PAS encodes locations via relative anchors and bins to deliver roughly 370-400m adversarial error in spatial RAG while retaining over half the baseline retrieval performance and keeping generation quality robust.
Colbert: Efficient and effective passage search via contextualized late interaction over bert
4 Pith papers cite this work. Polarity classification is still indexing.
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Tri-RAG turns external knowledge into Condition-Proof-Conclusion triplets and retrieves via the Condition anchor to improve efficiency and quality in LLM RAG.
Proposes TA2CL framework that uses temporal asynchronous alignment in contrastive learning to improve cross-subject EEG emotion classification, reporting 64.5% accuracy on 9-class FACED, 79.5% binary on FACED, 86.4% on SEED and 70.1% on SEED-V.
SkillGraph-Service builds a provenance-preserving knowledge graph from multiple competency frameworks and achieves nDCG@5 above 0.94 with sub-200 ms latency via KG-first hybrid retrieval and constrained LLM explanations.
citing papers explorer
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Privacy Without Losing Place: A Paradigm for Private Retrieval in Spatial RAGs
PAS encodes locations via relative anchors and bins to deliver roughly 370-400m adversarial error in spatial RAG while retaining over half the baseline retrieval performance and keeping generation quality robust.
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Transforming External Knowledge into Triplets for Enhanced Retrieval in RAG of LLMs
Tri-RAG turns external knowledge into Condition-Proof-Conclusion triplets and retrieves via the Condition anchor to improve efficiency and quality in LLM RAG.
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Cross-Subject EEG Emotion Recognition Based on Temporal Asynchronous Alignment Contrastive Learning
Proposes TA2CL framework that uses temporal asynchronous alignment in contrastive learning to improve cross-subject EEG emotion classification, reporting 64.5% accuracy on 9-class FACED, 79.5% binary on FACED, 86.4% on SEED and 70.1% on SEED-V.
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KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanation
SkillGraph-Service builds a provenance-preserving knowledge graph from multiple competency frameworks and achieves nDCG@5 above 0.94 with sub-200 ms latency via KG-first hybrid retrieval and constrained LLM explanations.