Generate to Explore, Select to Exploit: Aligning LLM-based Headline Generation with Personalized Recommendation

arXiv:2609.15094 · cs.IR, cs.AI · Submitted 2026-09-14 · Read on arXiv

cs.IR, cs.AI

Submitted: 2026-09-14

Updated: 2026-09-14

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Alignment — 11× in this paper · explained in 1 episode
• Mode Collapse — 9× in this paper · explained in 2 episodes
• Large Language Model — 7× in this paper
• Ablation — 6× in this paper · explained in 1 episode
• Group Sequence Policy Optimization — 6× in this paper
• Decoupling — 5× in this paper · explained in 2 episodes
• Personalization — 5× in this paper · explained in 2 episodes
• Redundancy — 5× in this paper · explained in 2 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Large Language Models (LLMs) — 4× in this paper · explained in 6 episodes
• Reward Function — 4× in this paper · explained in 2 episodes
• Reward Model — 4× in this paper
• Click-Through Rate — 3× in this paper
• Direct Preference Optimization — 3× in this paper
• Embeddings — 3× in this paper · explained in 2 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• Generative AI — 3× in this paper · explained in 2 episodes
• Hallucination — 3× in this paper · explained in 3 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Ablation Studies — 2× in this paper · explained in 1 episode
• Aleatoric Uncertainty — 2× in this paper · explained in 5 episodes
• Alignment Methods — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Daily Active Users — 2× in this paper
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Instruction Tuning — 2× in this paper · explained in 2 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Reward Hacking — 2× in this paper · explained in 8 episodes
• Reward Shaping — 2× in this paper · explained in 2 episodes
• Supervised Fine-Tuning — 2× in this paper
• Verification — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Contextual Understanding — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Direct Preference Optimization (DPO) — 1× in this paper · explained in 9 episodes
• Generative Recommendation — 1× in this paper · explained in 2 episodes
• Homogeneity — 1× in this paper · explained in 2 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Pairwise Comparisons — 1× in this paper · explained in 2 episodes
• Perplexity — 1× in this paper · explained in 3 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes

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