activity
20232025
most citedBaichuan 2: Open Large-scale Language Models

127 citations · 139 across the 21 of their papers we have counts for

collaborators
Showing 2025Show all

8 papers · 1 filter

cs.SD2025

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…

cs.AI2025

ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning

Mingyang Chen, Linzhuang Sun, Tianpeng Li +10

Large Language Models (LLMs) have shown remarkable capabilities in reasoning, exemplified by the success of OpenAI-o1 and DeepSeek-R1. However, integrating reasoning with external…

cs.CV2025

DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies

Wei Song, Yuran Wang, Zijia Song +6

The differing representation spaces required for visual understanding and generation pose a challenge in unifying them within the autoregressive paradigm of large language models.…

cs.CL2025★ 2 cited

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…

cs.CL2025

MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought Verification

Linzhuang Sun, Hao Liang, Jingxuan Wei +5

According to the Test-Time Scaling, the integration of External Slow-Thinking with the Verify mechanism has been demonstrated to enhance multi-round reasoning in large language mod…

cs.CV2025★ 1 cited

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.…

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.CL2025★ 4 cited

Med-R: Crafting Trustworthy LLM Physicians via Retrieval and Reasoning of Evidence-Based Medicine

Keer Lu, Zheng Liang, Da Pan +6

Large Language Models (LLMs) have exhibited remarkable capabilities in clinical scenarios. Despite their potential, existing works face challenges when applying LLMs to medical set…