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20242026
most citedA Comprehensive Guide to Explainable AI: From Classical Models to LLMs

8 citations · 11 across the 17 of their papers we have counts for

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cs.LG2026

Position: Quantum Program Generation Must Prioritize Validity Over Probabilistic Scaling

Junhao Song, Yu Zhou, William Knottenbelt +1

The scaling hypothesis assumes that increasing model parameters yields emergent reasoning capabilities. This position paper argues that applying this probabilistic paradigm to gene…

cs.LG2025

Is GPT-OSS All You Need? Benchmarking Large Language Models for Financial Intelligence and the Surprising Efficiency Paradox

Ziqian Bi, Danyang Zhang, Junhao Song +1

The rapid adoption of large language models in financial services necessitates rigorous evaluation frameworks to assess their performance, efficiency, and practical applicability.…

cs.LG2025

Predicting ICU In-Hospital Mortality Using Adaptive Transformer Layer Fusion

Han Wang, Ruoyun He, Guoguang Lao +16

Early identification of high-risk ICU patients is crucial for directing limited medical resources. We introduce ALFIA (Adaptive Layer Fusion with Intelligent Attention), a modular,…

cs.LG2025

Multimodal Representation Learning and Fusion

Qihang Jin, Enze Ge, Yuhang Xie +8

Multi-modal learning is a fast growing area in artificial intelligence. It tries to help machines understand complex things by combining information from different sources, like im…

cs.LG2025

Active Learning Methods for Efficient Data Utilization and Model Performance Enhancement

Chiung-Yi Tseng, Junhao Song, Ziqian Bi +4

In the era of data-driven intelligence, the paradox of data abundance and annotation scarcity has emerged as a critical bottleneck in the advancement of machine learning. This pape…

cs.LG2025

Generative Adversarial Networks Bridging Art and Machine Intelligence

Junhao Song, Yichao Zhang, Ziqian Bi +25

Generative Adversarial Networks (GAN) have greatly influenced the development of computer vision and artificial intelligence in the past decade and also connected art and machine i…

cs.LG2024★ 8 cited

A Comprehensive Guide to Explainable AI: From Classical Models to LLMs

Weiche Hsieh, Ziqian Bi, Chuanqi Jiang +24

Explainable Artificial Intelligence (XAI) addresses the growing need for transparency and interpretability in AI systems, enabling trust and accountability in decision-making proce…

cs.LG2024

Deep Learning, Machine Learning, Advancing Big Data Analytics and Management

Weiche Hsieh, Ziqian Bi, Keyu Chen +23

Advancements in artificial intelligence, machine learning, and deep learning have catalyzed the transformation of big data analytics and management into pivotal domains for researc…