Qwen | search
Click here to view Qwen news from 60+ newspapers.
Bookmark or Share- A Simple and Effective Pruning Approach for Large Language ModelsTL;DR: We propose a simple and effective method to prune LLMs by weights and activations. As their size increases, Large Languages Models (LLMs) are natural candidates for network pruning methods: approaches that drop a subset of network weights while striving to preserve performance. Existing methods, however, require either retraining, which ...
- MetaGPT: Meta Programming for A Multi-Agent Collaborative FrameworkTL;DR: This paper introduces MetaGPT, an innovative meta-programming framework for LLM-based multi-agent collaborations. Recently, remarkable progress has been made on automated problem solving through societies of agents based on large language models (LLMs). Previous LLM-based multi-agent systems can already solve simple dialogue tasks.
- YARN: E CONTEXT WINDOW EXTENSION OF L MODELS - OpenReviewx less training steps than previous methods. Using YaRN, we show that LLaMA models can effectively utilize and extrapolate to context lengths much longer than their original pre-training would allow, while also surpassing previous the. tate-of-the-art at context window extension. In addition, we demonstrate that YaRN exhibits the capability to ...
- ICLR 2024 - OpenReviewWelcome to the OpenReview homepage for ICLR 2024
- Dynamic LLM-Agent Network: An LLM-agent Collaboration Framework...Keywords: large language model, LLM-powered agent, multi-agent collaboration, reasoning, code generation
More
