4 papers
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…