Zobrazeno 1 - 10
of 5 235
pro vyhledávání: '"Li, haoran"'
Efficient exploration is crucial in cooperative multi-agent reinforcement learning (MARL), especially in sparse-reward settings. However, due to the reliance on the unimodal policy, existing methods are prone to falling into the local optima, hinderi
Externí odkaz:
http://arxiv.org/abs/2411.03603
With the advancement of technology, large language models (LLMs) have achieved remarkable performance across various natural language processing (NLP) tasks, powering LLM-integrated applications like Microsoft Copilot. However, as LLMs continue to ev
Externí odkaz:
http://arxiv.org/abs/2411.00459
Autor:
Xia, Peng, Zhu, Kangyu, Li, Haoran, Wang, Tianze, Shi, Weijia, Wang, Sheng, Zhang, Linjun, Zou, James, Yao, Huaxiu
Artificial Intelligence (AI) has demonstrated significant potential in healthcare, particularly in disease diagnosis and treatment planning. Recent progress in Medical Large Vision-Language Models (Med-LVLMs) has opened up new possibilities for inter
Externí odkaz:
http://arxiv.org/abs/2410.13085
Autor:
Chan, Chunkit, Jiayang, Cheng, Liu, Xin, Yim, Yauwai, Jiang, Yuxin, Deng, Zheye, Li, Haoran, Song, Yangqiu, Wong, Ginny Y., See, Simon
Debate is the process of exchanging viewpoints or convincing others on a particular issue. Recent research has provided empirical evidence that the persuasiveness of an argument is determined not only by language usage but also by communicator charac
Externí odkaz:
http://arxiv.org/abs/2410.04239
Recently, multimodal large language models (MLLMs) have demonstrated strong visual understanding and decision-making capabilities, enabling the exploration of autonomously improving MLLMs in unknown environments. However, external feedback like human
Externí odkaz:
http://arxiv.org/abs/2410.03303
With high-dimensional state spaces, visual reinforcement learning (RL) faces significant challenges in exploitation and exploration, resulting in low sample efficiency and training stability. As a time-efficient diffusion model, although consistency
Externí odkaz:
http://arxiv.org/abs/2410.00051
Event Causality Identification (ECI) focuses on extracting causal relations between events in texts. Existing methods for ECI primarily rely on causal features and external knowledge. However, these approaches fall short in two dimensions: (1) causal
Externí odkaz:
http://arxiv.org/abs/2409.13621
As text-based speech editing becomes increasingly prevalent, the demand for unrestricted free-text editing continues to grow. However, existing speech editing techniques encounter significant challenges, particularly in maintaining intelligibility an
Externí odkaz:
http://arxiv.org/abs/2409.12992
Autor:
Kofford, Spencer, Li, Haoran, Kwapisz, Robert, Ready, Roy A., Sawhney, Akshay, Cheung, Oi Chee, Fan, Mingyu, Jayich, Andrew M.
We report on spectroscopy of the low-lying electronic transitions in $^{224}$Ra$^+$. The ion's low charge to mass ratio and convenient wavelengths make $^{224}$Ra$^+$ a promising optical clock candidate. We measured the frequencies of the the $^2{S}_
Externí odkaz:
http://arxiv.org/abs/2409.09873
Cooperative localization and target tracking are essential for multi-robot systems to implement high-level tasks. To this end, we propose a distributed invariant Kalman filter based on covariance intersection for effective multi-robot pose estimation
Externí odkaz:
http://arxiv.org/abs/2409.09410