Zobrazeno 1 - 10
of 3 454
pro vyhledávání: '"Qian, Hong"'
Autor:
Li, Bingdong, Di, Zixiang, Yang, Yanting, Qian, Hong, Yang, Peng, Hao, Hao, Tang, Ke, Zhou, Aimin
In this paper, we introduce a novel approach for large language model merging via black-box multi-objective optimization algorithms. The goal of model merging is to combine multiple models, each excelling in different tasks, into a single model that
Externí odkaz:
http://arxiv.org/abs/2407.00487
Publikováno v:
KDD 2024
Cognitive diagnosis models (CDMs) are designed to learn students' mastery levels using their response logs. CDMs play a fundamental role in online education systems since they significantly influence downstream applications such as teachers' guidance
Externí odkaz:
http://arxiv.org/abs/2407.17476
Knowledge tracing (KT) is a crucial task in intelligent education, focusing on predicting students' performance on given questions to trace their evolving knowledge. The advancement of deep learning in this field has led to deep-learning knowledge tr
Externí odkaz:
http://arxiv.org/abs/2406.12896
Since Newton's time, deterministic causality has been considered a crucial prerequisite in any fundamental theory in physics. In contrast, the present work investigates stochastic dynamical models for motion in one spatial dimension, in which Newtoni
Externí odkaz:
http://arxiv.org/abs/2406.02405
Autor:
Qian, Hong, Shen, Zhongwei
Entropy, its production, and its change in a dynamical system can be understood from either a fully stochastic dynamic description or from a deterministic dynamics exhibiting chaotic behavior. By taking the former approach based on the general diffus
Externí odkaz:
http://arxiv.org/abs/2406.00165
Autor:
Li, Bingdong, Di, Zixiang, Lu, Yongfan, Qian, Hong, Wang, Feng, Yang, Peng, Tang, Ke, Zhou, Aimin
Multi-objective Bayesian optimization (MOBO) has shown promising performance on various expensive multi-objective optimization problems (EMOPs). However, effectively modeling complex distributions of the Pareto optimal solutions is difficult with lim
Externí odkaz:
http://arxiv.org/abs/2405.08674
Autor:
Lu, Yongfan, Di, Zixiang, Li, Bingdong, Liu, Shengcai, Qian, Hong, Yang, Peng, Tang, Ke, Zhou, Aimin
Multi-objective combinatorial optimization (MOCO) problems are prevalent in various real-world applications. Most existing neural MOCO methods rely on problem decomposition to transform an MOCO problem into a series of singe-objective combinatorial o
Externí odkaz:
http://arxiv.org/abs/2405.08604
Cognitive diagnosis aims to gauge students' mastery levels based on their response logs. Serving as a pivotal module in web-based online intelligent education systems (WOIESs), it plays an upstream and fundamental role in downstream tasks like learni
Externí odkaz:
http://arxiv.org/abs/2404.11290
With the development of artificial intelligence, personalized learning has attracted much attention as an integral part of intelligent education. China, the United States, the European Union, and others have put forward the importance of personalized
Externí odkaz:
http://arxiv.org/abs/2402.01666
Publikováno v:
Published in AAAI 2024
Cognitive diagnosis assessment is a fundamental and crucial task for student learning. It models the student-exercise interaction, and discovers the students' proficiency levels on each knowledge attribute. In real-world intelligent education systems
Externí odkaz:
http://arxiv.org/abs/2401.10840