18 citations · 33 across the 6 of their papers we have counts for
7 papers
HD-cos Networks: Efficient Neural Architectures for Secure Multi-Party Computation
Wittawat Jitkrittum, Michal Lukasik, Ananda Theertha Suresh +2
Multi-party computation (MPC) is a branch of cryptography where multiple non-colluding parties execute a well designed protocol to securely compute a function. With the non-colludi…
Leveraging redundancy in attention with Reuse Transformers
Srinadh Bhojanapalli, Ayan Chakrabarti, Andreas Veit +5
Pairwise dot product-based attention allows Transformers to exchange information between tokens in an input-dependent way, and is key to their success across diverse applications i…
Teacher's pet: understanding and mitigating biases in distillation
Michal Lukasik, Srinadh Bhojanapalli, Aditya Krishna Menon +1
Knowledge distillation is widely used as a means of improving the performance of a relatively simple student model using the predictions from a complex teacher model. Several works…
Eigen Analysis of Self-Attention and its Reconstruction from Partial Computation
Srinadh Bhojanapalli, Ayan Chakrabarti, Himanshu Jain +3
State-of-the-art transformer models use pairwise dot-product based self-attention, which comes at a computational cost quadratic in the input sequence length. In this paper, we inv…
Semantic Label Smoothing for Sequence to Sequence Problems
Michal Lukasik, Himanshu Jain, Aditya Krishna Menon +4
Label smoothing has been shown to be an effective regularization strategy in classification, that prevents overfitting and helps in label de-noising. However, extending such method…
Text Segmentation by Cross Segment Attention
Michal Lukasik, Boris Dadachev, Gonçalo Simões +1
Document and discourse segmentation are two fundamental NLP tasks pertaining to breaking up text into constituents, which are commonly used to help downstream tasks such as informa…