharma, Anwitaman Datta, Vigneshwaran Shankaran, Rajesh Sharma
We demonstrate the Misinformation Concierge, a proof-of-concept that provides actionable intelligence on misinformation prevalent in social media.
no code implementations • 29 May 2023 • Animesh Chaturvedi, Rajesh Sharma
For a given set of Hate Terms lists (HTs-lists) and Hate Speech data (HS-data), it is challenging to understand which hate term contributes the most for hate speech classification.
no code implementations • 29 May 2023 • Orchid Chetia Phukan, Arun Balaji Buduru, Rajesh Sharma
Speech emotion recognition (SER) is a field that has drawn a lot of attention due to its applications in diverse fields.
no code implementations • 22 Apr 2023 • Orchid Chetia Phukan, Arun Balaji Buduru, Rajesh Sharma
In this work, we exploit this research gap and perform a comparative analysis of embeddings extracted from eight speech and audio PTMs (wav2vec 2. 0, data2vec, wavLM, UniSpeech-SAT, wav2clip, YAMNet, x-vector, ECAPA).
no code implementations • 15 Jan 2023 • Rahul Goel, Angelo Furno, Rajesh Sharma
Nonetheless, alternative data sources, such as call data records (CDR) and mobile app usage, can serve as cost-effective and up-to-date sources for identifying socio-economic indicators.
no code implementations • 25 Feb 2022 • Mudit Dhawan, Shakshi Sharma, Aditya Kadam, Rajesh Sharma, Ponnurangam Kumaraguru
A plethora of previous multimodal-based work has tried to address the problem of modeling heterogeneous modalities in identifying fake content.
no code implementations • 25 Jan 2022 • Rahul Goel, Modar Sulaiman, Kimia Noorbakhsh, Mahdi Sharifi, Rajesh Sharma, Pooyan Jamshidi, Kallol Roy
The pretrained transformer of GPT-2 is trained to generate text and then fine-tuned to classify facial images.
no code implementations • 9 Nov 2021 • Sabur Butt, Shakshi Sharma, Rajesh Sharma, Grigori Sidorov, Alexander Gelbukh
In the descriptive line of works, where researchers have tried to analyse rumours using NLP approaches, there isnt much emphasis on psycho-linguistics analyses of social media text.
1 code implementation • 16 Aug 2021 • Shakshi Sharma, Rajesh Sharma, Anwitaman Datta
We build on this to study and contrast the characteristics of tweets in the corpus that are misleading in nature against non-misleading ones.
no code implementations • 4 Jul 2021 • Mohit Mayank, Shakshi Sharma, Rajesh Sharma
Our approach is a combination of the NLP -- where we encode the news content, and the GNN technique -- where we encode the Knowledge Graph (KG).
1 code implementation • 2 Jul 2021 • Raj Jagtap, Abhinav Kumar, Rahul Goel, Shakshi Sharma, Rajesh Sharma, Clint P. George
Using caption dataset, the proposed models can classify videos among three classes (Misinformation, Debunking Misinformation, and Neutral) with 0. 85 to 0. 90 F1-score.
no code implementations • 11 Apr 2021 • Abdul Wahid, Rajesh Sharma, Chandra Sekhara Rao Annavarapu
Scientific publications play a vital role in the career of a researcher.
no code implementations • 13 Nov 2020 • Rahul Goel, Lucas Javier Ford, Maksym Obrizan, Rajesh Sharma
COVID-19 has had a much larger impact on the financial markets compared to previous epidemics because the news information is transferred over the social networks at a speed of light.
2 code implementations • 15 Oct 2020 • Shakshi Sharma, Rajesh Sharma
Thus, it is important to detect and control the misinformation in such platforms before it spreads to the masses.
no code implementations • 29 Apr 2020 • Ivan Slobozhan, Peter Ormosi, Rajesh Sharma
We also investigate the influence of the intensity of the lobbying activity on how discernible a lobbied bill is from one that was not subject to lobbying.
no code implementations • 18 Apr 2020 • Navedanjum Ansari, Rajesh Sharma
Three out of four proposed architectures outperformed the accuracy from previous machine learning and deep learning research work, two out of four models outperformed accuracy from previous deep learning study on Quora's question pair dataset, and our best model achieved accuracy of 85. 82% which is close to Quora state of the art accuracy.