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[2025-2] 전연주 - MaeTok: Masked Autoencoders Are Effective Tokenizers for Diffusion Models 논문 링크: arxiv.org/pdf/2502.03444깃허브 링크: Hhhhhhao/continuous_tokenizer GitHub - Hhhhhhao/continuous_tokenizerContribute to Hhhhhhao/continuous_tokenizer development by creating an account on GitHub.github.com허깅페이스 링크: MAETok/maetok-b-128 · Hugging Face MAETok/maetok-b-128 · Hugging FaceThis model has been pushed to the Hub using the PytorchModelHubMixin integration: Library: [More Information Need.. 2025. 7. 12.
[2025-1] 임준수 - Self-Adapting Language Models https://arxiv.org/abs/2506.10943 Self-Adapting Language ModelsLarge language models (LLMs) are powerful but static; they lack mechanisms to adapt their weights in response to new tasks, knowledge, or examples. We introduce Self-Adapting LLMs (SEAL), a framework that enables LLMs to self-adapt by generating their ownarxiv.org Abstract기존의 대형 언어 모델(LLM)은 강력하지만 정적(static)이며 새로운 작업이나 지식에 즉각적으로 적응하는 능.. 2025. 7. 10.
[2025-1] 임재열 - Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks는 2017년 ICML에서 발표된,모델에 독립적인 meta learning 알고리즘을 제안한 논문입니다. [MAML]https://arxiv.org/abs/1703.03400 Model-Agnostic Meta-Learning for Fast Adaptation of Deep NetworksWe propose an algorithm for meta-learning that is model-agnostic, in the sense that it is compatible with any model trained with gradient descent and applicable to a vari.. 2025. 7. 5.
[2025-1] 백승우 - GUI Agent by Script-based Automation 2025. 7. 4.