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Can you apply some of the concepts of siamese networks, one shot learning, few shot learning, matching networks to reduce the number of images required for training.
children can learn new objects …
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### Details
I've recently attempted to utilize DSPy for the BigBench Hard dataset, specifically focusing on the Casual Judgment scenarios. These scenarios are characterized by lengthy descriptions, wh…
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The `seen_tokens` attribute is deprecated and will be removed in v4.41. Use the `cache_position` model input instead.
Traceback (most recent call last):
File "/hpc2hdd/home/yhuang489/junhao/Emu3/e…
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Are there plans to evaluate the vision modality of GPT-4? I am interested to know how GPT-4 could perform on classification tasks with 0- and few-shot-learning and how it compares to vision-only model…
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Hello author, thank you for your outstanding work! Can you please publish the source code for your Extended Article "Self-Supervised Learning for Few-Shot Medical Image Segmentation,"(doi: 10.1109/TMI…
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Currently, few-shot learning prompts contain only fixed examples and thus may not benefit from those examples when processing text that is significantly different from the examples in the prompts. The…
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## What's few-shot/zero-shot HPO
Few-shot HPO is a both promising-performance and budget-friendly HPO solution. It is divided into two processes: offline processing and online processing. In offline…
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@WangYueFt @HobbitLong I was curious, why did you implement your own resnets instead of using the ones already available in pytorch? is there anything bad about those for meta-learning/few-shot learn…
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Hi,
Which model (either chat or text-completion) should be used for in-context learning using few-shot prompting?
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Is there a plan to release pre-trained weights so that sampling/evaluation can be done without re-training everything from scratch?