Adaptive trie-guided decoding with document context and tunable penalties improves in-document query auto-completion, outperforming baselines and larger models like LLaMA-3 on seen queries.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.IR 2representative citing papers
WeWrite mines user logs to decide when personalization is needed and trains LLMs with SFT and GRPO to rewrite video search queries, delivering 1.07% more long-view clicks and 2.97% fewer reformulations in live A/B tests.
citing papers explorer
-
DocQAC: Adaptive Trie-Guided Decoding for Effective In-Document Query Auto-Completion
Adaptive trie-guided decoding with document context and tunable penalties improves in-document query auto-completion, outperforming baselines and larger models like LLaMA-3 on seen queries.
-
When & How to Write for Personalized Demand-aware Query Rewriting in Video Search
WeWrite mines user logs to decide when personalization is needed and trains LLMs with SFT and GRPO to rewrite video search queries, delivering 1.07% more long-view clicks and 2.97% fewer reformulations in live A/B tests.