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Xuequn Shang

7 accepted papers

2026

CellAgent: LLM-Driven Multi-Agent Framework for Natural Language-Based Single-Cell Analysis

ICLR 2026poster

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) data analysis are pivotal for advancing biological research, enabling precise characterization of cellular heterogeneity. However, existing analysis approaches require extensive manual programming and complex tool integration, p…

Cited by 0SourcecodeScholar
2026

KSS-MoE: Knowledge Space Synergy Framework in Mixture of Experts for Continual Visual Instruction Tuning

AAAI 2026technical

Multimodal Large Language Models (MLLMs) employing the Mixture-of-Experts (MoE) structure exhibit encouraging results in visual language tasks. However, they struggle with catastrophic forgetting due to a lack of effective collaboration among experts and negative transfer across tasks. This happens

Cited by 0SourcePDFScholar
2025

Metapath and Hypergraph Structure-based Multi-Channel Graph Contrastive Learning for Student Performance Prediction

IJCAI 2025

Considerable attention has been paid to predicting student performance on exercises. The performance of prior studies is determined by the quality of the trait features of students and exercises. Nevertheless, most of the prior study primarily examines simple pairwise interactions in learning trait

2025

Multi-Scale Temporal Neural Network for Stock Trend Prediction Enhanced by Temporal Hyepredge Learning

IJCAI 2025

Existing research in Stock Trend Prediction (STP) focuses on temporal features extracted from a temporal sequence of stock data with a look-back window, which frequently leads to the omission of important periodic patterns, such as weekly and monthly variations in stock prices. Furthermore, these me

2024

A Robust Dual-debiasing VQA Model based on Counterfactual Causal Effect

EMNLP 2024finding

Traditional VQA models are inherently vulnerable to language bias, resulting in a significant performance drop when encountering out-of-distribution datasets. The conventional VQA models suffer from language bias that indicates a spurious correlation between textual questions and answers. Given the…

2023

Imbalanced Node Classification Beyond Homophilic Assumption

IJCAI 2023poster

Imbalanced node classification widely exists in real-world networks where graph neural networks (GNNs) are usually highly inclined to majority classes and suffer from severe performance degradation on classifying minority class nodes. Various imbalanced node classification methods have been proposed…

Cited by 14SourcePDFScholar
2022

Topology Imbalance and Relation Inauthenticity Aware Hierarchical Graph Attention Networks for Fake News Detection

COLING 2022main

Fake news detection is a challenging problem due to its tremendous real-world political and social impacts. Recent fake news detection works focus on learning news features from News Propagation Graph (NPG). However, little attention is paid to the issues of both authenticity of the relationships an…

Cited by 16SourcePDFScholar