collaborators

5 papers

cs.AI2026

RealUnify: Do Unified Models Truly Benefit from Unification? A Comprehensive Benchmark

Yang Shi, Yuhao Dong, Yue Ding +22

The integration of visual understanding and generation into unified multimodal models represents a significant stride toward general-purpose AI. However, a fundamental question rem…

cs.AI2026

VTC-Bench: Evaluating Agentic Multimodal Models via Compositional Visual Tool Chaining

Xuanyu Zhu, Yuhao Dong, Rundong Wang +9

Recent advancements extend Multimodal Large Language Models (MLLMs) beyond standard visual question answering to utilizing external tools for advanced visual tasks. Despite this pr…

cs.CL2025

MLLM-CL: Continual Learning for Multimodal Large Language Models

Hongbo Zhao, Fei Zhu, Haiyang Guo +4

Recent Multimodal Large Language Models (MLLMs) excel in vision-language understanding but face challenges in adapting to dynamic real-world scenarios that require continuous integ…

cs.CE2025

HRFT: Mining High-Frequency Risk Factor Collections End-to-End via Transformer

Wenyan Xu, Rundong Wang, Chen Li +2

In quantitative trading, transforming historical stock data into interpretable, formulaic risk factors enhances the identification of market volatility and risk. Despite recent adv…

cs.CE2025

Learning Explainable Stock Predictions with Tweets Using Mixture of Experts

Wenyan Xu, Dawei Xiang, Rundong Wang +4

Stock price movements are influenced by many factors, and alongside historical price data, tex-tual information is a key source. Public news and social media offer valuable insight…