Oceania
Semantic Density: Uncertainty Quantification for Large Language Models through Confidence Measurement in Semantic Space
A new framework is proposed in this paper to address these issues.
Certified Adversarial Robustness via Randomized α-Smoothing for Regression Models
Certified adversarial robustness of large-scale deep networks has progressed substantially after the introduction of randomized smoothing.
Why some people cannot move on from the death of a loved one
Prolonged grief disorder affects around 1 in 20 people, and we're starting to understand the neuroscience behind it For most people, the intense sting of grief eases with time. For some, however, persistent and painful grief remains, developing into prolonged grief disorder. A new review of the condition, which affects around 5 per cent of bereaved people, sheds light on how it develops. This could help doctors predict which recently bereaved people will benefit from extra support. The decision to include prolonged grief disorder (PGD) in the American Psychiatric Association's diagnostic manual in 2022 sparked intense debate over whether it was pathologising a normal human response to loss and imposing an arbitrary timeline on what constitutes "normal" grief.
PROSPECT PTMs: Rich Labeled Tandem Mass Spectrometry Dataset of Modified Peptides for Machine Learning in Proteomics
The field of proteomics aims to study and understand the complex landscape of proteins present within a biological system.
VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images
Hence, we consider asking a VLM to provide the scientific name of the organism shown in a given image. There are two types of questions that we consider for this task. First, we consider open-ended questions, where we do not provide any answer choices (or options) to the VLM in the input prompt.
VastTrack: Vast Category Visual Object Tracking
V astTrack consists of a few attractive properties: (1) V ast Object Category . In particular, it covers targets from 2,115 categories, significantly surpassing object classes of existing popular benchmarks ( e.g ., GOT -10k with 563 classes and LaSOT with 70 categories). Through providing such vast object classes, we expect to learn more general object tracking.