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Found 10 papers, 3 papers with code
RDRec: Rationale Distillation for LLM-based Recommendation
Large language model (LLM)-based recommender models that bridge users and items through textual prompts for effective semantic reasoning have gained considerable attention.
NFARec: A Negative Feedback-Aware Recommender Model
In this paper, we propose a negative feedback-aware recommender model (NFARec) that maximizes the leverage of negative feedback.
CaDRec: Contextualized and Debiased Recommender Model
To tackle the skewed distribution, we propose two strategies for disentangling interactions: (1) modeling individual biases to learn unbiased item embeddings, and (2) incorporating item popularity with positional encoding.
Enhanced Coherence-Aware Network with Hierarchical Disentanglement for Aspect-Category Sentiment Analysis
To address the issue of multiple aspect categories and sentiment entanglement, we propose a hierarchical disentanglement module to extract distinct categories and sentiment features.
Semi-Automatic Construction and Refinement of an Annotated Corpus for a Deep Learning Framework for Emotion Classification
Therefore, this paper proposes a method of creating a semi-automatically constructed emotion corpus.
