Zobrazeno 1 - 10
of 3 259
pro vyhledávání: '"Semedo AT"'
Vision Language Models (VLMs) have demonstrated strong capabilities across various visual understanding and reasoning tasks. However, their real-world deployment is often constrained by high latency during inference due to substantial compute require
Externí odkaz:
http://arxiv.org/abs/2411.03312
The growing demand for surveillance in public spaces presents significant challenges due to the shortage of human resources. Current AI-based video surveillance systems heavily rely on core computer vision models that require extensive finetuning, wh
Externí odkaz:
http://arxiv.org/abs/2410.21113
Conversational systems must be robust to user interactions that naturally exhibit diverse conversational traits. Capturing and simulating these diverse traits coherently and efficiently presents a complex challenge. This paper introduces Multi-Trait
Externí odkaz:
http://arxiv.org/abs/2410.12891
Guiding users through complex procedural plans is an inherently multimodal task in which having visually illustrated plan steps is crucial to deliver an effective plan guidance. However, existing works on plan-following language models (LMs) often ar
Externí odkaz:
http://arxiv.org/abs/2409.19074
Vision-language models (VLMs) such as CLIP are trained via contrastive learning between text and image pairs, resulting in aligned image and text embeddings that are useful for many downstream tasks. A notable drawback of CLIP, however, is that the r
Externí odkaz:
http://arxiv.org/abs/2409.09721
Autor:
Rodrigues-Silva C, Semedo AT, Neri HFS, Vianello RP, Galaviz-Hernández C, Sosa-Macías M, de Brito RB, Ghedini PC
Publikováno v:
Neuropsychiatric Disease and Treatment, Vol Volume 16, Pp 427-432 (2020)
Christielly Rodrigues-Silva,1 Agostinho Tavares Semedo,1 Hiasmin Franciely da Silva Neri,1 Rosana Pereira Vianello,2 Carlos Galaviz-Hernández,3 Martha Sosa-Macías,3 Rodrigo Bernini de Brito,1,4 Paulo César Ghedini1 1Department of Pharmacology, Ins
Externí odkaz:
https://doaj.org/article/a393e8f88f9d499b977944a7dc49c355
Significant strides have been made in natural language tasks, largely attributed to the emergence of powerful large language models (LLMs). These models, pre-trained on extensive and diverse corpora, have become increasingly capable of comprehending
Externí odkaz:
http://arxiv.org/abs/2402.12969
Training Large Language Models (LLMs) to follow user instructions has been shown to supply the LLM with ample capacity to converse fluently while being aligned with humans. Yet, it is not completely clear how an LLM can lead a plan-grounded conversat
Externí odkaz:
http://arxiv.org/abs/2402.01053
Autor:
Ribeiro, Neuza, Gomes, Daniel, Gomes, Gabriela Pedro, Ullah, Atiat, Dias Semedo, Ana Suzete, Singh, Sharda
Publikováno v:
International Journal of Organizational Analysis, 2024, Vol. 32, Issue 10, pp. 2339-2356.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJOA-09-2023-3980
Autor:
Ferreira, Rafael, Tavares, Diogo, Silva, Diogo, Valério, Rodrigo, Bordalo, João, Simões, Inês, Ramos, Vasco, Semedo, David, Magalhães, João
In this report, we describe the vision, challenges, and scientific contributions of the Task Wizard team, TWIZ, in the Alexa Prize TaskBot Challenge 2022. Our vision, is to build TWIZ bot as an helpful, multimodal, knowledgeable, and engaging assista
Externí odkaz:
http://arxiv.org/abs/2310.02118