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cs.CL2026
Rethinking Continual Experience Internalization for Self-Evolving LLM Agents
Jingwen Chen, Wenkai Yang, Shengda Fan +7
Experience internalization converts contextual experience from past interactions into reusable parametric capability, offering a promising path toward continual learning in large l…
cs.CL2025
Data Metabolism: An Efficient Data Design Schema For Vision Language Model
Jingyuan Zhang, Hongzhi Zhang, Zhou Haonan +7
Data curation plays a crucial role in training powerful Visual Language Models (VLMs). In this work, we introduce the concept of Data Metabolism and present our data-centric framew…
cs.CL2025
Capybara-OMNI: An Efficient Paradigm for Building Omni-Modal Language Models
Xingguang Ji, Jiakang Wang, Hongzhi Zhang +6
With the development of Multimodal Large Language Models (MLLMs), numerous outstanding accomplishments have emerged within the open-source community. Due to the complexity of creat…