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cs.AI2026
Full-bandwidth transformer
Xi Wang, Ziyang Cai, Zheng Zhan +5
Autoregressive transformers compute along two axes: horizontally across generated tokens, and vertically through model depth. Dense attention gives each token broad horizontal acce…
cs.AI2026
Generalized Parallel Scaling with Interdependent Generations
Harry Dong, David Brandfonbrener, Eryk Helenowski +5
Parallel LLM inference scaling involves sampling a set of responses for a single input prompt. However, these parallel responses tend to be generated independently from e…
cs.AI2024
Towards Low-bit Communication for Tensor Parallel LLM Inference
Harry Dong, Tyler Johnson, Minsik Cho +1
Tensor parallelism provides an effective way to increase server large language model (LLM) inference efficiency despite adding an additional communication cost. However, as server…