Results 291 to 300 of about 467,421 (344)

Decoding brain-wide signatures of uninformed choices for BCI assisted decision-making

open access: yes
Gimple S   +10 more
europepmc   +1 more source

Dynamic and task-dependent decoding of the human attentional spotlight from MEG

open access: yes
Mostafalu M   +5 more
europepmc   +1 more source
Some of the next articles are maybe not open access.

Related searches:

Medical Image Segmentation via Cascaded Attention Decoding

IEEE Workshop/Winter Conference on Applications of Computer Vision, 2023
Transformers have shown great promise in medical image segmentation due to their ability to capture long-range dependencies through self-attention. However, they lack the ability to learn the local (contextual) relations among pixels.
Md Mostafijur Rahman, R. Marculescu
semanticscholar   +1 more source

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

International Conference on Machine Learning
Large Language Models (LLMs) employ auto-regressive decoding that requires sequential computation, with each step reliant on the previous one's output.
Tianle Cai   +6 more
semanticscholar   +1 more source

DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving

USENIX Symposium on Operating Systems Design and Implementation
DistServe improves the performance of large language models (LLMs) serving by disaggregating the prefill and decoding computation. Existing LLM serving systems colocate the two phases and batch the computation of prefill and decoding across all users and
Yinmin Zhong   +7 more
semanticscholar   +1 more source

Decoding CODECs

Journal of Telemedicine and Telecare, 2008
Summary A codec is the mechanism by which video and audio signals are compressed to conserve bandwidth before transmission across a telecommunication network. It may be implemented either in hardware or software. In the past, manufacturers sometimes used proprietary codecs that were incompatible with those from other manufacturers.
Rex E, Gantenbein, Barbara J, Robinson
openaire   +2 more sources

Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding

Annual Meeting of the Association for Computational Linguistics
To mitigate the high inference latency stemming from autoregressive decoding in Large Language Models (LLMs), Speculative Decoding has emerged as a novel decoding paradigm for LLM inference.
Heming Xia   +8 more
semanticscholar   +1 more source

Home - About - Disclaimer - Privacy