most citedBaichuan-Audio: A Unified Framework for End-to-End Speech Interaction

2 citations · 4 across the 7 of their papers we have counts for

collaborators

10 papers

cs.CR2025

EquaCode: A Multi-Strategy Jailbreak Approach for Large Language Models via Equation Solving and Code Completion

Zhen Liang, Hai Huang, Zhengkui Chen

Large language models (LLMs), such as ChatGPT, have achieved remarkable success across a wide range of fields. However, their trustworthiness remains a significant concern, as they…

cs.LG20252 cited

Baichuan-M2: Scaling Medical Capability with Large Verifier System

M2 Team, Chengfeng Dou, Chong Liu +31

As large language models (LLMs) advance in conversational and reasoning capabilities, their practical application in healthcare has become a critical research focus. However, there…

cs.LG2025

ProGMLP: A Progressive Framework for GNN-to-MLP Knowledge Distillation with Efficient Trade-offs

Weigang Lu, Ziyu Guan, Wei Zhao +5

GNN-to-MLP (G2M) methods have emerged as a promising approach to accelerate Graph Neural Networks (GNNs) by distilling their knowledge into simpler Multi-Layer Perceptrons (MLPs).…

cs.CL20252 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

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

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…