Zobrazeno 1 - 10
of 411
pro vyhledávání: '"Meng, Fanxu"'
Recent development in Artificial Intelligence (AI) models has propelled their application in scientific discovery, but the validation and exploration of these discoveries require subsequent empirical experimentation. The concept of self-driving labor
Externí odkaz:
http://arxiv.org/abs/2411.00444
Crafting automation systems tailored for specific domains requires aligning the space of human experts' semantics with the space of robot executable actions, and scheduling the required resources and system layout accordingly. Regrettably, there are
Externí odkaz:
http://arxiv.org/abs/2410.05663
The qubit mapping problem (QMP) focuses on the mapping and routing of qubits in quantum circuits so that the strict connectivity constraints imposed by near-term quantum hardware are satisfied. QMP is a pivotal task for quantum circuit compilation an
Externí odkaz:
http://arxiv.org/abs/2409.04752
Autor:
Meng, Fanxu, Zhou, Xiangzhen
Quantum computing presents a compelling prospect for revolutionizing the field of combinatorial optimization, in virtue of the unique attributes of quantum mechanics such as superposition and entanglement. The Quantum Approximate Optimization Algorit
Externí odkaz:
http://arxiv.org/abs/2407.12242
Autor:
Shi, Yu-Zhe, Hou, Haofei, Bi, Zhangqian, Meng, Fanxu, Wei, Xiang, Ruan, Lecheng, Wang, Qining
Publikováno v:
In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) 2024
Accurate representation of procedures in restricted scenarios, such as non-standardized scientific experiments, requires precise depiction of constraints. Unfortunately, Domain-specific Language (DSL), as an effective tool to express constraints stru
Externí odkaz:
http://arxiv.org/abs/2406.12324
To parameter-efficiently fine-tune (PEFT) large language models (LLMs), the low-rank adaptation (LoRA) method approximates the model changes $\Delta W \in \mathbb{R}^{m \times n}$ through the product of two matrices $A \in \mathbb{R}^{m \times r}$ an
Externí odkaz:
http://arxiv.org/abs/2404.02948
The human brain is naturally equipped to comprehend and interpret visual information rapidly. When confronted with complex problems or concepts, we use flowcharts, sketches, and diagrams to aid our thought process. Leveraging this inherent ability ca
Externí odkaz:
http://arxiv.org/abs/2311.09241
The pre-trained large language models (LLMs) have shown their extraordinary capacity to solve reasoning tasks, even on tasks that require a complex process involving multiple sub-steps. However, given the vast possible generation space of all the tas
Externí odkaz:
http://arxiv.org/abs/2310.05452
Autor:
Tang, Xiaojuan, Zheng, Zilong, Li, Jiaqi, Meng, Fanxu, Zhu, Song-Chun, Liang, Yitao, Zhang, Muhan
The emergent few-shot reasoning capabilities of Large Language Models (LLMs) have excited the natural language and machine learning community over recent years. Despite of numerous successful applications, the underlying mechanism of such in-context
Externí odkaz:
http://arxiv.org/abs/2305.14825
Publikováno v:
In Information Sciences February 2025 690
