{"total":17,"rows":[{"id":"2311.10766","title":"Value FULCRA: Mapping Large Language Models to the Multidimensional Spectrum of Basic Human Values","created":"2023-11-15","cited_by_count":50,"area":null},{"id":"2311.01967","title":"The language of prompting: What linguistic properties make a prompt successful?","created":"2023-11-03","cited_by_count":44,"area":null},{"id":"2306.07075","title":"Large Language Models as Tax Attorneys: A Case Study in Legal Capabilities Emergence","created":"2023-06-12","cited_by_count":42,"area":null},{"id":"2310.16570","title":"Give Me the Facts! A Survey on Factual Knowledge Probing in Pre-trained Language Models","created":"2023-10-25","cited_by_count":32,"area":null},{"id":"2310.11053","title":"Denevil: Towards Deciphering and Navigating the Ethical Values of Large Language Models via Instruction Learning","created":"2023-10-17","cited_by_count":26,"area":null},{"id":"2310.17630","title":"InstOptima: Evolutionary Multi-objective Instruction Optimization via Large Language Model-based Instruction Operators","created":"2023-10-26","cited_by_count":17,"area":null},{"id":"2404.17642","title":"Empowering Large Language Models for Textual Data Augmentation","created":"2024-04-26","cited_by_count":17,"area":null},{"id":"2310.06680","title":"Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach","created":"2023-10-10","cited_by_count":15,"area":null},{"id":"2310.15829","title":"Unnatural language processing: How do language models handle machine-generated prompts?","created":"2023-10-24","cited_by_count":8,"area":null},{"id":"2406.17513","title":"Brittle Minds, Fixable Activations: Understanding Belief Representations in Language Models","created":"2024-06-25","cited_by_count":8,"area":null},{"id":"2310.13307","title":"Test-Time Self-Adaptive Small Language Models for Question Answering","created":"2023-10-20","cited_by_count":7,"area":null},{"id":"2311.07064","title":"Prompts have evil twins","created":"2023-11-13","cited_by_count":7,"area":null},{"id":"2412.08127","title":"Evil twins are not that evil: Qualitative insights into machine-generated prompts","created":"2024-12-11","cited_by_count":5,"area":null},{"id":"2609.30243","title":"JevOut: Natural Context Can Flip Decision Models","created":"2026-09-24","cited_by_count":4,"area":null},{"id":"2502.12859","title":"PAFT: Prompt-Agnostic Fine-Tuning","created":"2025-02-18","cited_by_count":2,"area":null},{"id":"2505.02273","title":"Demystifying optimized prompts in language models","created":"2025-05-04","cited_by_count":1,"area":null},{"id":"2603.16045","title":"POaaS: Minimal-Edit Prompt Optimization as a Service to Lift Accuracy and Cut Hallucinations on On-Device sLLMs","created":"2026-03-17","cited_by_count":1,"area":null}],"next_cursor":null}