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pro vyhledávání: '"A, Eshghi"'
In dialogue, the addressee may initially misunderstand the speaker and respond erroneously, often prompting the speaker to correct the misunderstanding in the next turn with a Third Position Repair (TPR). The ability to process and respond appropriat
Externí odkaz:
http://arxiv.org/abs/2409.14247
Autor:
Pantazopoulos, Georgios, Nikandrou, Malvina, Suglia, Alessandro, Lemon, Oliver, Eshghi, Arash
This study explores replacing Transformers in Visual Language Models (VLMs) with Mamba, a recent structured state space model (SSM) that demonstrates promising performance in sequence modeling. We test models up to 3B parameters under controlled cond
Externí odkaz:
http://arxiv.org/abs/2409.05395
Autor:
Suglia, Alessandro, Greco, Claudio, Baker, Katie, Part, Jose L., Papaioannou, Ioannis, Eshghi, Arash, Konstas, Ioannis, Lemon, Oliver
AI personal assistants deployed via robots or wearables require embodied understanding to collaborate with humans effectively. However, current Vision-Language Models (VLMs) primarily focus on third-person view videos, neglecting the richness of egoc
Externí odkaz:
http://arxiv.org/abs/2406.13807
An effective method for combining frozen large language models (LLM) and visual encoders involves a resampler module that creates a `visual prompt' which is provided to the LLM, along with the textual prompt. While this approach has enabled impressiv
Externí odkaz:
http://arxiv.org/abs/2404.13594
Autor:
Pantazopoulos, Georgios, Nikandrou, Malvina, Parekh, Amit, Hemanthage, Bhathiya, Eshghi, Arash, Konstas, Ioannis, Rieser, Verena, Lemon, Oliver, Suglia, Alessandro
Interactive and embodied tasks pose at least two fundamental challenges to existing Vision & Language (VL) models, including 1) grounding language in trajectories of actions and observations, and 2) referential disambiguation. To tackle these challen
Externí odkaz:
http://arxiv.org/abs/2311.04067
Autor:
Eshghi, Arash, Ashrafzadeh, Arash
In conversation, speakers produce language incrementally, word by word, while continuously monitoring the appropriateness of their own contribution in the dynamically unfolding context of the conversation; and this often leads them to repair their ow
Externí odkaz:
http://arxiv.org/abs/2308.11683
Autor:
Shahab Eshghi, Hamed Rajabi, Natalia Matushkina, Lisa Claußen, Johannes Poser, Thies H. Büscher, Stanislav N. Gorb
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-17 (2024)
Abstract WingAnalogy is a computer tool for automated insect wing morphology and asymmetry analysis. It facilitates project management, enabling users to import pairs of wing images obtained from individual insects, such as left and right, fore- and
Externí odkaz:
https://doaj.org/article/1b358f9e4aca451fa28699d84e9f6ca9
Autor:
Nafiseh Mortazavi, Alireza Eshghi, Ardalan Ahmadvand, Gholamreza Bahoush, Parnian Ahmadvand, Ali Ghasemi, Kazem Ghaffari
Publikováno v:
BMC Nephrology, Vol 25, Iss 1, Pp 1-5 (2024)
Abstract Background Horseshoe kidney is the most common renal fusion anomaly, and Wilms tumor is the most frequent renal malignancy in children. The occurrence of Wilms tumor in association with horseshoe kidney is a scarce anomaly. However, the aris
Externí odkaz:
https://doaj.org/article/9b772d9451ed4b6d891ba026e514378d
The ability to handle miscommunication is crucial to robust and faithful conversational AI. People usually deal with miscommunication immediately as they detect it, using highly systematic interactional mechanisms called repair. One important type of
Externí odkaz:
http://arxiv.org/abs/2307.16689
Referential ambiguities arise in dialogue when a referring expression does not uniquely identify the intended referent for the addressee. Addressees usually detect such ambiguities immediately and work with the speaker to repair it using meta-communi
Externí odkaz:
http://arxiv.org/abs/2307.15554