NARRA-Gym is an executable benchmark that generates complete interactive narrative episodes from emotional seeds and logs full model trajectories to expose gaps in coherence, adaptation, and personalization that static story tests miss.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages =
2 Pith papers cite this work. Polarity classification is still indexing.
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Narrative-UFET shows that adding controlled synthetic narrative context improves ultra-fine entity typing on long-tail types over sentence-level baselines, with type-changing narratives providing stronger gains than natural contexts.
citing papers explorer
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NARRA-Gym for Evaluating Interactive Narrative Agents
NARRA-Gym is an executable benchmark that generates complete interactive narrative episodes from emotional seeds and logs full model trajectories to expose gaps in coherence, adaptation, and personalization that static story tests miss.
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Narrative-UFET: Narrative Generation for Ultra-Fine Entity Typing
Narrative-UFET shows that adding controlled synthetic narrative context improves ultra-fine entity typing on long-tail types over sentence-level baselines, with type-changing narratives providing stronger gains than natural contexts.