Papers by Yueen Ma

2 papers
VOLTA: Improving Generative Diversity by Variational Mutual Information Maximizing Autoencoder (2024.findings-naacl)

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Challenge: generative diversity is a critical yet underexplored issue in natural language generation . previous approaches to enhance diversity of Transformer models have been limited by their latent variables .
Approach: They propose a framework that bridges Transformer with VAE to enhance generative diversity.
Outcome: The proposed framework improves generative diversity while maintaining generative quality.
Astra: Efficient Transformer Architecture and Contrastive Dynamics Learning for Embodied Instruction Following (2025.emnlp-main)

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Challenge: Existing vision-language-action models rely on causal attention for processing sequences composed of interleaved segments from different modalities.
Approach: They propose a Transformer architecture featuring trajectory attention and learnable action queries that efficiently process segmented multimodal trajectories and predict actions for imitation learning.
Outcome: The proposed architecture performs better on three large-scale robot manipulation benchmarks than previous models.

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