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Jiashu Pu

4 accepted papers

2024

HoLLMwood: Unleashing the Creativity of Large Language Models in Screenwriting via Role Playing

EMNLP 2024finding

Generative AI has demonstrated unprecedented creativity in the field of computer vision, yet such phenomena have not been observed in natural language processing. In particular, large language models (LLMs) can hardly produce written works at the level of human experts due to the extremely high comp…

Cited by 7SourcePDFScholar
2023

Just Adjust One Prompt: Enhancing In-Context Dialogue Scoring via Constructing the Optimal Subgraph of Demonstrations and Prompts

EMNLP 2023long main

The use of modern Large Language Models (LLMs) as chatbots still has some problems such as hallucinations and lack of empathy. Identifying these issues can help improve chatbot performance. The community has been continually iterating on reference-free dialogue evaluation methods based on large lang…

Cited by 0SourcecodeScholar
2022

Probing Simile Knowledge from Pre-trained Language Models

ACL 2022long

Simile interpretation (SI) and simile generation (SG) are challenging tasks for NLP because models require adequate world knowledge to produce predictions. Previous works have employed many hand-crafted resources to bring knowledge-related into models, which is time-consuming and labor-intensive. In…