Zobrazeno 1 - 10
of 5 979
pro vyhledávání: '"Mureşan, A."'
Publikováno v:
A&A, Volume number 692, Published 2024-12-06
The rich diversity of multi-planetary systems and their architectures is greatly contrasted by the uniformity exhibited within many of these systems. Previous studies have shown that compact Kepler systems tend to exhibit a peas-in-a-pod architecture
Externí odkaz:
http://arxiv.org/abs/2410.23399
Autor:
Alshomary, Milad, Ri, Narutatsu, Apidianaki, Marianna, Patel, Ajay, Muresan, Smaranda, McKeown, Kathleen
Recent state-of-the-art authorship attribution methods learn authorship representations of texts in a latent, non-interpretable space, hindering their usability in real-world applications. Our work proposes a novel approach to interpreting these lear
Externí odkaz:
http://arxiv.org/abs/2409.07072
Explanations form the foundation of knowledge sharing and build upon communication principles, social dynamics, and learning theories. We focus specifically on conversational approaches for explanations because the context is highly adaptive and inte
Externí odkaz:
http://arxiv.org/abs/2406.18512
Autor:
Samadarshi, Prisha, Mustafa, Mariam, Kulkarni, Anushka, Rothkopf, Raven, Chakrabarty, Tuhin, Muresan, Smaranda
The New York Times Connections game has emerged as a popular and challenging pursuit for word puzzle enthusiasts. We collect 438 Connections games to evaluate the performance of state-of-the-art large language models (LLMs) against expert and novice
Externí odkaz:
http://arxiv.org/abs/2406.11012
Large Vision-Language Models (VLMs) have demonstrated strong capabilities in tasks requiring a fine-grained understanding of literal meaning in images and text, such as visual question-answering or visual entailment. However, there has been little ex
Externí odkaz:
http://arxiv.org/abs/2405.01474
Digital education has gained popularity in the last decade, especially after the COVID-19 pandemic. With the improving capabilities of large language models to reason and communicate with users, envisioning intelligent tutoring systems (ITSs) that ca
Externí odkaz:
http://arxiv.org/abs/2404.04728
Recognizing fallacies is crucial for ensuring the quality and validity of arguments across various domains. However, computational fallacy recognition faces challenges due to the diverse genres, domains, and types of fallacies found in datasets. This
Externí odkaz:
http://arxiv.org/abs/2311.09552
Autor:
Yang, Chenghao, Chakrabarty, Tuhin, Hochstatter, Karli R, Slavin, Melissa N, El-Bassel, Nabila, Muresan, Smaranda
In the last decade, the United States has lost more than 500,000 people from an overdose involving prescription and illicit opioids making it a national public health emergency (USDHHS, 2017). Medical practitioners require robust and timely tools tha
Externí odkaz:
http://arxiv.org/abs/2311.09066
Natural language instructions are a powerful interface for editing the outputs of text-to-image diffusion models. However, several challenges need to be addressed: 1) underspecification (the need to model the implicit meaning of instructions) 2) grou
Externí odkaz:
http://arxiv.org/abs/2310.19145
Social norms fundamentally shape interpersonal communication. We present NormDial, a high-quality dyadic dialogue dataset with turn-by-turn annotations of social norm adherences and violations for Chinese and American cultures. Introducing the task o
Externí odkaz:
http://arxiv.org/abs/2310.14563