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Yuchen Yuan

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#artificial intelligence Preprint Oct 2026

Beyond the Sequentiality Bottleneck: A Hybrid Diffusion-Autoregressive Framework for Efficient Multimodal Reasoning

Experiments on vision-language benchmarks show that CoRAL significantly outperforms prior diffusion-based methods and achieves competitive performance against strong ARMs, achieving both superior efficiency and quality.

Wei Cai, Jian Zhao, Yu-Chen Yuan et al. · 0 citations
#artificial intelligence Preprint Oct 2026

When Reasoning Is Not Enough: Proactive Inquiry for Cross-Modal Safety in Multimodal Large Language Models

Multimodal large language models (MLLMs) can act unsafely when individually benign images and texts are interpreted jointly. Beyond implicit reasoning risk, where reasoning drifts toward harm, we identify intent-level risk, where cross-modal ambiguity silently commits the model to a hazardous premise that path-level op...

Wei Cai, Jian Zhao, Yu-Chen Yuan et al. · 0 citations
#artificial intelligence Preprint Sep 2026

CaLR: Causal Latent Revision for Robust Diffusion Reasoning

Causal Latent Revision (CaLR), a framework that reformulates reasoning as constrained latent optimization, performs gradient-guided ``thought revision" to enforce logical consistency, enabling dynamic self-correction of intermediate steps during parallel generation.

Wei Cai, Jian Zhao, Yu-Chen Yuan et al. · 0 citations
#machine learning Preprint Jul 2026

QEncodeBench: Can Large Language Models Encode Classical Problems into Verified Quantum Oracles?

QEncodeBench tasks large language models with encoding classical constraint problems as phase oracles and scores the generated circuits with an adversarially self-validated verifier that decides full solution-set equivalence up to a global phase, with ancillas restored and resource budgets enforced.

Xu-Jun Che, Han-Han Wu, Yu-Chen Yuan et al. · 1 citation
Preprint Aug 2026

AeroCopilotBench: A Two-Tier Benchmark for Evaluating LLM Agents as Aviation Copilots in an Interactive Virtual Cockpit Environment

A safety-gated evaluation framework in which a trajectory succeeds only when all task goals are achieved without violating any hard safety constraint, while safe goal progress and trajectory safety are measured separately is established.

Yu-Chen Yuan, Zheng-Huang Wu, Yuan-Gan Li et al. · 0 citations

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