Author

Michael Kampouridis

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#natural language process... Preprint Sep 2026

Pruning for Efficiency, Paying in Fairness: Demographic Disparities in Pruned Speech-LLMs

Speech-LLMs are expensive to run, making compression important for real-world deployment. However, compressed models are usually selected using aggregate word error rate (WER), which can hide how pruning affects different demographic groups. In this work, we systematically study the effect of audio encoder pruning on S...

Ganesh Pavan Kartikeya Bharadwaj Kolluri, Michael Kampouridis, Ravi Shekhar · 0 citations

#natural language process... Preprint Jul 2026

CARD: Cross-component Audio Representation Distillation for Encoder-Free Audio Captioning

Modern automated audio captioning systems pair a frozen audio encoder with a large language model (LLM) via a trainable projector, incurring the encoder's inference cost and bottlenecking the model through its fixed acoustic features. We present CARD, an encoder-free audio captioning model that removes the encoder at i...

Ganesh Pavan Kartikeya Bharadwaj Kolluri, Yuchen Zhang, Michael Kampouridis et al. · 0 citations