7 citations · 8 across the 6 of their papers we have counts for
6 papers
Multi Attribute Bias Mitigation via Representation Learning
Rajeev Ranjan Dwivedi, Ankur Kumar, Vinod K Kurmi
Real world images frequently exhibit multiple overlapping biases, including textures, watermarks, gendered makeup, scene object pairings, etc. These biases collectively impair the…
A Data-Driven Diffusion-based Approach for Audio Deepfake Explanations
Petr Grinberg, Ankur Kumar, Surya Koppisetti +1
Evaluating explainability techniques, such as SHAP and LRP, in the context of audio deepfake detection is challenging due to lack of clear ground truth annotations. In the cases wh…
What Does an Audio Deepfake Detector Focus on? A Study in the Time Domain
Petr Grinberg, Ankur Kumar, Surya Koppisetti +1
Adding explanations to audio deepfake detection (ADD) models will boost their real-world application by providing insight on the decision making process. In this paper, we propose…
Residual vector quantization for KV cache compression in large language model
Ankur Kumar
KV cache compression methods have mainly relied on scalar quantization techniques to reduce the memory requirements during decoding. In this work, we apply residual vector quantiza…
Learn from Real: Reality Defender's Submission to ASVspoof5 Challenge
Yi Zhu, Chirag Goel, Surya Koppisetti +3
Audio deepfake detection is crucial to combat the malicious use of AI-synthesized speech. Among many efforts undertaken by the community, the ASVspoof challenge has become one of t…
Stateful Conformer with Cache-based Inference for Streaming Automatic Speech Recognition
Vahid Noroozi, Somshubra Majumdar, Ankur Kumar +2
In this paper, we propose an efficient and accurate streaming speech recognition model based on the FastConformer architecture. We adapted the FastConformer architecture for stream…