Large Language Model

Towards Building Specialized Generalist AI with System 1 and System 2 Fusion
In this perspective paper, we introduce the concept of Specialized Generalist Artificial Intelligence (SGAI or simply SGI) as a crucial …
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Towards Building Specialized Generalist AI with System 1 and System 2 Fusion
Fast and Slow Generating: An Empirical Study on Large and Small Language Models Collaborative Decoding
Large Language Models (LLMs) demonstrate impressive performance in diverse applications, yet they face significant drawbacks, including …
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Fast and Slow Generating: An Empirical Study on Large and Small Language Models Collaborative Decoding
Intuitive Fine-Tuning: Towards Simplifying Alignment into a Single Process
Supervised Fine-Tuning (SFT) and Preference Optimization (PO) are two fundamental processes for enhancing the capabilities of Language …
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Intuitive Fine-Tuning: Towards Simplifying Alignment into a Single Process
UltraMedical: Building Specialized Generalists in Biomedicine
Large Language Models (LLMs) have demonstrated remarkable capabilities across various domains and are moving towards more specialized …
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UltraMedical: Building Specialized Generalists in Biomedicine
CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following
With the advancement of language models (LMs), their exposure to private data is increas- ingly inevitable, and their deployment (espe- …
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CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following
Investigating Deep Watermark Security: An Adversarial Transferability Perspective
The rise of generative neural networks has triggered an increased demand for intellectual property (IP) protection in generated …
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Investigating Deep Watermark Security: An Adversarial Transferability Perspective
CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model
Instruction tuning has recently been recognized as an effective way of aligning Large Language Models (LLMs) to enhance their …
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CRaSh: Clustering, Removing, and Sharing Enhance Fine-tuning without Full Large Language Model
Sparse Low-rank Adaptation of Pre-trained Language Models
Fine-tuning pre-trained large language models in a parameter-efficient manner is widely studied for its effectiveness and efficiency. …
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Sparse Low-rank Adaptation of Pre-trained Language Models