papers

Publications (8)

cs.CL2025

Baichuan-Omni-1.5 Technical Report

Yadong Li, Jun Liu, Tao Zhang +89

We introduce Baichuan-Omni-1.5, an omni-modal model that not only has omni-modal understanding capabilities but also provides end-to-end audio generation capabilities. To achieve f…

cs.CV2025

MMLongCite: A Benchmark for Evaluating Fidelity of Long-Context Vision-Language Models

Keyan Zhou, Zecheng Tang, Lingfeng Ming +8

The rapid advancement of large vision language models (LVLMs) has led to a significant expansion of their context windows. However, an extended context window does not guarantee th…

cs.CL2025

Do Thinking Tokens Help or Trap? Towards More Efficient Large Reasoning Model

Bowen Ding, Yuhan Chen, Futing Wang +2

Large Reasoning Models (LRMs) excel at solving complex problems but face an overthinking dilemma. When handling simple tasks, they often produce verbose responses overloaded with t…

cs.DB2021

SOUP: Spatial-Temporal Demand Forecasting and Competitive Supply

Bolong Zheng, Qi Hu, Lingfeng Ming +4

We consider a setting with an evolving set of requests for transportation from an origin to a destination before a deadline and a set of agents capable of servicing the requests. I…

cs.RO2023

Realistic Safety-critical Scenarios Search for Autonomous Driving System via Behavior Tree

Ping Zhang, Lingfeng Ming, Tingyi Yuan +5

The simulation-based testing of Autonomous Driving Systems (ADSs) has gained significant attention. However, current approaches often fall short of accurately assessing ADSs for tw…

cs.AI2024

M3GIA: A Cognition Inspired Multilingual and Multimodal General Intelligence Ability Benchmark

Wei Song, Yadong Li, Jianhua Xu +8

As recent multi-modality large language models (MLLMs) have shown formidable proficiency on various complex tasks, there has been increasing attention on debating whether these mod…

cs.CL2024

Marco-LLM: Bridging Languages via Massive Multilingual Training for Cross-Lingual Enhancement

Lingfeng Ming, Bo Zeng, Chenyang Lyu +17

Large Language Models (LLMs) have achieved remarkable progress in recent years; however, their excellent performance is still largely limited to major world languages, primarily En…

cs.CV2025

Ocean-OCR: Towards General OCR Application via a Vision-Language Model

Song Chen, Xinyu Guo, Yadong Li +10

Multimodal large language models (MLLMs) have shown impressive capabilities across various domains, excelling in processing and understanding information from multiple modalities.…