Zobrazeno 1 - 10
of 549
pro vyhledávání: '"Shakarian, A."'
Autor:
Lee, Nathaniel, Ngu, Noel, Sahdev, Harshdeep Singh, Motaganahall, Pramod, Chowdhury, Al Mehdi Saadat, Xi, Bowen, Shakarian, Paulo
Predicting price spikes in critical metals such as Cobalt, Copper, Magnesium, and Nickel is crucial for mitigating economic risks associated with global trends like the energy transition and reshoring of manufacturing. While traditional models have f
Externí odkaz:
http://arxiv.org/abs/2410.12785
Recent advances in Hierarchical Multi-label Classification (HMC), particularly neurosymbolic-based approaches, have demonstrated improved consistency and accuracy by enforcing constraints on a neural model during training. However, such work assumes
Externí odkaz:
http://arxiv.org/abs/2407.15192
Autor:
Bavikadi, Divyagna, Aditya, Dyuman, Parkar, Devendra, Shakarian, Paulo, Mueller, Graham, Parvis, Chad, Simari, Gerardo I.
The ability to generate artificial human movement patterns while meeting location and time constraints is an important problem in the security community, particularly as it enables the study of the analog problem of detecting such patterns while main
Externí odkaz:
http://arxiv.org/abs/2407.06447
Autor:
Wei, Hua, Shakarian, Paulo, Lebiere, Christian, Draper, Bruce, Krishnaswamy, Nikhil, Nirenburg, Sergei
Metacognition is the concept of reasoning about an agent's own internal processes and was originally introduced in the field of developmental psychology. In this position paper, we examine the concept of applying metacognition to artificial intellige
Externí odkaz:
http://arxiv.org/abs/2406.12147
Autor:
Bavikadi, Divyagna, Agarwal, Ayushi, Ganta, Shashank, Chung, Yunro, Song, Lusheng, Qiu, Ji, Shakarian, Paulo
Recent advances in experimental methods have enabled researchers to collect data on thousands of analytes simultaneously. This has led to correlational studies that associated molecular measurements with diseases such as Alzheimer's, Liver, and Gastr
Externí odkaz:
http://arxiv.org/abs/2405.10345
Autor:
Mukherji, Kaustuv, Parkar, Devendra, Pokala, Lahari, Aditya, Dyuman, Shakarian, Paulo, Dorman, Clark
Recent advances in reinforcement learning (RL) have shown much promise across a variety of applications. However, issues such as scalability, explainability, and Markovian assumptions limit its applicability in certain domains. We observe that many o
Externí odkaz:
http://arxiv.org/abs/2310.06835
Classification of movement trajectories has many applications in transportation and is a key component for large-scale movement trajectory generation and anomaly detection which has key safety applications in the aftermath of a disaster or other exte
Externí odkaz:
http://arxiv.org/abs/2308.14250
Error prediction in large language models often relies on domain-specific information. In this paper, we present measures for quantification of error in the response of a large language model based on the diversity of responses to a given prompt - he
Externí odkaz:
http://arxiv.org/abs/2308.11189
Autor:
Aditya, Dyuman, Mukherji, Kaustuv, Balasubramanian, Srikar, Chaudhary, Abhiraj, Shakarian, Paulo
The growing popularity of neuro symbolic reasoning has led to the adoption of various forms of differentiable (i.e., fuzzy) first order logic. We introduce PyReason, a software framework based on generalized annotated logic that both captures the cur
Externí odkaz:
http://arxiv.org/abs/2302.13482
Publikováno v:
AAAI Spring Symposium 2023 (MAKE)
We study the performance of a commercially available large language model (LLM) known as ChatGPT on math word problems (MWPs) from the dataset DRAW-1K. To our knowledge, this is the first independent evaluation of ChatGPT. We found that ChatGPT's per
Externí odkaz:
http://arxiv.org/abs/2302.13814