Zobrazeno 1 - 10
of 3 543
pro vyhledávání: '"Madureira P"'
This paper introduces ROSAR, a novel framework enhancing the robustness of deep learning object detection models tailored for side-scan sonar (SSS) images, generated by autonomous underwater vehicles using sonar sensors. By extending our prior work o
Externí odkaz:
http://arxiv.org/abs/2410.10554
Autor:
Beyer, Anne, Chalamalasetti, Kranti, Hakimov, Sherzod, Madureira, Brielen, Sadler, Philipp, Schlangen, David
It has been established in recent work that Large Language Models (LLMs) can be prompted to "self-play" conversational games that probe certain capabilities (general instruction following, strategic goal orientation, language understanding abilities)
Externí odkaz:
http://arxiv.org/abs/2405.20859
Autor:
Madureira, Brielen, Schlangen, David
Active participation in a conversation is key to building common ground, since understanding is jointly tailored by producers and recipients. Overhearers are deprived of the privilege of performing grounding acts and can only conjecture about intende
Externí odkaz:
http://arxiv.org/abs/2405.01139
"A Three-Field Domain Decomposition Method" is the title of a seminal paper by F. Brezzi and L. D. Marini which introduces a three-field formulation for elliptic partial differential equations. Based on that, we propose the Multiscale-Hybrid-Hybrid M
Externí odkaz:
http://arxiv.org/abs/2404.16978
In this paper we present YOLOX-ViT, a novel object detection model, and investigate the efficacy of knowledge distillation for model size reduction without sacrificing performance. Focused on underwater robotics, our research addresses key questions
Externí odkaz:
http://arxiv.org/abs/2403.09313
Incremental models that process sentences one token at a time will sometimes encounter points where more than one interpretation is possible. Causal models are forced to output one interpretation and continue, whereas models that can revise may edit
Externí odkaz:
http://arxiv.org/abs/2402.13113
Autor:
Madureira, Brielen, Schlangen, David
Clarification requests are a mechanism to help solve communication problems, e.g. due to ambiguity or underspecification, in instruction-following interactions. Despite their importance, even skilful models struggle with producing or interpreting suc
Externí odkaz:
http://arxiv.org/abs/2401.17039
In this manuscript we propose and analyze an implicit two-point type method (or inertial method) for obtaining stable approximate solutions to linear ill-posed operator equations. The method is based on the iterated Tikhonov (iT) scheme. We establish
Externí odkaz:
http://arxiv.org/abs/2401.15213
In NLP, incremental processors produce output in instalments, based on incoming prefixes of the linguistic input. Some tokens trigger revisions, causing edits to the output hypothesis, but little is known about why models revise when they revise. A p
Externí odkaz:
http://arxiv.org/abs/2310.18229
Autor:
Jéssica de Andrade-da-Costa, Michelle de-Souza-Ferreira, Nathália Campos dos Santos Touça, Annie Cristhine Moraes Sousa-Squiavinato, Sheila Coelho Soares-Lima, José Andrés Morgado-Díaz, Julio Cesar Madureira de-Freitas-Junior
Publikováno v:
Discover Oncology, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Colorectal cancer (CRC) has a high mortality rate, resulting from the processes of metastasis and disease recurrence. Cancer stem cells (CSCs) are believed to be crucial for both processes, as they ensure the maintenance of the tumor bulk, i
Externí odkaz:
https://doaj.org/article/f4d505dc498146d690147f1cad3c59cc
