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Christoforos Nalmpantis
Christoforos Nalmpantis
Postdoctoral Researcher, Fundamental AI Research at Meta
Verified email at fb.com
Title
Cited by
Cited by
Year
Augmented language models: a survey
G Mialon, R Dessì, M Lomeli, C Nalmpantis, R Pasunuru, R Raileanu, ...
arXiv preprint arXiv:2302.07842, 2023
3512023
Sliding window approach for online energy disaggregation using artificial neural networks
O Krystalakos, C Nalmpantis, D Vrakas
Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 1-6, 2018
1562018
Machine learning approaches for non-intrusive load monitoring: from qualitative to quantitative comparation
C Nalmpantis, D Vrakas
Artificial Intelligence Review 52, 217-243, 2019
1482019
Peer: A collaborative language model
T Schick, J Dwivedi-Yu, Z Jiang, F Petroni, P Lewis, G Izacard, Q You, ...
arXiv preprint arXiv:2208.11663, 2022
442022
On time series representations for multi-label NILM
C Nalmpantis, D Vrakas
Neural Computing and Applications 32, 17275-17290, 2020
432020
Signal2vec: Time series embedding representation
C Nalmpantis, D Vrakas
International conference on engineering applications of neural networks, 80-90, 2019
412019
Understanding the effects of rlhf on llm generalisation and diversity
R Kirk, I Mediratta, C Nalmpantis, J Luketina, E Hambro, E Grefenstette, ...
arXiv preprint arXiv:2310.06452, 2023
292023
Imaging time-series for NILM
L Kyrkou, C Nalmpantis, D Vrakas
International Conference on Engineering Applications of Neural Networks, 188-196, 2019
212019
Neural Fourier energy disaggregation
C Nalmpantis, N Virtsionis Gkalinikis, D Vrakas
Sensors 22 (2), 473, 2022
192022
SAED: Self-attentive energy disaggregation
N Virtsionis-Gkalinikis, C Nalmpantis, D Vrakas
Machine Learning, 1-20, 2021
172021
Neurons in large language models: Dead, n-gram, positional
E Voita, J Ferrando, C Nalmpantis
arXiv preprint arXiv:2309.04827, 2023
162023
Torch-nilm: An effective deep learning toolkit for non-intrusive load monitoring in pytorch
N Virtsionis Gkalinikis, C Nalmpantis, D Vrakas
Energies 15 (7), 2647, 2022
132022
Attention in recurrent neural networks for energy disaggregation
N Virtsionis Gkalinikis, C Nalmpantis, D Vrakas
Discovery Science: 23rd International Conference, DS 2020, Thessaloniki …, 2020
122020
A benchmark framework to evaluate energy disaggregation solutions
N Symeonidis, C Nalmpantis, D Vrakas
International Conference on Engineering Applications of Neural Networks, 19-30, 2019
102019
Hyperparameter tuning using quantum genetic algorithms
A Lentzas, C Nalmpantis, D Vrakas
2019 IEEE 31st International Conference on Tools with Artificial …, 2019
82019
Augmented language models: a survey, 2023
G Mialon, R Dessi, M Lomeli, C Nalmpantis, R Pasunuru, R Raileanu, ...
URL: https://arxiv. org/abs/2302.07842. doi 10, 48550, 0
7
Teaching large language models to reason with reinforcement learning
A Havrilla, Y Du, SC Raparthy, C Nalmpantis, J Dwivedi-Yu, ...
arXiv preprint arXiv:2403.04642, 2024
52024
Energy profile representation in vector space
C Nalmpantis, O Krystalakos, D Vrakas
Proceedings of the 10th Hellenic Conference on Artificial Intelligence, 1-5, 2018
52018
Augmented language models: a survey. CoRR, abs/2302.07842, 2023. doi: 10.48550
G Mialon, R Dessì, M Lomeli, C Nalmpantis, R Pasunuru, R Raileanu, ...
arXiv preprint arXiv.2302.07842, 0
5
Variational Regression for Multi-Target Energy Disaggregation
N Virtsionis Gkalinikis, C Nalmpantis, D Vrakas
Sensors 23 (4), 2051, 2023
42023
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