Papers by Niraj Jha

1 papers
DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling (2024.naacl-long)

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Challenge: Rapid explosion in model sizes has resulted in high inference times . open-source LLMs are democratizing research in natural language processing .
Approach: They propose a suite of multi-token prediction language models that reduce net inference times by leveraging traditional autoregressive weights.
Outcome: The proposed model achieves same-quality generated text as baseline (Pythia-6.9B) with only 5.87% and 2.67% parameter and training time overheads.

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