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pro vyhledávání: '"Koopman A"'
Generation with source attribution is important for enhancing the verifiability of retrieval-augmented generation (RAG) systems. However, existing approaches in RAG primarily link generated content to document-level references, making it challenging
Externí odkaz:
http://arxiv.org/abs/2412.14457
2D Matryoshka Training is an advanced embedding representation training approach designed to train an encoder model simultaneously across various layer-dimension setups. This method has demonstrated higher effectiveness in Semantic Text Similarity (S
Externí odkaz:
http://arxiv.org/abs/2411.17299
Effective approaches that can scale embedding model depth (i.e. layers) and embedding size allow for the creation of models that are highly scalable across different computational resources and task requirements. While the recently proposed 2D Matryo
Externí odkaz:
http://arxiv.org/abs/2410.13230
The emergence of Vec2Text -- a method for text embedding inversion -- has raised serious privacy concerns for dense retrieval systems which use text embeddings. This threat comes from the ability for an attacker with access to embeddings to reconstru
Externí odkaz:
http://arxiv.org/abs/2410.06628
Currently, neural-network processing in machine learning applications relies on layer synchronization, whereby neurons in a layer aggregate incoming currents from all neurons in the preceding layer, before evaluating their activation function. This i
Externí odkaz:
http://arxiv.org/abs/2408.05098
The Shared Task on Large-Scale Radiology Report Generation (RRG24) aims to expedite the development of assistive systems for interpreting and reporting on chest X-ray (CXR) images. This task challenges participants to develop models that generate the
Externí odkaz:
http://arxiv.org/abs/2408.03500
We propose a new statistical reduced complexity climate model. The centerpiece of the model consists of a set of physical equations for the global climate system which we show how to cast in non-linear state space form. The parameters in the model ar
Externí odkaz:
http://arxiv.org/abs/2407.04351
Clinical documentation is an important aspect of clinicians' daily work and often demands a significant amount of time. The BioNLP 2024 Shared Task on Streamlining Discharge Documentation (Discharge Me!) aims to alleviate this documentation burden by
Externí odkaz:
http://arxiv.org/abs/2407.02723
The goal of screening prioritisation in systematic reviews is to identify relevant documents with high recall and rank them in early positions for review. This saves reviewing effort if paired with a stopping criterion, and speeds up review completio
Externí odkaz:
http://arxiv.org/abs/2407.00635
Autor:
Bhimani, Sanah, Lashner, Jack, Aiola, Simone, Crowley, Kevin T., Galitzki, Nicholas, Geras, Remington G., Harrington, Kathleen, Hasselfield, Matthew, Johnson, Alyssa, Koopman, Brian J., Nakata, Hironobu, Newburgh, Laura, Nguyen, David V., Randall, Michael J., Silva-Feaver, Max
The Simons Observatory (SO) is a Cosmic Microwave Background experiment located in the Atacama Desert in Chile. SO consists of three small aperture telescopes (SATs) and one large aperture telescope (LAT) with a total of 60,000 detectors in six frequ
Externí odkaz:
http://arxiv.org/abs/2406.19576