Evaluation of few-shot learning capabilities for downstream tasks (%).

Evaluation of few-shot learning capabilities for downstream tasks (%).

<p>Evaluation of few-shot learning capabilities for downstream tasks (%).</p>

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Bibliographic Details
Main Author:	Chenglong Ge (2626258) (author)
Other Authors:	Jing Zhang (23775) (author), Jianping Du (556784) (author), Jiachen Yao (22287863) (author), Tianhe Yang (433724) (author), Xuebin Wang (1788466) (author), Linyu Wang (4624090) (author)
Published:	2025
Subjects:	Biophysics Biotechnology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified lyapunov stability criteria interpretable statistical priors intelligent perception systems integrates statistical mechanics improve trajectory understanding efficient expansion strategy dual spatiotemporal adapters large language models pro outperforms state modal adaptation framework injecting domain knowledge modal adaptation art models unified modeling training data shot scenarios representation collapse public datasets new parameters multimodal data limited samples heterogeneous trajectories heterogeneous conflicts guided cross first work experimental results effective solution dynamic features classification accuracy approach incorporates ais show
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Summary:	<p>Evaluation of few-shot learning capabilities for downstream tasks (%).</p>

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