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Niraj Jha

2 accepted papers

2024

DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling

NAACL 2024long

Traditional language models operate autoregressively, i.e., they predict one token at a time. Rapid explosion in model sizes has resulted in high inference times. In this work, we propose DynaMo, a suite of multi-token prediction language models that reduce net inference times. Our models *dynamical…

2023

Im-Promptu: In-Context Composition from Image Prompts

NeurIPS 2023poster

Large language models are few-shot learners that can solve diverse tasks from a handful of demonstrations. This implicit understanding of tasks suggests that the attention mechanisms over word tokens may play a role in analogical reasoning. In this work, we investigate whether analogical reasoning c…

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