The paper defines Agent AI as interactive multimodal systems that perceive grounded data and generate embodied actions, arguing this approach can mitigate hallucinations in foundation models.
arXiv preprint arXiv:2212.01326 , year=
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LexPath combines IRAC-guided sparse retrieval, structure-guided dense retrieval, and intent-aware reranking to outperform standard lexical, dense, hybrid, and RAG baselines on legal article retrieval benchmarks.
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Agent AI: Surveying the Horizons of Multimodal Interaction
The paper defines Agent AI as interactive multimodal systems that perceive grounded data and generate embodied actions, arguing this approach can mitigate hallucinations in foundation models.
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LexPath: A domain-oriented multi-path framework for legal article retrieval
LexPath combines IRAC-guided sparse retrieval, structure-guided dense retrieval, and intent-aware reranking to outperform standard lexical, dense, hybrid, and RAG baselines on legal article retrieval benchmarks.