REPREC: Representation Driven Parameter-Efficient Recommendation System

arXiv:2607.24845 · cs.IR, cs.AI · Submitted 2026-07-24 · Read on arXiv

cs.IR, cs.AI

Submitted: 2026-07-24

Updated: 2026-08-28

Code: https://github.com/phdbotcode/REPREC

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Core — 12× in this paper · explained in 2 episodes
• Alignment — 11× in this paper · explained in 1 episode
• Adaptation — 7× in this paper · explained in 1 episode
• Embeddings — 7× in this paper · explained in 2 episodes
• Fine-Tuning — 6× in this paper · explained in 5 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Distillation — 3× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 3× in this paper · explained in 6 episodes
• Personalization — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Modularity — 2× in this paper · explained in 9 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• IEEE International Conference on Data Mining — 1× in this paper
• Robustness — 1× in this paper · explained in 5 episodes
• Steering — 1× in this paper · explained in 2 episodes

Sources

• Generalized User Representations for Transfer Learning
• Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders
• Mistral 7B
• FinTRec: Transformer Based Unified Contextual Ads Targeting and Personalization for Financial Applications
• ClipCap: CLIP Prefix for Image Captioning
• PinnerFormer: Sequence Modeling for User Representation at Pinterest

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