Tencent Youtu Lab has collaborated with the research team at Shanghai Jiao Tong University to introduce a revolutionary knowledge enhancement method, paving new avenues for optimizing large models. This innovative technology discards the limitations of traditional model fine-tuning, directly extracting knowledge from open-source data, significantly simplifying the model optimization process, and achieving outstanding performance that surpasses existing state-of-the-art technologies (SOTA) across multiple tasks. In recent years, while large language models (LLMs) have made significant progress in various fields, they still face numerous challenges in practical applications. Traditional model fine-tuning methods...

The expert team formed by the MIFA Laboratory of the Shanghai Jiao Tong University Qingtuan Research Institute and the Endocrinology Department of Zhongshan Hospital affiliated with Fudan University has recently developed a dedicated large model for diabetes named Diabetica. This model integrates the language processing capabilities of large models with specialized knowledge in diabetes, aiming to provide intelligent support for doctors, patients, and medical education. The team employed a novel framework to establish a comprehensive data processing system, created high-quality datasets and evaluation benchmarks, and fine-tuned the large language model, significantly enhancing its performance on diabetes-related tasks.

Tencent Youtu Lab and Shanghai Jiao Tong University released a comprehensive review focusing on dataset evaluation and selection for instruction tuning to enhance large model performance. The study aims to help large models grasp the essence of natural language processing by analyzing data quality, diversity, and importance to guide the construction of efficient and critical datasets. It highlights that data quality directly impacts tuning effect....

The LSLM full-duplex language model developed in collaboration between Shanghai Jiao Tong University and ByteDance revolutionizes traditional AI assistant interaction by enabling real-time conversation where users can listen while speaking. The core advantage of LSLM lies in its ability to simultaneously process speech input and generate output, significantly enhancing the natural flow of dialogue. By integrating streaming self-supervised learning with a token-based decoder, this model supports real-time speech interaction and performs exceptionally well even in noisy environments. LSLM's mid-term fusion strategy strikes the optimal balance between speech generation and real-time interaction, demonstrating impressive noise resistance.

The AI painter struggles to generate specific scenes like 'Ice Cola in a teacup,' highlighting the issue of text-image misalignment. Zhao Juntu, a PhD student at Shanghai Jiao Tong University, and his team discovered that even the most advanced AI models have difficulty accurately understanding and realizing complex concepts described in text, such as the difference between a transparent glass cup and a traditional teacup. To address this issue, they proposed a Mixture of Concept Experts (MoCE) method, utilizing large language models to help AI grasp hidden concepts, thereby enabling more precise control over text.

Shanghai Jiao Tong University, in collaboration with Baidu, has jointly released the Version 2.0 of the 白玉兰科学大模型. This version includes 'Legal Open Source' and 'Chemical Synthesis 2.0'. The 白玉兰科学大模型 — Legal Open Source surpasses other open-source Chinese general models in comprehensive legal assessment testing. This collaboration promotes advancements in the field of AI for Science. Both parties have made new progress in their cooperation within AI for Science, setting a benchmark for collaboration.