7 citations · 23 across the 22 of their papers we have counts for
9 papers · 1 filter
What Makes In-context Learning Effective for Mathematical Reasoning: A Theoretical Analysis
Jiayu Liu, Zhenya Huang, Chaokun Wang +3
Owing to the capability of in-context learning, large language models (LLMs) have shown impressive performance across diverse mathematical reasoning benchmarks. However, we find th…
Nested Hash Layer: A Plug-and-play Module for Multiple-length Hash Code Learning
Liyang He, Yuren Zhang, Rui Li +3
Deep supervised hashing is essential for efficient storage and search in large-scale image retrieval. Traditional deep supervised hashing models generate single-length hash codes,…
A Survey of Models for Cognitive Diagnosis: New Developments and Future Directions
Fei Wang, Weibo Gao, Qi Liu +8
Cognitive diagnosis has been developed for decades as an effective measurement tool to evaluate human cognitive status such as ability level and knowledge mastery. It has been appl…
EduNLP: Towards a Unified and Modularized Library for Educational Resources
Zhenya Huang, Yuting Ning, Longhu Qin +8
Educational resource understanding is vital to online learning platforms, which have demonstrated growing applications recently. However, researchers and developers always struggle…
Learning to Solve Geometry Problems via Simulating Human Dual-Reasoning Process
Tong Xiao, Jiayu Liu, Zhenya Huang +4
Geometry Problem Solving (GPS), which is a classic and challenging math problem, has attracted much attention in recent years. It requires a solver to comprehensively understand bo…
Survey of Computerized Adaptive Testing: A Machine Learning Perspective
Yan Zhuang, Qi Liu, Haoyang Bi +12
Computerized Adaptive Testing (CAT) offers an efficient and personalized method for assessing examinee proficiency by dynamically adjusting test questions based on individual perfo…
A Knowledge-Injected Curriculum Pretraining Framework for Question Answering
Xin Lin, Tianhuang Su, Zhenya Huang +3
Knowledge-based question answering (KBQA) is a key task in NLP research, and also an approach to access the web data and knowledge, which requires exploiting knowledge graphs (KGs)…
Bit-mask Robust Contrastive Knowledge Distillation for Unsupervised Semantic Hashing
Liyang He, Zhenya Huang, Jiayu Liu +4
Unsupervised semantic hashing has emerged as an indispensable technique for fast image search, which aims to convert images into binary hash codes without relying on labels. Recent…
Unified Uncertainty Estimation for Cognitive Diagnosis Models
Fei Wang, Qi Liu, Enhong Chen +4
Cognitive diagnosis models have been widely used in different areas, especially intelligent education, to measure users' proficiency levels on knowledge concepts, based on which us…