2 citations · 4 across the 9 of their papers we have counts for
9 papers
EduFlow: Advancing MLLMs' Problem-Solving Proficiency through Multi-Stage, Multi-Perspective Critique
Chenglin Zhu, Tao Zhang, Chong Li +3
Multimodal large language models (MLLMs) still perform poorly on scientific tasks, particularly those requiring multi-step and interpretable reasoning. Their limitations include in…
K12Vista: Exploring the Boundaries of MLLMs in K-12 Education
Chong Li, Chenglin Zhu, Tao Zhang +3
Multimodal large language models have demonstrated remarkable reasoning capabilities in various visual tasks. However, their abilities in K12 scenarios are still systematically und…
S2SBench: A Benchmark for Quantifying Intelligence Degradation in Speech-to-Speech Large Language Models
Yuanbo Fang, Haoze Sun, Jun Liu +5
End-to-end speech large language models ((LLMs)) extend the capabilities of text-based models to directly process and generate audio tokens. However, this often leads to a decline…
Baichuan-Audio: A Unified Framework for End-to-End Speech Interaction
Tianpeng Li, Jun Liu, Tao Zhang +11
We introduce Baichuan-Audio, an end-to-end audio large language model that seamlessly integrates audio understanding and generation. It features a text-guided aligned speech genera…
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.…
Baichuan Alignment Technical Report
Mingan Lin, Fan Yang, Yanjun Shen +21
We introduce Baichuan Alignment, a detailed analysis of the alignment techniques employed in the Baichuan series of models. This represents the industry's first comprehensive accou…
Baichuan-Omni Technical Report
Yadong Li, Haoze Sun, Mingan Lin +23
The salient multimodal capabilities and interactive experience of GPT-4o highlight its critical role in practical applications, yet it lacks a high-performing open-source counterpa…
SysBench: Can Large Language Models Follow System Messages?
Yanzhao Qin, Tao Zhang, Yanjun Shen +8
Large Language Models (LLMs) have become instrumental across various applications, with the customization of these models to specific scenarios becoming increasingly critical. Syst…
CFBench: A Comprehensive Constraints-Following Benchmark for LLMs
Tao Zhang, Chenglin Zhu, Yanjun Shen +10
The adeptness of Large Language Models (LLMs) in comprehending and following natural language instructions is critical for their deployment in sophisticated real-world applications…