Search Results for author:
Found 6 papers, 3 papers with code
LoMA: Lossless Compressed Memory Attention
We introduce Lossless Compressed Memory Attention (LoMA), a novel approach that enables lossless compression of the KV cache, thereby reducing the memory and computational demands during autoregressive generation.
DoNet: Deep De-overlapping Network for Cytology Instance Segmentation
Cell instance segmentation in cytology images has significant importance for biology analysis and cancer screening, while remains challenging due to 1) the extensive overlapping translucent cell clusters that cause the ambiguous boundaries, and 2) the confusion of mimics and debris as nuclei.
Explainable Information Retrieval: A Survey
Explainable information retrieval is an emerging research area aiming to make transparent and trustworthy information retrieval systems.
BERT Rankers are Brittle: a Study using Adversarial Document Perturbations
The aim of our algorithms is to add/replace a small number of tokens to a highly relevant or non-relevant document to cause a large rank demotion or promotion.
WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma
According to the technical reports of the top-tier teams, CAM is still the most popular approach in WSSS.
Data Augmentation
Weakly supervised Semantic Segmentation
+1
A Black-Scholes user's guide to the Bachelier model
To cope with the negative oil futures price caused by the COVID-19 recession, global commodity futures exchanges temporarily switched the option model from Black--Scholes to Bachelier in 2020.
