시작은 미약하였으나 , 그 끝은 창대하리라

(내 연구에 필요한 정보만..작성함)

논문링크: https://arxiv.org/abs/2203.00555 DeepNet: Scaling Transformers to 1,000 Layers In this paper, we propose a simple yet effective method to stabilize extremely deep Transformers. Specifically, we introduce a new normalization function (DeepNorm) to modify the residual connection in Transformer, accompanying with theoretically derived i arxiv.org 논문링크: https://arxiv.org/abs/2210.06423 Foundat..

논문링크 : https://proceedings.neurips.cc/paper_files/paper/2023/hash/6dcf277ea32ce3288914faf369fe6de0-Abstract-Conference.html Visual Instruction Tuning Requests for name changes in the electronic proceedings will be accepted with no questions asked. However name changes may cause bibliographic tracking issues. Authors are asked to consider this carefully and discuss it with their co-authors prior ..

논문링크 : https://arxiv.org/abs/2306.14824 Kosmos-2: Grounding Multimodal Large Language Models to the World We introduce Kosmos-2, a Multimodal Large Language Model (MLLM), enabling new capabilities of perceiving object descriptions (e.g., bounding boxes) and grounding text to the visual world. Specifically, we represent refer expressions as links in Markdown, i arxiv.org Published : 2023.07 (arXi..

논문 링크: https://arxiv.org/abs/2302.14045 Language Is Not All You Need: Aligning Perception with Language Models A big convergence of language, multimodal perception, action, and world modeling is a key step toward artificial general intelligence. In this work, we introduce Kosmos-1, a Multimodal Large Language Model (MLLM) that can perceive general modalities, learn arxiv.org Published : 2023.03 ..

논문 링크: https://www.mdpi.com/2504-446X/7/2/114 Semantic Scene Understanding with Large Language Models on Unmanned Aerial Vehicles Unmanned Aerial Vehicles (UAVs) are able to provide instantaneous visual cues and a high-level data throughput that could be further leveraged to address complex tasks, such as semantically rich scene understanding. In this work, we built on the use of Lar www.mdpi.co..

논문링크 : https://arxiv.org/abs/2302.00402 mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video Recent years have witnessed a big convergence of language, vision, and multi-modal pretraining. In this work, we present mPLUG-2, a new unified paradigm with modularized design for multi-modal pretraining, which can benefit from modality collaboration whil arxiv.org Published ..

논문 링크 : https://arxiv.org/abs/2305.06355 VideoChat: Chat-Centric Video Understanding In this paper, we initiate an attempt of developing an end-to-end chat-centric video understanding system, coined as VideoChat. It integrates video foundation models and large language models via a learnable neural interface, excelling in spatiotemporal re arxiv.org Published : 2021.03.24 (arxiv - 24.01.14 기준) C..