{"total":34,"rows":[{"id":"2406.07496","title":"TextGrad: Automatic \"Differentiation\" via Text","created":"2024-06-11","cited_by_count":273,"area":null},{"id":"2405.17202","title":"Efficient multi-prompt evaluation of LLMs","created":"2024-05-27","cited_by_count":73,"area":null},{"id":"2405.03644","title":"When LLMs Meet Cybersecurity: A Systematic Literature Review","created":"2024-05-06","cited_by_count":71,"area":null},{"id":"2406.15708","title":"Teach Better or Show Smarter? On Instructions and Exemplars in Automatic Prompt Optimization","created":"2024-06-22","cited_by_count":29,"area":null},{"id":"2406.04687","title":"LogiCode: an LLM-Driven Framework for Logical Anomaly Detection","created":"2024-06-07","cited_by_count":19,"area":null},{"id":"2401.04122","title":"From Prompt Engineering to Prompt Science With Human in the Loop","created":"2024-01-01","cited_by_count":12,"area":null},{"id":"2510.09201","title":"Multimodal Prompt Optimization: Why Not Leverage Multiple Modalities for MLLMs","created":"2025-10-10","cited_by_count":7,"area":null},{"id":"2403.12196","title":"Leveraging Large Language Models to Detect npm Malicious Packages","created":"2024-03-18","cited_by_count":6,"area":null},{"id":"2505.15741","title":"Large Language Models and Evolutionary Computation: A Critical Review of Bidirectional Interaction, Automated Algorithm Design, and Co-Adaptive Systems","created":"2025-05-21","cited_by_count":6,"area":null},{"id":"2505.18524","title":"metaTextGrad: Automatically optimizing language model optimizers","created":"2025-05-24","cited_by_count":6,"area":null},{"id":"2404.09022","title":"Navigating the Landscape of Large Language Models: A Comprehensive Review and Analysis of Paradigms and Fine-Tuning Strategies","created":"2024-04-13","cited_by_count":5,"area":null},{"id":"2410.12843","title":"Exploring Prompt Engineering: A Systematic Review with SWOT Analysis","created":"2024-10-09","cited_by_count":5,"area":null},{"id":"2501.05079","title":"Multimodal-to-Text Prompt Engineering in Large Language Models Using Feature Embeddings for GNSS Interference Characterization","created":"2025-01-09","cited_by_count":4,"area":null},{"id":"2604.00025","title":"Brevity Constraints Reverse Performance Hierarchies in Language Models","created":"2026-03-11","cited_by_count":4,"area":null},{"id":"2501.06689","title":"TAPO: Task-Referenced Adaptation for Prompt Optimization","created":"2025-01-12","cited_by_count":3,"area":null},{"id":"2502.17441","title":"Renaissance of Literate Programming in the Era of LLMs: Enhancing LLM-Based Code Generation in Large-Scale Projects","created":"2024-12-25","cited_by_count":3,"area":null},{"id":"2511.21714","title":"GPS: General Per-Sample Prompter","created":"2025-11-18","cited_by_count":3,"area":null},{"id":"2507.09875","title":"Function Induction and Task Generalization: An Interpretability Study with Off-by-One Addition","created":"2025-07-14","cited_by_count":2,"area":null},{"id":"2508.06729","title":"Large Language Models for Oral History Understanding with Text Classification and Sentiment Analysis","created":"2025-08-08","cited_by_count":2,"area":null},{"id":"2512.11013","title":"PIAST: Rapid Prompting with In-context Augmentation for Scarce Training data","created":"2025-12-11","cited_by_count":2,"area":null},{"id":"2407.14371","title":"Open Artificial Knowledge","created":"2024-07-19","cited_by_count":1,"area":null},{"id":"2504.12545","title":"Knowledge Acquisition on Mass-shooting Events via LLMs for AI-Driven Justice","created":"2025-04-17","cited_by_count":1,"area":null},{"id":"2507.17264","title":"Understanding Prompt Programming Tasks and Questions","created":"2025-07-23","cited_by_count":1,"area":null},{"id":"2507.19756","title":"Are You There God? Lightweight Narrative Annotation of Christian Fiction with LMs","created":"2025-07-26","cited_by_count":1,"area":null},{"id":"2511.10465","title":"Beyond Elicitation: Provision-based Prompt Optimization for Knowledge-Intensive Tasks","created":"2025-11-13","cited_by_count":1,"area":null},{"id":"2508.13072","title":"A Language-Signal-Vision Multimodal Framework for Multitask Cardiac Analysis","created":"2025-08-18","cited_by_count":0,"area":null},{"id":"2508.21097","title":"Model-Driven Quantum Code Generation Using Large Language Models and Retrieval-Augmented Generation","created":"2025-08-28","cited_by_count":0,"area":null},{"id":"2510.05921","title":"Prompt reinforcing for long-term planning of large language models","created":"2025-10-07","cited_by_count":0,"area":null},{"id":"2511.16122","title":"ELPO: Ensemble Learning Based Prompt Optimization for Large Language Models","created":"2025-11-20","cited_by_count":0,"area":null},{"id":"2511.16688","title":"Prompt-Based Value Steering of Large Language Models","created":"2025-11-14","cited_by_count":0,"area":null},{"id":"2601.15575","title":"PromptHelper: A Prompt Recommender System for Encouraging Creativity in AI Chatbot Interactions","created":"2026-01-22","cited_by_count":0,"area":null},{"id":"2602.03358","title":"GFlowPO: Generative Flow Network as a Language Model Prompt Optimizer","created":"2026-02-03","cited_by_count":0,"area":null},{"id":"2603.04292","title":"Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models","created":"2026-03-04","cited_by_count":0,"area":null},{"id":"2606.11459","title":"APEX: Automated Prompt Engineering eXpert with Dynamic Data Selection","created":"2026-06-09","cited_by_count":0,"area":null}],"next_cursor":null}