Author name cluster

Inder Khatri

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

4 papers

1 author row

AAAI Conference 2023 Short Paper

An Emotion-Guided Approach to Domain Adaptive Fake News Detection Using Adversarial Learning (Student Abstract)

Arkajyoti Chakraborty
Inder Khatri
Arjun Choudhry
Pankaj Gupta
Dinesh Kumar Vishwakarma
Mukesh Prasad

Recent works on fake news detection have shown the efficacy of using emotions as a feature for improved performance. However, the cross-domain impact of emotion-guided features for fake news detection still remains an open problem. In this work, we propose an emotion-guided, domain-adaptive, multi-task approach for cross-domain fake news detection, proving the efficacy of emotion-guided models in cross-domain settings for various datasets.

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AAAI Conference 2023 Short Paper

CKS: A Community-Based K-shell Decomposition Approach Using Community Bridge Nodes for Influence Maximization (Student Abstract)

Inder Khatri
Aaryan Gupta
Arjun Choudhry
Aryan Tyagi
Dinesh Kumar Vishwakarma
Mukesh Prasad

Social networks have enabled user-specific advertisements and recommendations on their platforms, which puts a significant focus on Influence Maximisation (IM) for target advertising and related tasks. The aim is to identify nodes in the network which can maximize the spread of information through a diffusion cascade. We propose a community structures-based approach that employs K-Shell algorithm with community structures to generate a score for the connections between seed nodes and communities. Further, our approach employs entropy within communities to ensure the proper spread of information within the communities. We validate our approach on four publicly available networks and show its superiority to four state-of-the-art approaches while still being relatively efficient.

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AAAI Conference 2023 Short Paper

Transformer-Based Named Entity Recognition for French Using Adversarial Adaptation to Similar Domain Corpora (Student Abstract)

Arjun Choudhry
Pankaj Gupta
Inder Khatri
Aaryan Gupta
Maxime Nicol
Marie-Jean Meurs
Dinesh Kumar Vishwakarma

Named Entity Recognition (NER) involves the identification and classification of named entities in unstructured text into predefined classes. NER in languages with limited resources, like French, is still an open problem due to the lack of large, robust, labelled datasets. In this paper, we propose a transformer-based NER approach for French using adversarial adaptation to similar domain or general corpora for improved feature extraction and better generalization. We evaluate our approach on three labelled datasets and show that our adaptation framework outperforms the corresponding non-adaptive models for various combinations of transformer models, source datasets and target corpora.

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AAAI Conference 2022 Short Paper

An Emotion-Based Multi-Task Approach to Fake News Detection (Student Abstract)

Arjun Choudhry
Inder Khatri
Minni Jain

Social media, blogs, and online articles are instant sources of news for internet users globally. But due to their unmoderated nature, a significant percentage of these texts are fake news or rumors. Their deceptive nature and ability to propagate instantly can have an adverse effect on society. In this work, we hypothesize that legitimacy of news has a correlation with its emotion, and propose a multi-task framework predicting both the emotion and legitimacy of news. Experimental results verify that our multi-task models outperform their single-task counterparts in terms of accuracy.

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