Publications (12)
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…
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…
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.…
Beyond Sight: Towards Cognitive Alignment in LVLM via Enriched Visual Knowledge
Yaqi Zhao, Yuanyang Yin, Lin Li +7
Does seeing always mean knowing? Large Vision-Language Models (LVLMs) integrate separately pre-trained vision and language components, often using CLIP-ViT as vision backbone. Howe…
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…
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…
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…
PAS: Data-Efficient Plug-and-Play Prompt Augmentation System
Miao Zheng, Hao Liang, Fan Yang +16
In recent years, the rise of Large Language Models (LLMs) has spurred a growing demand for plug-and-play AI systems. Among the various AI techniques, prompt engineering stands out…
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…
BaichuanSEED: Sharing the Potential of ExtensivE Data Collection and Deduplication by Introducing a Competitive Large Language Model Baseline
Guosheng Dong, Da Pan, Yiding Sun +17
The general capabilities of Large Language Models (LLM) highly rely on the composition and selection on extensive pretraining datasets, treated as commercial secrets by several ins…
MathScape: Benchmarking Multimodal Large Language Models in Real-World Mathematical Contexts
Hao Liang, Linzhuang Sun, Minxuan Zhou +7
With the rapid progress of Multimodal LLMs, evaluating their mathematical reasoning capabilities has become an increasingly important research direction. In particular, visual-text…
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…