most citedCOEFF-KANs: A Paradigm to Address the Electrolyte Field with KANs

4 citations · 4 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI2024

KALE-LM-Chem: Vision and Practice Toward an AI Brain for Chemistry

Weichen Dai, Yezeng Chen, Zijie Dai +9

Recent advancements in large language models (LLMs) have demonstrated strong potential for enabling domain-specific intelligence. In this work, we present our vision for building a…

cs.LG20244 cited

COEFF-KANs: A Paradigm to Address the Electrolyte Field with KANs

Xinhe Li, Zhuoying Feng, Yezeng Chen +4

To reduce the experimental validation workload for chemical researchers and accelerate the design and optimization of high-energy-density lithium metal batteries, we aim to leverag…

cs.CL2024

Brain-Inspired Two-Stage Approach: Enhancing Mathematical Reasoning by Imitating Human Thought Processes

Yezeng Chen, Zui Chen, Yi Zhou

Although large language models demonstrate emergent abilities in solving math word problems, there is a challenging task in complex multi-step mathematical reasoning tasks. To impr…

cs.CL2024

An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning

Zui Chen, Yezeng Chen, Jiaqi Han +3

Large language models (LLMs) are displaying emergent abilities for math reasoning tasks,and there is a growing attention on enhancing the ability of open-source LLMs through superv…

cs.CL2023

Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset

Haoyi Wu, Wenyang Hui, Yezeng Chen +3

Mathematical understanding and reasoning are crucial tasks for assessing the capabilities of artificial intelligence (AI). However, existing benchmarks either require just a few st…