collaborators

11 papers

cs.AI2026

RoleMix: Unifying Sequential and Non-Sequential Features via Semantic Tokenization for Post-Click Conversion Rate Prediction

Wenan Wang, Qin Zhao, Zhixiang Lu

Post-click conversion rate (PCVR) prediction is central to industrial recommendation, but remains challenged by the structural mismatch between sparse, unordered multi-field featur…

cs.AI2026

TAVR-VLM: Risk-Conditioned Causal Grounding for Hallucination-Resistant Report Generation

Zhixiang Lu, Xiwei Liu, Sifan Song +5

Transcatheter Aortic Valve Replacement (TAVR) planning requires meticulous multimodal reasoning. However, adapting Multimodal Large Language Models (MLLMs) to this high-stakes doma…

cs.CL2026

Dialectic-Med: Mitigating Diagnostic Hallucinations via Counterfactual Adversarial Multi-Agent Debate

Zhixiang Lu, Jionglong Su

Multimodal Large Language Models (MLLMs) in healthcare suffer from severe confirmation bias, often hallucinating visual details to support initial, potentially erroneous diagnostic…

cs.CL2026

MERIT: Multilingual Expert-Reward Informed Tuning for Chinese-Centric Low-Resource Machine Translation

Zhixiang Lu, Chong Zhang, Chenyu Xue +4

Neural machine translation (NMT) from Chinese to low-resource Southeast Asian languages remains severely constrained by the extreme scarcity of clean parallel corpora and the perva…

cs.AI2026

EcoThink: A Green Adaptive Inference Framework for Sustainable and Accessible Agents

Linxiao Li, Zhixiang Lu

As the Web transitions from static retrieval to generative interaction, the escalating environmental footprint of Large Language Models (LLMs) presents a critical sustainability ch…

cs.CV2026

SkinCLIP-VL: Consistency-Aware Vision-Language Learning for Multimodal Skin Cancer Diagnosis

Zhixiang Lu, Shijie Xu, Kaicheng Yan +6

The deployment of vision-language models (VLMs) in dermatology is hindered by the trilemma of high computational costs, extreme data scarcity, and the black-box nature of deep lear…