8 citations · 11 across the 17 of their papers we have counts for
17 papers
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…
Data Verification is the Future of Quantum Computing Copilots
Junhao Song, Ziqian Bi, Xinliang Chia +2
Quantum program generation demands a level of precision that may not be compatible with the statistical reasoning carried out in the inference of large language models (LLMs). Hall…
47B Mixture-of-Experts Beats 671B Dense Models on Chinese Medical Examinations
Chiung-Yi Tseng, Danyang Zhang, Tianyang Wang +8
The rapid advancement of large language models(LLMs) has prompted significant interest in their potential applications in medical domains. This paper presents a comprehensive bench…
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.…
AutoSurvey2: Empowering Researchers with Next Level Automated Literature Surveys
Siyi Wu, Chiaxin Liang, Ziqian Bi +7
The rapid growth of research literature, particularly in large language models (LLMs), has made producing comprehensive and current survey papers increasingly difficult. This paper…
Towards Alignment-Centric Paradigm: A Survey of Instruction Tuning in Large Language Models
Xudong Han, Junjie Yang, Tianyang Wang +4
Instruction tuning is a pivotal technique for aligning large language models (LLMs) with human intentions, safety constraints, and domain-specific requirements. This survey provide…
Is GPT-OSS Good? A Comprehensive Evaluation of OpenAI's Latest Open Source Models
Ziqian Bi, Keyu Chen, Chiung-Yi Tseng +9
In August 2025, OpenAI released GPT-OSS models, its first open weight large language models since GPT-2 in 2019, comprising two mixture of experts architectures with 120B and 20B p…
Exploring Efficiency Frontiers of Thinking Budget in Medical Reasoning: Scaling Laws between Computational Resources and Reasoning Quality
Ziqian Bi, Lu Chen, Junhao Song +15
This study presents the first comprehensive evaluation of thinking budget mechanisms in medical reasoning tasks, revealing fundamental scaling laws between computational resources…
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,…
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…
Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models
Junjie Yang, Junhao Song, Xudong Han +9
Knowledge distillation (KD) is a technique for transferring knowledge from complex teacher models to simpler student models, significantly enhancing model efficiency and accuracy.…
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…
Advanced Deep Learning Methods for Protein Structure Prediction and Design
Yichao Zhang, Ningyuan Deng, Xinyuan Song +25
After AlphaFold won the Nobel Prize, protein prediction with deep learning once again became a hot topic. We comprehensively explore advanced deep learning methods applied to prote…
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…
Deep Learning Model Security: Threats and Defenses
Tianyang Wang, Ziqian Bi, Yichao Zhang +24
Deep learning has transformed AI applications but faces critical security challenges, including adversarial attacks, data poisoning, model theft, and privacy leakage. This survey e…
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…
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…