DTL-NS introduces hierarchical index trees and LLM inference on item-ID encodings to identify false negatives and perform multi-view hard negative sampling for improved implicit CF recommendation.
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CDGLT achieves SOTA on MET-Meme for multimodal metaphor identification by using SLERP-based concept drift and prompt-adapted LayerNorm tuning with reduced compute.
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Dual-Tree LLM-Enhanced Negative Sampling for Implicit Collaborative Filtering
DTL-NS introduces hierarchical index trees and LLM inference on item-ID encodings to identify false negatives and perform multi-view hard negative sampling for improved implicit CF recommendation.
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Concept Drift Guided LayerNorm Tuning for Efficient Multimodal Metaphor Identification
CDGLT achieves SOTA on MET-Meme for multimodal metaphor identification by using SLERP-based concept drift and prompt-adapted LayerNorm tuning with reduced compute.