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Xuesong Lu

8 accepted papers

2026

EdGCL: Disentangling Social and Cognitive Homophily in Graph-Based Educational Recommender Systems

AAAI 2026technical

Educational recommendation systems have been a fundamental component for alleviating learning disorientation in self-paced learning. While existing studies mainly leverage cognitive theories to guide learning motivation modeling, they critically overlook the role of social influences. Through empiri

Cited by 0SourcePDFScholar
2026

LLM-Enhanced Knowledge and Learning Path Understanding for Graph-based Educational Recommendation

IJCAI 2026

Educational recommendations empower personalized learning by suggesting suitable learning resources to learners, and the graph-based recommenders are widely adopted. Existing methods are mainly ID-based, which initialize learners and resources with trainable identifiers and optimize their representa

Cited by 0Scholar
2025

Personalized Question Answering with User Profile Generation and Compression

EMNLP 2025

Large language models (LLMs) offer a novel and convenient avenue for humans to acquire knowledge. However, LLMs are prone to providing “midguy” answers regardless of users’ knowledge background, thereby failing to meet each user’s personalized needs. To tackle the problem, we propose to generate per

2024

Two Issues with Chinese Spelling Correction and A Refinement Solution

ACL 2024short

The Chinese Spelling Correction (CSC) task aims to detect and correct misspelled characters in Chinese text, and has received lots of attention in the past few years. Most recent studies adopt a Transformer-based model and leverage different features of characters such as pronunciation, glyph and co…

2022

CAT-probing: A Metric-based Approach to Interpret How Pre-trained Models for Programming Language Attend Code Structure

EMNLP 2022finding

Code pre-trained models (CodePTMs) have recently demonstrated significant success in code intelligence. To interpret these models, some probing methods have been applied. However, these methods fail to consider the inherent characteristics of codes. In this paper, to address the problem, we propose…

2022

Multi-task Learning for Paraphrase Generation With Keyword and Part-of-Speech Reconstruction

ACL 2022findings

Paraphrase generation using deep learning has been a research hotspot of natural language processing in the past few years. While previous studies tackle the problem from different aspects, the essence of paraphrase generation is to retain the key semantics of the source sentence and rewrite the res…

2017

Impacts of Anxiety in Building Fire and Smoke Evacuation: Modeling and Validation

RA-L 2017

Anxiety impairs evacuees' ability to select appropriate routes during building fire and smoke evacuations. Understanding anxiety is thus essential to provide proper guidance to evacuees. However, it is challenging to model how anxiety affects evacuees' decision-making process, and how to validate th

Cited by 29SourceScholar