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pro vyhledávání: '"Chen Chunlin"'
Thermodynamic analysis of vanadium distribution behavior in blast furnaces and basic oxygen furnaces
Publikováno v:
High Temperature Materials and Processes, Vol 42, Iss 1, Pp pp. 793-805 (2023)
Production data from a vanadium (V)-containing titaniferous magnetite (VTM) smelting blast furnace (BF) ironmaking plant and a V-recovering basic oxygen furnace (BOF) shop were collected over a period of 1 year. The corresponding thermodynamics was a
Externí odkaz:
https://doaj.org/article/c63df2e827714f249e351439a50a5d5b
Tensor-based multi-view clustering has recently received significant attention due to its exceptional ability to explore cross-view high-order correlations. However, most existing methods still encounter some limitations. (1) Most of them explore the
Externí odkaz:
http://arxiv.org/abs/2411.07685
A longstanding goal of artificial general intelligence is highly capable generalists that can learn from diverse experiences and generalize to unseen tasks. The language and vision communities have seen remarkable progress toward this trend by scalin
Externí odkaz:
http://arxiv.org/abs/2410.11448
For on-policy reinforcement learning, discretizing action space for continuous control can easily express multiple modes and is straightforward to optimize. However, without considering the inherent ordering between the discrete atomic actions, the e
Externí odkaz:
http://arxiv.org/abs/2408.00309
Publikováno v:
High Temperature Materials and Processes, Vol 38, Iss 2019, Pp 354-361 (2019)
The effects of MgO, Al2O3, C/S (CaO/SiO2) and FeO on the viscosity and the liquidus temperature (TLQ) of blast furnace (BF) primary slag were analyzed by using multiphase equilibrium. The results show that the TLQ of primary slag exhibits a minimum v
Externí odkaz:
https://doaj.org/article/0c8e17b95b104557a1e89b259c7d2437
Autor:
Liu, Zichuan, Wang, Zefan, Xu, Linjie, Wang, Jinyu, Song, Lei, Wang, Tianchun, Chen, Chunlin, Cheng, Wei, Bian, Jiang
The advent of large language models (LLMs) has revolutionized the field of natural language processing, yet they might be attacked to produce harmful content. Despite efforts to ethically align LLMs, these are often fragile and can be circumvented by
Externí odkaz:
http://arxiv.org/abs/2404.13968
We study continual offline reinforcement learning, a practical paradigm that facilitates forward transfer and mitigates catastrophic forgetting to tackle sequential offline tasks. We propose a dual generative replay framework that retains previous kn
Externí odkaz:
http://arxiv.org/abs/2404.10662
Autor:
Liu, Zichuan, Zhang, Yingying, Wang, Tianchun, Wang, Zefan, Luo, Dongsheng, Du, Mengnan, Wu, Min, Wang, Yi, Chen, Chunlin, Fan, Lunting, Wen, Qingsong
Explaining multivariate time series is a compound challenge, as it requires identifying important locations in the time series and matching complex temporal patterns. Although previous saliency-based methods addressed the challenges, their perturbati
Externí odkaz:
http://arxiv.org/abs/2401.08552
Real-world multi-agent tasks usually involve dynamic team composition with the emergence of roles, which should also be a key to efficient cooperation in multi-agent reinforcement learning (MARL). Drawing inspiration from the correlation between role
Externí odkaz:
http://arxiv.org/abs/2312.04819
Autor:
Liu, Mingfeng, Wang, Jiantao, Hu, Junwei, Liu, Peitao, Niu, Haiyang, Yan, Xuexi, Li, Jiangxu, Yan, Haile, Yang, Bo, Sun, Yan, Chen, Chunlin, Kresse, Georg, Zuo, Liang, Chen, Xing-Qiu
Publikováno v:
Nat Commun 15, 3079 (2024)
Reconstructive phase transitions involving breaking and reconstruction of primary chemical bonds are ubiquitous and important for many technological applications. In contrast to displacive phase transitions, the dynamics of reconstructive phase trans
Externí odkaz:
http://arxiv.org/abs/2310.05683