5 citations · 6 across the 11 of their papers we have counts for
11 papers
BiG-SURE - Bipartite Graph for Semantic Uncertainty and Reliability Estimation of LLMs
Debarpan Bhattacharya, Malay Phadke, Sriram Ganapathy
Reliable uncertainty estimation is a crucial requirement for deploying large language models (LLMs) and vision-language models (VLMs) in safety-critical settings, especially when t…
FESTA: Functionally Equivalent Sampling for Trust Assessment of Multimodal LLMs
Debarpan Bhattacharya, Apoorva Kulkarni, Sriram Ganapathy
The accurate trust assessment of multimodal large language models (MLLMs) generated predictions, which can enable selective prediction and improve user confidence, is challenging d…
Benchmarking and Confidence Evaluation of LALMs For Temporal Reasoning
Debarpan Bhattacharya, Apoorva Kulkarni, Sriram Ganapathy
The popular success of text-based large language models (LLM) has streamlined the attention of the multimodal community to combine other modalities like vision and audio along with…
Towards Unbiased Evaluation of Time-series Anomaly Detector
Debarpan Bhattacharya, Sumanta Mukherjee, Chandramouli Kamanchi +3
Time series anomaly detection (TSAD) is an evolving area of research motivated by its critical applications, such as detecting seismic activity, sensor failures in industrial plant…
Gradient-free Post-hoc Explainability Using Distillation Aided Learnable Approach
Debarpan Bhattacharya, Amir H. Poorjam, Deepak Mittal +1
The recent advancements in artificial intelligence (AI), with the release of several large models having only query access, make a strong case for explainability of deep models in…
Coswara: A respiratory sounds and symptoms dataset for remote screening of SARS-CoV-2 infection
Debarpan Bhattacharya, Neeraj Kumar Sharma, Debottam Dutta +8
This paper presents the Coswara dataset, a dataset containing diverse set of respiratory sounds and rich meta-data, recorded between April-2020 and February-2022 from 2635 individu…
Interpretable Acoustic Representation Learning on Breathing and Speech Signals for COVID-19 Detection
Debottam Dutta, Debarpan Bhattacharya, Sriram Ganapathy +3
In this paper, we describe an approach for representation learning of audio signals for the task of COVID-19 detection. The raw audio samples are processed with a bank of 1-D convo…
Analyzing the impact of SARS-CoV-2 variants on respiratory sound signals
Debarpan Bhattacharya, Debottam Dutta, Neeraj Kumar Sharma +8
The COVID-19 outbreak resulted in multiple waves of infections that have been associated with different SARS-CoV-2 variants. Studies have reported differential impact of the varian…
Svadhyaya system for the Second Diagnosing COVID-19 using Acoustics Challenge 2021
Deepak Mittal, Amir H. Poorjam, Debottam Dutta +4
This report describes the system used for detecting COVID-19 positives using three different acoustic modalities, namely speech, breathing, and cough in the second DiCOVA challenge…
Coswara: A website application enabling COVID-19 screening by analysing respiratory sound samples and health symptoms
Debarpan Bhattacharya, Debottam Dutta, Neeraj Kumar Sharma +8
The COVID-19 pandemic has accelerated research on design of alternative, quick and effective COVID-19 diagnosis approaches. In this paper, we describe the Coswara tool, a website a…
The Second DiCOVA Challenge: Dataset and performance analysis for COVID-19 diagnosis using acoustics
Neeraj Kumar Sharma, Srikanth Raj Chetupalli, Debarpan Bhattacharya +3
The Second Diagnosis of COVID-19 using Acoustics (DiCOVA) Challenge aimed at accelerating the research in acoustics based detection of COVID-19, a topic at the intersection of acou…