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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

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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

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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…