Results 21 to 30 of about 83,605 (232)
Improving Prompt Tuning with Learned Prompting Layers
CoRR, 2023 Prompt tuning prepends a soft prompt to the input embeddings or hidden states and only optimizes the prompt to adapt pretrained models (PTMs) to downstream tasks. The previous work manually selects prompt layers which are far from optimal and failed to exploit the potential of prompt tuning.
Wei Zhu, Ming Tan
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, 2023 Autistic children can experience memory and communication challenges that make reporting or recalling events difficult. Although open-ended prompts are generally considered the most effective question type, there is some debate about the utility of such ...
Dargue, N +5 more
core +1 more source
CoRR, 2016 Delay games are two-player games of infinite duration in which one player may delay her moves to obtain a lookahead on her opponent's moves. Recently, such games with quantitative winning conditions in weak MSO with the unbounding quantifier were studied, but their properties turned out to be unsatisfactory.
Felix Klein 0001, Martin Zimmermann 0002
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Late Prompt Tuning: A Late Prompt Could Be Better Than Many Prompts
Findings of the Association for Computational Linguistics: EMNLP 2022, 2022 Accepted by Findings of EMNLP ...
Xiangyang Liu +3 more
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Prompt-to-Prompt Image Editing with Cross Attention Control
CoRR, 2022 Recent large-scale text-driven synthesis models have attracted much attention thanks to their remarkable capabilities of generating highly diverse images that follow given text prompts. Such text-based synthesis methods are particularly appealing to humans who are used to verbally describe their intent.
ABERMAN KFIR +5 more
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Findings of the Association for Computational Linguistics: ACL 2025Current large language model (LLM) applications often employ multi-component prompts, comprising both system and user prompts, to guide model behaviors. While recent advancements have demonstrated the efficacy of automatically optimizing either the system or user prompt to boost performance, such unilateral approaches often yield suboptimal outcomes ...
Xinyu Zhang 0019 +3 more
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From liveness to promptness [PDF]
Formal Methods in System Design, 2007 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Orna Kupferman +2 more
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Prompt Engineering a Prompt Engineer
Findings of the Association for Computational Linguistics ACL 2024Prompt engineering is a challenging yet crucial task for optimizing the performance of large language models on customized tasks. It requires complex reasoning to examine the model's errors, hypothesize what is missing or misleading in the current prompt, and communicate the task with clarity.
Qinyuan Ye +3 more
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Prompt Exploration with Prompt Regression
CoRRIn the advent of democratized usage of large language models (LLMs), there is a growing desire to systematize LLM prompt creation and selection processes beyond iterative trial-and-error. Prior works majorly focus on searching the space of prompts without accounting for relations between prompt variations.
Michael Feffer +3 more
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