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SYMDIREC: A Neuro-Symbolic Divide-Retrieve-Conquer Framework for Enhanced RTL Synthesis and Summarization
SYMDIREC: A Neuro-Symbolic Divide-Retrieve-Conquer Framework for Enhanced RTL Synthesis and Summarization
Arxiv
0+阅读 · 3月17日
Prompt Programming for Cultural Bias and Alignment of Large Language Models
Arxiv
0+阅读 · 3月17日
Generation of Programming Exam Question and Answer Using ChatGPT Based on Prompt Engineering
Arxiv
0+阅读 · 3月16日
Prompt Readiness Levels (PRL): a maturity scale and scoring framework for production grade prompt assets
Arxiv
0+阅读 · 3月16日
Customizing ChatGPT for Second Language Speaking Practice: Genuine Support or Just a Marketing Gimmick?
Arxiv
0+阅读 · 3月16日
What You Prompt is What You Get: Increasing Transparency of Prompting Using Prompt Cards
Arxiv
0+阅读 · 3月13日
Evaluating Prompt Engineering Strategies for Sentiment Control in AI-Generated Texts
Arxiv
0+阅读 · 2月6日
Paraphrase Types Elicit Prompt Engineering Capabilities
Arxiv
0+阅读 · 2月15日
Prompt Engineer: Analyzing Hard and Soft Skill Requirements in the AI Job Market
Arxiv
0+阅读 · 2月12日
TraceLLM: Leveraging Large Language Models with Prompt Engineering for Enhanced Requirements Traceability
Arxiv
0+阅读 · 2月1日
Smarter AI Through Prompt Engineering: Insights and Case Studies from Data Science Application
Arxiv
0+阅读 · 1月30日
Rec-R1: Bridging Generative Large Language Models and User-Centric Recommendation Systems via Reinforcement Learning
Arxiv
0+阅读 · 1月28日
Theoretical Foundations of Prompt Engineering: From Heuristics to Expressivity
Arxiv
0+阅读 · 1月13日
Prompting in Practice: Investigating Software Practitioners' Use of Generative AI Tools
Arxiv
0+阅读 · 1月23日
A Peek Behind the Curtain: Using Step-Around Prompt Engineering to Identify Bias and Misinformation in GenAI Models
Arxiv
0+阅读 · 1月22日
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