Reproduction confirms PAG boosts generative retrieval effectiveness, but its look-ahead planning signal collapses under intent-preserving typos and query mismatches, reverting performance to unguided decoding.
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Re-evaluating controlled text generation systems under standardized conditions reveals that many published performance claims do not hold, highlighting the need for consistent evaluation practices.
SEM-CTRL integrates token-level MCTS with Answer Set Grammars to enforce rich context-sensitive syntactic and semantic constraints on off-the-shelf LLM decoders, enabling guaranteed valid completions.
citing papers explorer
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Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval
Reproduction confirms PAG boosts generative retrieval effectiveness, but its look-ahead planning signal collapses under intent-preserving typos and query mismatches, reverting performance to unguided decoding.
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A Comparative Study of Controlled Text Generation Systems Using Level-Playing-Field Evaluation Principles
Re-evaluating controlled text generation systems under standardized conditions reveals that many published performance claims do not hold, highlighting the need for consistent evaluation practices.
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$\texttt{SEM-CTRL}$: Semantically Controlled Decoding
SEM-CTRL integrates token-level MCTS with Answer Set Grammars to enforce rich context-sensitive syntactic and semantic constraints on off-the-shelf LLM decoders, enabling guaranteed valid completions.