Search Results for author: Vy A. Vo

Found 5 papers, 1 papers with code

Scope is all you need: Transforming LLMs for HPC Code

1 code implementation18 Aug 2023 Tal Kadosh, Niranjan Hasabnis, Vy A. Vo, Nadav Schneider, Neva Krien, Abdul Wasay, Nesreen Ahmed, Ted Willke, Guy Tamir, Yuval Pinter, Timothy Mattson, Gal Oren

With easier access to powerful compute resources, there is a growing trend in the field of AI for software development to develop larger and larger language models (LLMs) to address a variety of programming tasks.

Code Completion

Memory in humans and deep language models: Linking hypotheses for model augmentation

no code implementations4 Oct 2022 Omri Raccah, Phoebe Chen, Ted L. Willke, David Poeppel, Vy A. Vo

The computational complexity of the self-attention mechanism in Transformer models significantly limits their ability to generalize over long temporal durations.

Slower is Better: Revisiting the Forgetting Mechanism in LSTM for Slower Information Decay

no code implementations12 May 2021 Hsiang-Yun Sherry Chien, Javier S. Turek, Nicole Beckage, Vy A. Vo, Christopher J. Honey, Ted L. Willke

Altogether, we found that LSTM with the proposed forget gate can learn long-term dependencies, outperforming other recurrent networks in multiple domains; such gating mechanism can be integrated into other architectures for improving the learning of long timescale information in recurrent neural networks.

Image Classification Language Modelling

Multi-timescale Representation Learning in LSTM Language Models

no code implementations ICLR 2021 Shivangi Mahto, Vy A. Vo, Javier S. Turek, Alexander G. Huth

Earlier work has demonstrated that dependencies in natural language tend to decay with distance between words according to a power law.

Language Modelling Representation Learning

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