5 citations · 5 across the 2 of their papers we have counts for
4 papers
Mechanisms of Misgeneralization in Physical Sequence Modeling
Kento Nishi, Raphael Tang, Karun Kumar +2
Generative sequence models are often trained to plan motion in physical domains, from robotics to mechanical simulations. When constructing a dataset to train such a model, enginee…
WhisTLE: Deeply Supervised, Text-Only Domain Adaptation for Small Pretrained Speech Recognition Transformers
Akshat Pandey, Karun Kumar, Raphael Tang
Pretrained automatic speech recognition (ASR) models such as Whisper perform well but still need domain adaptation to handle unseen parlance. In many real-world settings, collectin…
SpeechNet: Weakly Supervised, End-to-End Speech Recognition at Industrial Scale
Raphael Tang, Karun Kumar, Gefei Yang +7
End-to-end automatic speech recognition systems represent the state of the art, but they rely on thousands of hours of manually annotated speech for training, as well as heavyweigh…
What the DAAM: Interpreting Stable Diffusion Using Cross Attention
Raphael Tang, Linqing Liu, Akshat Pandey +6
Large-scale diffusion neural networks represent a substantial milestone in text-to-image generation, but they remain poorly understood, lacking interpretability analyses. In this p…