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Dive into the research topics where Meng Fang is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Large Language Models Are Neurosymbolic Reasoners
Fang, M., Deng, S., Zhang, Y., Shi, Z., Chen, L., Pechenizkiy, M. & Wang, J., 25 Mar 2024, Thirty-Eighth AAAI Conference on Artificial Intelligence. Wooldridge, M., Dy, J. & Natarajan, S. (eds.). AAAI Press, p. 17985-17993 9 p. (Proceedings of the AAAI Conference on Artificial Intelligence; vol. 38, no. 16).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open Access5 Citations (Scopus) -
MaDi: Learning to Mask Distractions for Generalization in Visual Deep Reinforcement Learning
Grooten, B., Taylor, M. E., Tomilin, T., Mahmood, A. R., Vasan, G., Fang, M., Pechenizkiy, M. & Mocanu, D. C., 6 May 2024, AAMAS '24: Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems. Dastani, M., Sichman, J. S., Alechina, N. & Dignum, V. (eds.). Richland: International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS), p. 733-742 10 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open AccessFile3 Citations (Scopus)5 Downloads (Pure) -
Are Large Kernels Better Teachers than Transformers for ConvNets?
Huang, T., Yin, L., Zhang, Z., Shen, L., Fang, M., Pechenizkiy, M., Wang, Z. & Liu, S., 30 May 2023, 40th International Conference on Machine Learning, ICML 2023.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
Open AccessFile66 Downloads (Pure) -
Deep Reinforcement Learning for Real-Time Assembly Planning in Robot-Based Prefabricated Construction
Zhu, A. (Corresponding author), Dai, T., Xu, G., Pauwels, P., de Vries, B. & Fang, M. (Corresponding author), Jul 2023, In: IEEE Transactions on Automation Science and Engineering. 20, 3, p. 1515-1526 12 p., 10021301.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile27 Citations (Scopus)288 Downloads (Pure) -
LevDoom: A Benchmark for Generalization on Level Difficulty in Reinforcement Learning.
Tomilin, T., Dai, T., Fang, M. & Pechenizkiy, M., 2022, 2022 IEEE Conference on Games, CoG 2022. p. 72-79 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review
2 Citations (Scopus)
Prizes
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Best Paper Award of LoG 2022
Huang, T. (Recipient), Chen, T. (Recipient), Fang, M. (Recipient), Menkovski, V. (Recipient), Zhao, J. (Recipient), Yin, L. (Recipient), Pei, Y. (Recipient), Mocanu, D. C. (Recipient), Wang, Z. (Recipient), Pechenizkiy, M. (Recipient) & Liu, S. (Recipient), 1 Dec 2022
Prize: Other › Career, activity or publication related prizes (lifetime, best paper, poster etc.) › Scientific
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IEEE CASE2021 Best Student Paper Award Finalists
Zhu, A. (Recipient), Pauwels, P. (Recipient), de Vries, B. (Recipient) & Fang, M. (Recipient), 2021
Prize: Other › Career, activity or publication related prizes (lifetime, best paper, poster etc.) › Scientific
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Press/Media
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Reports from University of Technology Sydney Add New Data to Findings in Technology (Reinforcement Learning With Multiple Relational Attention for Solving Vehicle Routing Problems)
1/09/23
1 item of Media coverage
Press/Media: Expert Comment
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Studies Conducted at Eindhoven University of Technology on Technology Recently Reported (Deep Reinforcement Learning for Real-time Assembly Planning In Robot-based Prefabricated Construction)
de Vries, B., Pauwels, P. & Fang, M.
14/03/23
1 item of Media coverage
Press/Media: Expert Comment