Search Results for author: Shivchander Sudalairaj

Found 5 papers, 1 papers with code

LAB: Large-Scale Alignment for ChatBots

no code implementations2 Mar 2024 Shivchander Sudalairaj, Abhishek Bhandwaldar, Aldo Pareja, Kai Xu, David D. Cox, Akash Srivastava

This work introduces LAB (Large-scale Alignment for chatBots), a novel methodology designed to overcome the scalability challenges in the instruction-tuning phase of large language model (LLM) training.

Instruction Following Language Modelling +2

Multi-Symmetry Ensembles: Improving Diversity and Generalization via Opposing Symmetries

1 code implementation4 Mar 2023 Charlotte Loh, Seungwook Han, Shivchander Sudalairaj, Rumen Dangovski, Kai Xu, Florian Wenzel, Marin Soljacic, Akash Srivastava

In this work, we present Multi-Symmetry Ensembles (MSE), a framework for constructing diverse ensembles by capturing the multiplicity of hypotheses along symmetry axes, which explore the hypothesis space beyond stochastic perturbations of model weights and hyperparameters.

Diversity Representation Learning +1

Grafting Vision Transformers

no code implementations28 Oct 2022 Jongwoo Park, Kumara Kahatapitiya, Donghyun Kim, Shivchander Sudalairaj, Quanfu Fan, Michael S. Ryoo

In this paper, we present a simple and efficient add-on component (termed GrafT) that considers global dependencies and multi-scale information throughout the network, in both high- and low-resolution features alike.

Image Classification Instance Segmentation +3

On the Importance of Calibration in Semi-supervised Learning

no code implementations10 Oct 2022 Charlotte Loh, Rumen Dangovski, Shivchander Sudalairaj, Seungwook Han, Ligong Han, Leonid Karlinsky, Marin Soljacic, Akash Srivastava

State-of-the-art (SOTA) semi-supervised learning (SSL) methods have been highly successful in leveraging a mix of labeled and unlabeled data by combining techniques of consistency regularization and pseudo-labeling.

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