# LocalSUG: City-Preference-Enhanced LLM for Query Suggestion in Local-Life Services Source: [LocalSUG: City-Preference-Enhanced LLM for Query Suggestion in Local-Life Services]() Collection index: [llms.txt]() Data updated: 2026-06-02T05:00:05.013Z Authors: Jinwen Chen, Shiwen Zhang, Shuai Gong, Zheng Zhang, Yachao Zhao, Lingxiang Wang, Haibo Zhou, Wei Lin, Hainan Zhang Published: 2026-03-05T08:42:27.000Z ## Abstract In local-life service platforms, query suggestion reduces user effort by generating candidate queries from input prefixes. Traditional multi-stage systems rely heavily on historical popular queries, limiting their ability to capture long-tail and emerging demand. Although LLMs provide strong semantic generalization, their deployment in local-life services faces three challenges: insufficient city-preference awareness, exposure bias in preference optimization, and strict online latency constraints. We propose LocalSUG, an LLM-based query suggestion framework for local-life services. LocalSUG mines city-preference-enhanced candidates from term co-occurrence and injects them into prompts as dynamic references rather than fusing them into model parameters. This allows the model to adapt to changing city preferences, such as merchant openings or closures, while reducing stale or locally invalid suggestions. We further introduce a beam-search-driven GRPO algorithm to align training with inference-time decoding and optimize relevance together with business-oriented rewards. Finally, quality-aware beam acceleration and vocabulary pruning reduce online latency while preserving generation quality. Offline evaluations and large-scale online A/B testing show that LocalSUG improves CTR by +0.35% and reduces the low/no-result rate by 3.98%, demonstrating its effectiveness in real-world deployment. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Query Suggestion on local life service platform ORDER (test)](): Query Suggestion; local life service platform ORDER (test); HR@12: 97.09. - [Query Suggestion on Human Evaluation Query Suggestion](): Query Suggestion; Human Evaluation Query Suggestion; Bad Rating Score: 0.83. - [Search Query Suggestion on Online A/B Test Real-world traffic](): Search Query Suggestion; Online A/B Test Real-world traffic; Few/No-Result Rate: 2.56. - [Query Suggestion on local life service platform CLICK (test)](): Query Suggestion; local life service platform CLICK (test); HR@12: 96.36. ## Original sources and implementation [Original paper]() [PDF]()