SAGA: Structure-Attended Generative Action Embedding Model that encodes Multi-Surface User Action Sequences
cs.LG, cs.IR
Submitted: 2026-08-15
Updated: 2026-09-26
Terminology
Sources
- Your Spending Needs Attention: Modeling Financial Habits with Transformers
- PinFM: Foundation Model for User Activity Sequences at a Billion-scale Visual Discovery Platform
- OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment
- TransactionGPT
- Kunlun: Establishing Scaling Laws for Massive-Scale Recommendation Systems through Unified Architecture Design
- ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation
- FinTRec: Transformer Based Unified Contextual Ads Targeting and Personalization for Financial Applications
- Entire Space Multi-Task Model: An Effective Approach for Estimating Post-Click Conversion Rate
- PRAGMA: Revolut Foundation Model
- Open Banking Foundational Model: Learning Language Representations from Few Financial Transactions
- RoFormer: Enhanced Transformer with Rotary Position Embedding
- Contrastive Learning for Sequential Recommendation
- Generative Recommendation for Large-Scale Advertising
- OneTrans: Unified Feature Interaction and Sequence Modeling with One Transformer in Industrial Recommender
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