Papers with dynamic decoding

2 papers
D3: Dynamic Docid Decoding for Multi-Intent Generative Retrieval (2026.eacl-industry)

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Challenge: Existing GR systems rely on offline DocID assignment and constrained decoding . offline Doc ID assignment and decoding often prevents GR from capturing query-specific intent .
Approach: They propose a mechanism that adaptively refines DocIDs through query-informed identifier expansion.
Outcome: The proposed mechanism improves retrieval accuracy on unseen and multi-intent documents.
Subword Segmental Machine Translation: Unifying Segmentation and Target Sentence Generation (2023.findings-acl)

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Challenge: Subword segmenters are used in neural machine translation, but are not used in high-resource settings.
Approach: They propose a subword segmental machine translation (SSMT) that unifies subword and MT in a single trainable model.
Outcome: The proposed model improves chrF scores for morphologically rich agglutinative languages and is more robust on a test set constructed for evaluating morphology generalisations.

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