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pro vyhledávání: '"Li, Jiachen"'
The particle-particle random phase approximation (ppRPA) within the hole-hole channel was recently proposed as an efficient tool for computing excitation energies of point defects in solids [J. Phys. Chem. Lett. 2024, 15, 2757-2764]. In this work, we
Externí odkaz:
http://arxiv.org/abs/2406.18515
Autor:
Wang, Danqing, Antoniades, Antonis, Luong, Kha-Dinh, Zhang, Edwin, Kosan, Mert, Li, Jiachen, Singh, Ambuj, Wang, William Yang, Li, Lei
Counterfactual explanations of Graph Neural Networks (GNNs) offer a powerful way to understand data that can naturally be represented by a graph structure. Furthermore, in many domains, it is highly desirable to derive data-driven global explanations
Externí odkaz:
http://arxiv.org/abs/2406.13869
Direct alignment from preferences (DAP) has emerged as a promising paradigm for aligning large language models (LLMs) to human desiderata from pre-collected, offline preference datasets. While recent studies indicate that existing offline DAP methods
Externí odkaz:
http://arxiv.org/abs/2406.12168
Video generation has many unique challenges beyond those of image generation. The temporal dimension introduces extensive possible variations across frames, over which consistency and continuity may be violated. In this study, we move beyond evaluati
Externí odkaz:
http://arxiv.org/abs/2406.08656
Autor:
He, Xuehai, Feng, Weixi, Zheng, Kaizhi, Lu, Yujie, Zhu, Wanrong, Li, Jiachen, Fan, Yue, Wang, Jianfeng, Li, Linjie, Yang, Zhengyuan, Lin, Kevin, Wang, William Yang, Wang, Lijuan, Wang, Xin Eric
Multimodal Language Language Models (MLLMs) demonstrate the emerging abilities of "world models" -- interpreting and reasoning about complex real-world dynamics. To assess these abilities, we posit videos are the ideal medium, as they encapsulate ric
Externí odkaz:
http://arxiv.org/abs/2406.08407
Autor:
Li, Jiachen, Zhu, Tianyu
Quantitative simulation of electronic structure of solids requires the treatment of local and non-local electron correlations on an equal footing. Dynamical mean-field theory, a widely-used quantum embedding algorithm that assumes local self-energy a
Externí odkaz:
http://arxiv.org/abs/2406.07531
Autor:
Li, Jiachen, Feng, Weixi, Fu, Tsu-Jui, Wang, Xinyi, Basu, Sugato, Chen, Wenhu, Wang, William Yang
Diffusion-based text-to-video (T2V) models have achieved significant success but continue to be hampered by the slow sampling speed of their iterative sampling processes. To address the challenge, consistency models have been proposed to facilitate f
Externí odkaz:
http://arxiv.org/abs/2405.18750
Recent studies reveal that Large Language Models (LLMs) face challenges in balancing safety with utility, particularly when processing long texts for NLP tasks like summarization and translation. Despite defenses against malicious short questions, th
Externí odkaz:
http://arxiv.org/abs/2405.15202
Autor:
Li, Jiachen, Wang, Xinyao, Zhu, Sijie, Kuo, Chia-Wen, Xu, Lu, Chen, Fan, Jain, Jitesh, Shi, Humphrey, Wen, Longyin
Recent advancements in Multimodal Large Language Models (LLMs) have focused primarily on scaling by increasing text-image pair data and enhancing LLMs to improve performance on multimodal tasks. However, these scaling approaches are computationally e
Externí odkaz:
http://arxiv.org/abs/2405.05949
We numerically study the spectral statistics of open quantum many-body systems (OQMBS) as signatures of quantum chaos (or the lack thereof), using the dissipative spectral form factor (DSFF), a generalization of the spectral form factor to complex sp
Externí odkaz:
http://arxiv.org/abs/2405.01641