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SOTA2 Research · papers
Find papers, implementations, and the benchmark evidence behind state-of-the-art AI systems.
| arxiv 2311.03355 |
| Interfacing Foundation Models' Embeddings | Xueyan Zou, Linjie Li, Jianfeng Wang | 2023 | arxiv 2312.07532 |
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| Preventing Catastrophic Forgetting through Memory Networks in Continuous Detection | Gaurav Bhatt, James Ross, Leonid Sigal | 2024 | arxiv 2403.14797 |
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| Embedding-Free Transformer with Inference Spatial Reduction for Efficient Semantic Segmentation | Hyunwoo Yu, Yubin Cho, Beoungwoo Kang | 2024 | arxiv 2407.17261 |
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| DetToolChain: A New Prompting Paradigm to Unleash Detection Ability of MLLM | Yixuan Wu, Yizhou Wang, Shixiang Tang | 2024 | arxiv 2403.12488 |
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| Omobot: a low-cost mobile robot for autonomous search and fall detection | Shihab Uddin Ahamad, Masoud Ataei, Vijay Devabhaktuni | 2024 | arxiv 2408.05315 |
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| Efficient and Robust Quantization-aware Training via Adaptive Coreset Selection | Xijie Huang, Zechun Liu, Shih-Yang Liu | 2023 | arxiv 2306.07215 |
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| Vision-Language Dataset Distillation | Xindi Wu, Byron Zhang, Zhiwei Deng | 2023 | arxiv 2308.07545 |
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| A Semantic Space is Worth 256 Language Descriptions: Make Stronger Segmentation Models with Descriptive Properties | Junfei Xiao, Ziqi Zhou, Wenxuan Li | 2023 | arxiv 2312.13764 |
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| LowCLIP: Adapting the CLIP Model Architecture for Low-Resource Languages in Multimodal Image Retrieval Task | Ali Asgarov, Samir Rustamov | 2024 | arxiv 2408.13909 |
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| LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention | Renrui Zhang, Jiaming Han, Chris Liu | 2023 | arxiv 2303.16199 |
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