Výsledky vyhledávání - "Yang, JingSong"

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Self-evolving Agents with reflective and memory-augmented abilities

Autor: Liang, Xuechen, Tao, Meiling, Xia, Yinghui, Shi, Tianyu, Wang, Jun, Yang, JingSong

Large language models (LLMs) have made significant advances in the field of natural language processing, but they still face challenges such as continuous decision-making. In this research, we propose a novel framework by integrating iterative feedba

Externí odkaz: http://arxiv.org/abs/2409.00872

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LanguaShrink: Reducing Token Overhead with Psycholinguistics

Autor: Liang, Xuechen, Tao, Meiling, Xia, Yinghui, Shi, Tianyu, Wang, Jun, Yang, JingSong

As large language models (LLMs) improve their capabilities in handling complex tasks, the issues of computational cost and efficiency due to long prompts are becoming increasingly prominent. To accelerate model inference and reduce costs, we propose

Externí odkaz: http://arxiv.org/abs/2409.00855

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CMAT: A Multi-Agent Collaboration Tuning Framework for Enhancing Small Language Models

Autor: Liang, Xuechen, Tao, Meiling, Xia, Yinghui, Shi, Tianyu, Wang, Jun, Yang, JingSong

Open large language models (LLMs) have significantly advanced the field of natural language processing, showcasing impressive performance across various tasks.Despite the significant advancements in LLMs, their effective operation still relies heavil

Externí odkaz: http://arxiv.org/abs/2404.01663

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M3PT: A Multi-Modal Model for POI Tagging

Autor: Yang, Jingsong, Han, Guanzhou, Yang, Deqing, Liu, Jingping, Xiao, Yanghua, Xu, Xiang, Wu, Baohua, Ni, Shenghua

POI tagging aims to annotate a point of interest (POI) with some informative tags, which facilitates many services related to POIs, including search, recommendation, and so on. Most of the existing solutions neglect the significance of POI images and

Externí odkaz: http://arxiv.org/abs/2306.10079

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