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Found 7 papers, 5 papers with code
Efficient k-Nearest-Neighbor Machine Translation with Dynamic Retrieval
In this paper, we first conduct a preliminary study to reveal two key limitations of $k$NN-MT-AR: 1) the optimization gap leads to inaccurate estimation of $\lambda$ for determining $k$NN retrieval skipping, and 2) using a fixed threshold fails to accommodate the dynamic demands for $k$NN retrieval at different timesteps.
Retaining Key Information under High Compression Ratios: Query-Guided Compressor for LLMs
This decline can be attributed to the loss of key information during the compression process.
PolyLM: An Open Source Polyglot Large Language Model
Large language models (LLMs) demonstrate remarkable ability to comprehend, reason, and generate following nature language instructions.
Bridging the Domain Gaps in Context Representations for k-Nearest Neighbor Neural Machine Translation
$k$-Nearest neighbor machine translation ($k$NN-MT) has attracted increasing attention due to its ability to non-parametrically adapt to new translation domains.
Full-Resolution Network and Dual-Threshold Iteration for Retinal Vessel and Coronary Angiograph Segmentation
The results demonstrate that FR-UNet outperforms state-of-the-art methods by achieving the highest Sen, AUC, F1, and IOU on most of the above-mentioned datasets with fewer parameters, and that DTI enhances vessel connectivity while greatly improving sensitivity.
Ranked #1 on
Retinal Vessel Segmentation
on DRIVE
Fast List Decoders for Polarization-Adjusted Convolutional (PAC) Codes
Moreover, fast list decoding with four types of constituent nodes can further reduce decoding latency with negligible performance degradation.
Information Theory Information Theory
