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ReDSI not only standardizes DSI implementations but also outperforms previous baselines, challenging the status quo in generative retrieval.
Guaranteeing trivially parseable LLM outputs via suffix-constrained generation not only simplifies information extraction but can also improve performance on prediction tasks.
Existing zero-shot relation extraction models crumble when faced with realistic data scenarios, highlighting a critical gap between research and real-world applicability.