Hazards in Daily Life? Enabling Robots to Proactively Detect and Resolve Anomalies

Zirui Song*, Guangxian Ouyang*, Meng Fang, Hongbin Na, Zijing Shi, Zhenhao Chen, Yujie Fu, Zeyu Zhang, Shiyu Jiang, Miao Fang, Ling Chen, Xiuying Chen (*: first co-authors)

“AnomalyGen : A framework of anomaly vitrual scene data generation without human annotation, to enhance the robustness of robots.”

BenchLMM: Benchmarking Cross-style Visual Capability of Large Multimodal Models

Rizhao Cai*, Zirui Song*, Dayan Guan, Zhenhao Chen, Yaohang Li, Xing Luo, Chenyu Yi & Alex Kot (*: first co-authors)

“BenchLMM: A novel, comprehensive benchmark, specifically designed to investigate the cross-style capability of Large Multimodal Models (LMMs).”

Toolkit & Code

MedINST: Meta Dataset of Biomedical Instructions

Wenhan Han, Meng Fang, Zihan Zhang, Yu Yin, Zirui Song, Ling Chen, Mykola Pechenizkiy, Qingyu Chen

“MedINST, the Meta Dataset of Biomedical Instructions, a novel multi-domain, multi-task instructional meta-dataset. MedINST comprises 133 biomedical NLP tasks and over 7 million training samples.”

Unveiling the power of language models in chemical research question answering

Xiuying Chen, Tairan Wang, Taicheng Guo, Kehan Guo, Juexiao Zhou, Haoyang Li, Zirui Song, Xin Gao & Xiangliang Zhang

“ScholarChemQA, a large-scale QA dataset constructed from chemical papers.” Code

Geolocation with Real Human Gameplay Data: A Large-Scale Dataset and Human-Like Reasoning Framework

Zirui Song*, Jingpu Yang*, Yuan Huang*, Jonathan Tonglet, Zeyu Zhang, Tao Cheng, Meng Fang, Iryna Gurevych, Xiuying Chen (*: first co-authors)

“We introduce a comprehensive geolocation framework with three key components: GeoComp, a large-scale dataset; GeoCoT, a novel reasoning method; and GeoEval, an evaluation metric, collectively designed to address critical challenges and drive advancements in geolocation research. At the core of this framework is GeoComp (Geolocation Competition Dataset), a large-scale dataset collected from a geolocation game platform involving 740K users over two years. It comprises 25 million entries of metadata and 3 million geo-tagged locations spanning much of the globe”

Injecting Domain-Specific Knowledge into Large Language Models: A Comprehensive Survey

Zirui Song*, Bin Yan*, Yuhan Liu, Miao Fang, Mingzhe Li, Rui Yan, Xiuying Chen (*: first co-authors)

“LLMs general-purpose nature often limits their effectiveness in domain-specific applications that require specialized knowledge, such as healthcare, chemistry, or legal analysis. To address this, researchers have explored diverse methods to enhance LLMs by integrating domain-specific knowledge. In this survey, we provide a comprehensive overview of these methods, which we categorize into four key approaches: dynamic knowledge injection, static knowledge embedding, modular adapters, and prompt optimization.”

From a Tiny Slip to a Giant Leap: An LLM-Based Simulation for Fake News Evolution

Yuhan Liu,Zirui Song, Xiaoqing Zhang, Xiuying Chen, Rui Yan

“We take the first step toward simulating and revealing this evolution, proposing a Fake News evolUtion Simulation framEwork (FUSE) based on LLMs”

PedDet: Adaptive Spectral Optimization for Multimodal Pedestrian Detection

Rui Zhao*, Zeyu Zhang*, Yi Xu, Yi Yao, Yan Huang, Wenxin Zhang, Zirui Song, Xiuying Chen, Yang Zhao (*: first co-authors)

“PedDet, an adaptive spectral optimization complementarity framework specifically enhanced and optimized for multispectral pedestrian detection”

Foundations and recent trends in multimodal mobile agents: A survey

Biao Wu*, Yanda Li*, Meng Fang, Zirui Song, Zhiwei Zhang, Yunchao Wei, Ling Chen (*: first co-authors)

“Mobile agents are essential for automating tasks in complex and dynamic mobile environments. As foundation models evolve, the demands for agents that can adapt in real-time and process multimodal data have grown. This survey provides a comprehensive review of mobile agent technologies, focusing on recent advancements that enhance real-time adaptability and multimodal interaction.”

Note: The first author Biao Wu canceled my co-authorship during the second submission to ARR2025. And I have not received any explanation from him. But I think I still have credit for this work, and disagree with his decision.