Zobrazeno 1 - 10
of 945
pro vyhledávání: '"Loreggia, A."'
Autor:
Pallagani, Vishal, Roy, Kaushik, Muppasani, Bharath, Fabiano, Francesco, Loreggia, Andrea, Murugesan, Keerthiram, Srivastava, Biplav, Rossi, Francesca, Horesh, Lior, Sheth, Amit
Publikováno v:
Proceedings of the International Conference on Automated Planning and Scheduling, 34(1), 432-444 (2024)
Automated Planning and Scheduling is among the growing areas in Artificial Intelligence (AI) where mention of LLMs has gained popularity. Based on a comprehensive review of 126 papers, this paper investigates eight categories based on the unique appl
Externí odkaz:
http://arxiv.org/abs/2401.02500
Autor:
Pont, Thiago Dal, Galli, Federico, Loreggia, Andrea, Pisano, Giuseppe, Rovatti, Riccardo, Sartor, Giovanni
We present some initial results of a large-scale Italian project called PRODIGIT which aims to support tax judges and lawyers through digital technology, focusing on AI. We have focused on generation of summaries of judicial decisions and on the extr
Externí odkaz:
http://arxiv.org/abs/2308.04416
Autor:
Ganapini, Marianna B., Fabiano, Francesco, Horesh, Lior, Loreggia, Andrea, Mattei, Nicholas, Murugesan, Keerthiram, Pallagani, Vishal, Rossi, Francesca, Srivastava, Biplav, Venable, Brent
Nudging is a behavioral strategy aimed at influencing people's thoughts and actions. Nudging techniques can be found in many situations in our daily lives, and these nudging techniques can targeted at human fast and unconscious thinking, e.g., by usi
Externí odkaz:
http://arxiv.org/abs/2307.07628
Autor:
Pallagani, Vishal, Muppasani, Bharath, Murugesan, Keerthiram, Rossi, Francesca, Srivastava, Biplav, Horesh, Lior, Fabiano, Francesco, Loreggia, Andrea
Automated planning is concerned with developing efficient algorithms to generate plans or sequences of actions to achieve a specific goal in a given environment. Emerging Large Language Models (LLMs) can answer questions, write high-quality programmi
Externí odkaz:
http://arxiv.org/abs/2305.16151
Autor:
Fabiano, Francesco, Pallagani, Vishal, Ganapini, Marianna Bergamaschi, Horesh, Lior, Loreggia, Andrea, Murugesan, Keerthiram, Rossi, Francesca, Srivastava, Biplav
The concept of Artificial Intelligence has gained a lot of attention over the last decade. In particular, AI-based tools have been employed in several scenarios and are, by now, pervading our everyday life. Nonetheless, most of these systems lack man
Externí odkaz:
http://arxiv.org/abs/2303.04283
Autor:
Pallagani, Vishal, Muppasani, Bharath, Murugesan, Keerthiram, Rossi, Francesca, Horesh, Lior, Srivastava, Biplav, Fabiano, Francesco, Loreggia, Andrea
Large Language Models (LLMs) have been the subject of active research, significantly advancing the field of Natural Language Processing (NLP). From BERT to BLOOM, LLMs have surpassed state-of-the-art results in various natural language tasks such as
Externí odkaz:
http://arxiv.org/abs/2212.08681
Autor:
Glazier, Arie, Loreggia, Andrea, Mattei, Nicholas, Rahgooy, Taher, Rossi, Francesca, Venable, Brent
Many real-life scenarios require humans to make difficult trade-offs: do we always follow all the traffic rules or do we violate the speed limit in an emergency? These scenarios force us to evaluate the trade-off between collective rules and norms wi
Externí odkaz:
http://arxiv.org/abs/2202.10407
Publikováno v:
IEEE Access, Vol 12, Pp 74218-74229 (2024)
The analysis of road continuity in satellite images is a complex challenge. This is due to the difficulty in identifying the directional vector of road sections, especially when the satellite view of roads is obstructed by trees or other structures.
Externí odkaz:
https://doaj.org/article/cac40f03d5c34895ae9dc2b01a63f8ba
Autor:
Awad, Edmond, Levine, Sydney, Loreggia, Andrea, Mattei, Nicholas, Rahwan, Iyad, Rossi, Francesca, Talamadupula, Kartik, Tenenbaum, Joshua, Kleiman-Weiner, Max
Publikováno v:
Journal of Autonomous Agents and Multi-Agent Systems 38, 35 (2024)
One of the most remarkable things about the human moral mind is its flexibility. We can make moral judgments about cases we have never seen before. We can decide that pre-established rules should be broken. We can invent novel rules on the fly. Captu
Externí odkaz:
http://arxiv.org/abs/2201.07763
Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments
Autor:
Ganapini, Marianna B., Campbell, Murray, Fabiano, Francesco, Horesh, Lior, Lenchner, Jon, Loreggia, Andrea, Mattei, Nicholas, Rahgooy, Taher, Rossi, Francesca, Srivastava, Biplav, Venable, Brent
Current AI systems lack several important human capabilities, such as adaptability, generalizability, self-control, consistency, common sense, and causal reasoning. We believe that existing cognitive theories of human decision making, such as the thi
Externí odkaz:
http://arxiv.org/abs/2201.07050