Viral News - CybAI news

21 Aug

Improving VTE Identification through Language Models from Radiology Reports: A Comparative Study of Mamba, Phi-3 Mini, and BERT

stp2y0 CommentsViral News

arXiv:2408.09043v1 Announce Type: new Abstract: Venous thromboembolism (VTE) is a critical cardiovascular condition, encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE). Accurate and timely identification of VTE is essential for effective medical care. This study builds upon our previous work, which addressed VTE detection using deep learning methods for DVT and a hybrid approach combining deep learning and rule-based classification for PE. Our earlier approaches, while effective, had two major limitations: they were complex and required expert involvement for feature engineering of the rule set. To overcome these challenges, we utilize the Mamba architecture-based classifier. This model achieves remarkable…

21 Aug

ADen: Adaptive Density Representations for Sparse-view Camera Pose Estimation

stp2y0 CommentsViral News

arXiv:2408.09042v1 Announce Type: new Abstract: Recovering camera poses from a set of images is a foundational task in 3D computer vision, which powers key applications such as 3D scene/object reconstructions. Classic methods often depend on feature correspondence, such as keypoints, which require the input images to have large overlap and small viewpoint changes. Such requirements present considerable challenges in scenarios with sparse views. Recent data-driven approaches aim to directly output camera poses, either through regressing the 6DoF camera poses or formulating rotation as a probability distribution. However, each approach has its limitations. On one hand, directly regressing the camera poses…

21 Aug

CogLM: Tracking Cognitive Development of Large Language Models

stp2y0 CommentsViral News

arXiv:2408.09150v1 Announce Type: new Abstract: Piaget's Theory of Cognitive Development (PTC) posits that the development of cognitive levels forms the foundation for human learning across various abilities. As Large Language Models (LLMs) have recently shown remarkable abilities across a wide variety of tasks, we are curious about the cognitive levels of current LLMs: to what extent they have developed and how this development has been achieved. To this end, we construct a benchmark CogLM (Cognitive Ability Evaluation for Language Model) based on PTC to assess the cognitive levels of LLMs. CogLM comprises 1,220 questions spanning 10 cognitive abilities crafted by…

21 Aug

Appen CEO Ryan Kolln Discusses the Data Annotation and Labeling Biz on the Big Data Debrief

stp2y0 CommentsViral News

Appen CEO Ryan Kolln recently joined us on the innaugural edition of the Big Data Debrief to talk about Appen’s work in data annotation and labeling, and how the rise of GenAI will impact the world’s appetite for trusted, human-curated data. Appen is one of the leading providers of data annotation and labeling (DAL) solutions. The company, which is traded on the Australian Securities Exchange, has been providing DAL solutions for nearly 30 years. Kolln took the CEO and managing director position this February and recently spoke with Datanami about the company, how the market for DAL solutions is changing,…

20 Aug

Error Bounds For Gaussian Process Regression Under Bounded Support Noise With Applications To Safety Certification

stp2y0 CommentsViral News

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

20 Aug

Multi Teacher Privileged Knowledge Distillation for Multimodal Expression Recognition

stp2y0 CommentsViral News

[Submitted on 16 Aug 2024] View a PDF of the paper titled Multi Teacher Privileged Knowledge Distillation for Multimodal Expression Recognition, by Muhammad Haseeb Aslam and 3 other authors View PDF HTML (experimental) Abstract:Human emotion is a complex phenomenon conveyed and perceived through facial expressions, vocal tones, body language, and physiological signals. Multimodal emotion recognition systems can perform well because they can learn complementary and redundant semantic information from diverse sensors. In real-world scenarios, only a subset of the modalities employed for training may be available at test time. Learning privileged information allows a model to exploit data from additional…

20 Aug

Improving Rare Word Translation With Dictionaries and Attention Masking

stp2y0 CommentsViral News

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Source link lol

20 Aug

Cloudian Partners with Lenovo for EPYC All-Flash ‘HyperStore’

stp2y0 CommentsViral News

Cloudian and Lenovo today announced they’re teaming up to deliver a new HyperStore cluster designed to run big data, AI, and HPC workloads. Each HyperStore cluster will be composed of six Lenovo ThinkSystem SR635 V3 servers equipped with AMD EPYC 9454P processors and flash drives. The cluster will come pre-loaded with Cloudian’s S3-comptable object storage system. The combination of AMD processors and all-flash storage will allow the HyperStore cluster to read data at speeds up to 28.7 GB/s reads and write data at speeds up to 18.4 GB/s. According to Cloudian, testing shows the all-flash setup is 74% more efficient…

20 Aug

AdaRank: Disagreement Based Module Rank Prediction for Low-rank Adaptation

stp2y0 CommentsViral News

arXiv:2408.09015v1 Announce Type: new Abstract: With the rise of language and multimodal models of ever-increasing size, pretraining a general-purpose foundational model and adapting it to downstream tasks has become common practice. To this end, adaptation efficiency can be a critical bottleneck given the large model sizes, hence efficient finetuning methods such as LoRA have become prevalent. However, LoRA is typically applied with the same rank across all model layers, despite mounting evidence from transfer learning literature that during finetuning, later layers diverge more from pretrained weights. Inspired by the theory and observations around feature learning and module criticality, we develop…

20 Aug

Comparative Performance Analysis of Transformer-Based Pre-Trained Models for Detecting Keratoconus Disease

stp2y0 CommentsViral News

[Submitted on 16 Aug 2024] View a PDF of the paper titled Comparative Performance Analysis of Transformer-Based Pre-Trained Models for Detecting Keratoconus Disease, by Nayeem Ahmed and 5 other authors View PDF Abstract:This study compares eight pre-trained CNNs for diagnosing keratoconus, a degenerative eye disease. A carefully selected dataset of keratoconus, normal, and suspicious cases was used. The models tested include DenseNet121, EfficientNetB0, InceptionResNetV2, InceptionV3, MobileNetV2, ResNet50, VGG16, and VGG19. To maximize model training, bad sample removal, resizing, rescaling, and augmentation were used. The models were trained with similar parameters, activation function, classification function, and optimizer to compare performance. To…