Hugging Face Trending Papers
RecRSI: Mechanism-Guided Discovery of Recommendation Algorithms
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arXiv Machine Learning
Jul 14
RecRec: Recursive Refinement for Sequential Recommendation
arXiv:2607. 10541v1 Announce Type: cross Abstract: Sequential recommender systems typically infer user preferences through single-pass encoding of interaction histories without iterative refinement, relying on increasingly deep architectures to capture complex patterns.
arXiv AI
Aug 3
RecHarness: A Bandit-Routed Agentic Harness for Self-Evolving Recommender Systems
arXiv:2607. 29241v1 Announce Type: cross Abstract: Optimizing modern recommender models still depends heavily on engineers manually iterating over architectural, objective, and training-strategy changes.
arXiv Computation and Language
Sep 11
Auto-RecSys: Harnessing Autonomous Research Agents for Industry-Scale Recommender System
Auto-RecSys is an autonomous research system designed to scale long-horizon experimentation for industry‑scale recommendation models. It tackles long feedback loops and system complexity by enabling distributed asynchronous execution, centralized cross‑server memory, and a cognitive‑procedural separation that combines natural‑language skill files with deterministic scripts. The system incorporates a dual‑loop self‑evolving architecture—Execution Evolution and Idea Evolution loops—to refine operational playbooks and guide future experiments, thereby reducing human effort per cycle and improving reliability as playbooks mature.
arXiv AI
Oct 15
Eval4DiRec: A Unified and Systematic Evaluation Framework for Diffusion-based Recommender Systems
arXiv:2609.34404v2 Announce Type: replace-cross Abstract: Leveraging the strong generative capabilities and stable training dynamics of diffusion models, diffusion-based recommender systems (RSs) hav...
Hugging Face Trending Papers
5d ago
IntentGEO: Intent-aware Generative Engine Optimization for Recommendation
Large language models (LLMs) increasingly shape recommendations across chatbots, e-commerce, and user-generated content (UGC) platforms, creating demand for Generative Engine Optimization (GEO) to imp...
Hugging Face Trending Papers
Sep 24
Advancing Model Research in AgentX: Long-Horizon Autonomy for Industrial Recommender Systems
Advancing Model Research in AgentX: Long-Horizon Autonomy for Industrial Recommender Systems introduces AgentX-Model, a dual-agent framework that links proposal development with model experimentation in business-defined sandboxes. The Research Agent drafts proposals from literature and findings, while the Model Agent runs multi‑round experiments, returning code, metrics, and open questions. The framework cycles through Reproduce, Follow‑up, Composition, and Diagnose actions, achieving high AUC gains and significant business metric improvements in online A/B tests.