ReFormeR: Learning and Applying Explicit Query Reformulation Patterns
We present ReFormeR, a pattern-guided approach for query reformulation. Instead of prompting a language model to generate reformulations of a query directly, ReFormeR first elicits short reformulation patterns from pairs of initial queries and empirically stronger reformulations, consolidates them into a compact library of transferable reformulation patterns, and then selects an appropriate reformulation pattern for a new query given its retrieval context. The selected pattern constrains query reformulation to controlled operations such as sense disambiguation, vocabulary grounding, or discriminative facet addition, to name a few. As such, our proposed approach makes the reformulation pol...
| Authors | Amin Bigdeli, Mert Incesu, Negar Arabzadeh et al. |
|---|---|
| Primary category | cs.IR |
| Published | 1 April 2026 |
| Last updated at source | 1 April 2026 |
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