BLT-D, BLT-S, and BLT-DV use block-wise diffusion training and speculative verification to enable parallel byte generation in byte-level LMs, cutting memory-bandwidth cost by over 50%.
In: Findings of the Association for Computational Linguistics: EMNLP 2024
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
EchoSonar-R is a multi-view VLM for echocardiography that jointly does disease classification and report generation via SFT followed by GRPO reinforcement learning, reporting accuracy gains on private and public data.
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Fast Byte Latent Transformer
BLT-D, BLT-S, and BLT-DV use block-wise diffusion training and speculative verification to enable parallel byte generation in byte-level LMs, cutting memory-bandwidth cost by over 50%.
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EchoSonar-R: A Multi-View Reasoning-Enabled Model for Disease Classification and Report Generation in Echocardiography
EchoSonar-R is a multi-view VLM for echocardiography that jointly does disease classification and report generation via SFT followed by GRPO reinforcement learning, reporting accuracy gains on private and public data.