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Creating Suspenseful Stories: Iterative Planning with Large Language Models.

, and . EACL (1), page 2391-2407. Association for Computational Linguistics, (2024)

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Creating Suspenseful Stories: Iterative Planning with Large Language Models., and . EACL (1), page 2391-2407. Association for Computational Linguistics, (2024)Interact with the Explanations: Causal Debiased Explainable Recommendation System., , , , and . WSDM, page 472-481. ACM, (2024)Learn When (not) to Trust Language Models: A Privacy-Centric Adaptive Model-Aware Approach., , , , and . CoRR, (2024)Foundation Models for Recommender Systems: A Survey and New Perspectives., , , , , and . CoRR, (2024)Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models., , and . NAACL-HLT (1), page 1208-1218. Association for Computational Linguistics, (2019)Cost-Sensitive Active Learning for Dialogue State Tracking., , , , and . SIGDIAL Conference, page 209-213. Association for Computational Linguistics, (2018)Exploring Soft Prompt Initialization Strategy for Few-Shot Continual Text Classification., , , , , and . ICASSP, page 12106-12110. IEEE, (2024)Guiding Neural Story Generation with Reader Models., , , , , and . EMNLP (Findings), page 7087-7111. Association for Computational Linguistics, (2022)Calibrating Trust of Multi-Hop Question Answering Systems with Decompositional Probes., , and . EMNLP (Findings), page 2888-2902. Association for Computational Linguistics, (2022)Few-Shot Dialogue Summarization via Skeleton-Assisted Prompt Transfer in Prompt Tuning., , , , , , , , and . EACL (1), page 2408-2421. Association for Computational Linguistics, (2024)