·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
The AI layoff wave is becoming a powder keg3h◆GAGPO: Generalized Advantage Grouped Policy Optimization6h◆When and How Severely: Scenario-Specific Safety Envelopes for Driving VLAs6h◆AgentCyberRange: Benchmarking Frontier AI Systems in Realistic Cyber Ranges6h◆Geometric Domain Adaptation via Optimal Transport for Linear Regression in R^26h◆Robin-Neumann Coupling of PINN and FEM Solvers: A Steklov-Poincar\'e View, with Application to Fluid-Structure Interaction with Contact6h◆Gradient boosting for extremes: sampling theory and application to insurance6h◆Operator Calculus for Population-Based Optimization: A Mean-Field Convergence Theory6h◆PCR-CA: Parallel Codebook Representations with Contrastive Alignment for Multiple-Category App Recommendation6h◆MAD: Manifold Attracted Diffusion6h◆Concatenated Matrix SVD: Compression Bounds, Incremental Approximation, and Error-Constrained Clustering6h◆Mitigating Heterogeneity-Induced Drift in Hierarchical Sign-Based Federated Learning6h◆Generative Modeling of Bach-Style Symbolic Music: A Comparative Study of Autoregressive, Latent-Variable, and Adversarial Approaches6h◆Flood and Harvest: The Provable Necessity of Trivia for Generating Valuable Mathematics via the Lens of Language Generation in the Limit6h◆ClinHallu: A Benchmark for Diagnosing Stage-Wise Hallucinations in Medical MLLM Reasoning6h◆PRISM: Perception Reasoning Interleaved for Sequential Decision Making6h◆AdaTKG: Adaptive Memory for Temporal Knowledge Graph Reasoning6h◆Learning Developmental Scaffoldings to Guide Self-Organisation6h◆Planning with the Views via Scene Self-Exploration6h◆Application of Artificial Intelligence and Machine Learning in Libraries: A Systematic Review6h◆The AI layoff wave is becoming a powder keg3h◆GAGPO: Generalized Advantage Grouped Policy Optimization6h◆When and How Severely: Scenario-Specific Safety Envelopes for Driving VLAs6h◆AgentCyberRange: Benchmarking Frontier AI Systems in Realistic Cyber Ranges6h◆Geometric Domain Adaptation via Optimal Transport for Linear Regression in R^26h◆Robin-Neumann Coupling of PINN and FEM Solvers: A Steklov-Poincar\'e View, with Application to Fluid-Structure Interaction with Contact6h◆Gradient boosting for extremes: sampling theory and application to insurance6h◆Operator Calculus for Population-Based Optimization: A Mean-Field Convergence Theory6h◆PCR-CA: Parallel Codebook Representations with Contrastive Alignment for Multiple-Category App Recommendation6h◆MAD: Manifold Attracted Diffusion6h◆Concatenated Matrix SVD: Compression Bounds, Incremental Approximation, and Error-Constrained Clustering6h◆Mitigating Heterogeneity-Induced Drift in Hierarchical Sign-Based Federated Learning6h◆Generative Modeling of Bach-Style Symbolic Music: A Comparative Study of Autoregressive, Latent-Variable, and Adversarial Approaches6h◆Flood and Harvest: The Provable Necessity of Trivia for Generating Valuable Mathematics via the Lens of Language Generation in the Limit6h◆ClinHallu: A Benchmark for Diagnosing Stage-Wise Hallucinations in Medical MLLM Reasoning6h◆PRISM: Perception Reasoning Interleaved for Sequential Decision Making6h◆AdaTKG: Adaptive Memory for Temporal Knowledge Graph Reasoning6h◆Learning Developmental Scaffoldings to Guide Self-Organisation6h◆Planning with the Views via Scene Self-Exploration6h◆Application of Artificial Intelligence and Machine Learning in Libraries: A Systematic Review6h◆
News/PCR-CA: Parallel Codebook Representations with Contrastive Alignment for Multiple-Category App Recommendation
arxiv
PublishedJune 15, 2026 at 4:00 AM
—neutral

PCR-CA: Parallel Codebook Representations with Contrastive Alignment for Multiple-Category App Recommendation

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2508.18166v5 Announce Type: replace-cross Abstract: Modern app store recommender systems struggle with multiple-category apps, as traditional taxonomies fail to capture overlapping semantics, leading to suboptimal personalization. We propose PCR-CA (Parallel Codebook Representations with Contr

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivGAGPO: Generalized Advantage Grouped Policy Optimization6harxivWhen and How Severely: Scenario-Specific Safety Envelopes for Driving VLAs6harxivAgentCyberRange: Benchmarking Frontier AI Systems in Realistic Cyber Ranges6harxivGeometric Domain Adaptation via Optimal Transport for Linear Regression in R^26h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews