1 citations · 2 across the 6 of their papers we have counts for
8 papers
To Trust or Not to Trust: Retrieval-Augmented Fact Checking in Speech
Debajyoti Mazumder, Mamta, Abhirama Subramanyam Penamakuri
Online misinformation increasingly appears in spoken formats such as news clips, podcasts, interviews, political speeches, and social media videos, creating a need for fact-checkin…
Evaluating Cross-lingual Knowledge Consistency in Code-Mixed vis-a-vis Indian Languages using IndicKLAR
Debajyoti Mazumder, Divyansh Pathak, Prashant Kodali +3
Large language models often exhibit a substantial gap between their performance in English and in lower-resourced languages on equivalent knowledge queries---a cross-lingual consis…
Neither Here Nor There: Cross-Lingual Representation Dynamics of Code-Mixed Text in Multilingual Encoders
Debajyoti Mazumder, Divyansh Pathak, Prashant Kodali +1
Multilingual encoder-based language models are widely used for code-mixed analysis, yet their internal representations of code-mixed inputs -- and their relationship to the constit…
Mind the Links: Cross-Layer Attention for Link Prediction in Multiplex Networks
Devesh Sharma, Aditya Kishore, Ayush Garg +3
Multiplex graphs capture diverse relations among shared nodes. Most predictors either collapse layers or treat them independently. This loses crucial inter-layer dependencies and s…
On VLMs for Diverse Tasks in Multimodal Meme Classification
Deepesh Gavit, Debajyoti Mazumder, Samiran Das +1
In this paper, we present a comprehensive and systematic analysis of vision-language models (VLMs) for disparate meme classification tasks. We introduced a novel approach that gene…
Entailed Opinion Matters: Improving the Fact-Checking Performance of Language Models by Relying on their Entailment Ability
Gaurav Kumar, Ayush Garg, Debajyoti Mazumder +3
Automated fact-checking has been a challenging task for the research community. Prior work has explored various strategies, such as end-to-end training, retrieval-augmented generat…
Revealing the impact of synthetic native samples and multi-tasking strategies in Hindi-English code-mixed humour and sarcasm detection
Debajyoti Mazumder, Aakash Kumar, Jasabanta Patro
In this paper, we reported our experiments with various strategies to improve code-mixed humour and sarcasm detection. Particularly, we tried three approaches: (i) native sample mi…
Improving code-mixed hate detection by native sample mixing: A case study for Hindi-English code-mixed scenario
Debajyoti Mazumder, Aakash Kumar, Jasabanta Patro
Hate detection has long been a challenging task for the NLP community. The task becomes complex in a code-mixed environment because the models must understand the context and the h…