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Xiaohua Wu

3 accepted papers

2026

Exploring Selective Avoidance for Online User Behavior Analysis: A Forest of Thought Explanation

AAAI 2026technical

The response behaviors observed in online user-generated content (UGC) frequently demonstrate non-linear characteristics, such as conditional branching and selective avoidance. These patterns present additional challenges for ensuring the trustworthiness of Large Language Model (LLMs) reasoning, par

Cited by 0SourcePDFScholar
2026

HiFICL: High-Fidelity In-Context Learning for Multimodal Tasks

CVPR 2026

In-Context Learning (ICL) is a significant paradigm for Large Multimodal Models (LMMs), using a few in-context demonstrations (ICDs) for new task adaptation. However, its performance is sensitive to demonstration configurations and computationally expensive. Mathematically, the influence of these de

Cited by 0SourcecodeScholar
2022

Towards the Quantitative Interpretability Analysis of Citizens Happiness Prediction

IJCAI 2022poster

Evaluating the high-effect factors of citizens' happiness is beneficial to a wide range of policy-making for economics and politics in most countries. Benefiting from the high-efficiency of regression models, previous efforts by sociology scholars have analyzed the effect of happiness factors with h…