Advancing Model Research in AgentX: Long-Horizon Autonomy for Industrial Recommender Systems

arXiv:2609.30001 · cs.AI, cs.IR · Submitted 2026-09-24 · Read on arXiv

cs.AI, cs.IR

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• AUC — 105× in this paper · explained in 2 episodes
• Calibration — 29× in this paper · explained in 7 episodes
• Adaptation — 13× in this paper · explained in 1 episode
• Benchmark — 8× in this paper · explained in 2 episodes
• Quantization — 8× in this paper · explained in 12 episodes
• Verification — 8× in this paper · explained in 2 episodes
• Embeddings — 6× in this paper · explained in 2 episodes
• Agent Harness — 4× in this paper · explained in 2 episodes
• Fidelity — 4× in this paper · explained in 2 episodes
• Pruning — 3× in this paper · explained in 4 episodes
• Generative Recommendation — 2× in this paper · explained in 2 episodes
• Scaling Laws — 2× in this paper · explained in 4 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Attention-Free Token Mixer — 1× in this paper
• Core — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• AgentX: Towards Agent-Driven Self-Iteration of Industrial Recommender Systems
• From Trajectories to Evidence: Auditable Experimental Records for Industrial Research Agents
• NOVA: A Verification-Aware Agent Harness for Architecture Evolution in Industrial Recommender Systems
• RecHarness: A Bandit-Routed Agentic Harness for Self-Evolving Recommender Systems
• Auto-RecSys: Harnessing Autonomous Research Agents for Industry-Scale Recommender System
• AutoRecLab: Describe the Experiment, Get the Code!
• Agora: Git as Shared Memory for Collective AutoResearch
• AutoLR: Automating the Path from Research to Launch Review in Industrial Recommender Systems
• Self-Evolving Recommendation System: End-To-End Autonomous Model Optimization With LLM Agents
• HarnessDev: Can LLMs Create and Evolve Their Own Agent Harness?
• AlphaEvolve: A coding agent for scientific and algorithmic discovery
• AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench
• AI Research Preference Models
• Dream-RSI: Recursive Self-Improvement through Evolving Worlds
• UniMixer: A Unified Architecture for Scaling Laws in Recommendation Systems
• From Clues to Generation: Language-Guided Conditional Diffusion for Cross-Domain Recommendation
• FuXi-\beta: Towards a Lightweight and Fast Large-Scale Generative Recommendation Model
• DOS: Dual-Flow Orthogonal Semantic IDs for Recommendation in Meituan
• Differentiable Semantic ID for Generative Recommendation
• TokenMinds: Pretrained User Tokens and Embeddings for User Understanding in Large Recommender Systems

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