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Eric Nguyen

7 accepted papers

2024

FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Cores

ICLR 2024poster

Convolution models with long filters have demonstrated state-of-the-art reasoning abilities in many long-sequence tasks but lag behind the most optimized Transformers in wall-clock time. A major bottleneck is the Fast Fourier Transform (FFT)---which allows long convolutions to run in $O(N\log N)$ ti…

Cited by 24SourcePDFScholar
2024

Mechanistic Design and Scaling of Hybrid Architectures

ICML 2024poster

The development of deep learning architectures is a resource-demanding process, due to a vast design space, long prototyping times, and high compute costs associated with at-scale model training and evaluation. We set out to simplify this process by grounding it in an end-to-end mechanistic architec…

2023

Hyena Hierarchy: Towards Larger Convolutional Language Models

ICML 2023oral

Recent advances in deep learning have relied heavily on the use of large Transformers due to their ability to learn at scale. However, the core building block of Transformers, the attention operator, exhibits quadratic cost in sequence length, limiting the amount of context accessible. Existing subq…

2023

HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution

NeurIPS 2023spotlight

Genomic (DNA) sequences encode an enormous amount of information for gene regulation and protein synthesis. Similar to natural language models, researchers have proposed foundation models in genomics to learn generalizable features from unlabeled genome data that can then be fine-tuned for downstrea…

2023

Simple Hardware-Efficient Long Convolutions for Sequence Modeling

ICML 2023poster

State space models (SSMs) have high performance on long sequence modeling but require sophisticated initialization techniques and specialized implementations for high quality and runtime performance. We study whether a simple alternative can match SSMs in performance and efficiency: directly learnin…

2022

S4ND: Modeling Images and Videos as Multidimensional Signals with State Spaces

NeurIPS 2022accept

Visual data such as images and videos are typically modeled as discretizations of inherently continuous, multidimensional signals. Existing continuous-signal models attempt to exploit this fact by modeling the underlying signals of visual (e.g., image) data directly. However, these models have not…

Cited by 228SourcePDFScholar
2021

OSCAR-Net: Object-Centric Scene Graph Attention for Image Attribution

ICCV 2021poster

Images tell powerful stories but cannot always be trusted. Matching images back to trusted sources (attribution) enables users to make a more informed judgment of the images they encounter online. We propose a robust image hashing algorithm to perform such matching. Our hash is sensitive to manipula…

Cited by 19PDFScholar