Not All Is Lost: Repairing Lossy User Preference States of Personalization Encoders
cs.LG, cs.IR
Submitted: 2026-10-01
Updated: 2026-10-01
Terminology
Sources
- Reproducible scaling laws for contrastive language-image learning
- DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
- Session-based Recommendations with Recurrent Neural Networks
- Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders
- Decoupled Weight Decay Regularization
- DINOv2: Learning Robust Visual Features without Supervision
- Qwen2.5 Technical Report
- SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
- Text Embeddings by Weakly-Supervised Contrastive Pre-training
- SS4Rec: Continuous-Time Sequential Recommendation with State Space Models
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks