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Found 4 papers, 1 papers with code
RLingua: Improving Reinforcement Learning Sample Efficiency in Robotic Manipulations With Large Language Models
In this paper, we propose RLingua, a framework that can leverage the internal knowledge of large language models (LLMs) to reduce the sample complexity of RL in robotic manipulations.
Dual-Scale Interest Extraction Framework with Self-Supervision for Sequential Recommendation
Nevertheless, the existing approaches just extract each interest independently for the corresponding sub-sequence while ignoring the global correlation of the entire interaction sequence, which may fail to capture the user's inherent preference for the potential interests generalization and unavoidably make the recommended items homogeneous with the historical behaviors.
Detect Rumors in Microblog Posts for Low-Resource Domains via Adversarial Contrastive Learning
Massive false rumors emerging along with breaking news or trending topics severely hinder the truth.
Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks
Rumors are rampant in the era of social media.
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