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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2026 2verdicts
UNVERDICTED 2representative citing papers
STAMP mitigates semantic dilution in SID-based generative recommendation via adaptive input pruning and densified output supervision, delivering 1.23-1.38x speedup and 17-55% VRAM savings with maintained or improved accuracy.
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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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Semantic Trimming and Auxiliary Multi-step Prediction for Generative Recommendation
STAMP mitigates semantic dilution in SID-based generative recommendation via adaptive input pruning and densified output supervision, delivering 1.23-1.38x speedup and 17-55% VRAM savings with maintained or improved accuracy.