Can Unconfident LLM Annotations Be Used for Confident Conclusions?

27 August 2024

Papers citing "Can Unconfident LLM Annotations Be Used for Confident Conclusions?"

8 / 8 papers shown

Title
Always Tell Me The Odds: Fine-grained Conditional Probability Estimation Liaoyaqi Wang Zhengping Jiang Anqi Liu Benjamin Van Durme 47 0 0 02 May 2025
Fairness-Driven LLM-based Causal Discovery with Active Learning and Dynamic Scoring Khadija Zanna Akane Sano 36 0 0 21 Mar 2025
Scalable Evaluation of Online Moderation Strategies via Synthetic Simulations Dimitris Tsirmpas Ion Androutsopoulos John Pavlopoulos 31 0 0 13 Mar 2025
Model-in-the-Loop (MILO): Accelerating Multimodal AI Data Annotation with LLMs Yifan Wang David Stevens Pranay Shah Wenwen Jiang Miao Liu ... Boying Gong Daniel Lee Jiabo Hu Ning Zhang Bob Kamma 25 1 0 16 Sep 2024
Prompt Design Matters for Computational Social Science Tasks but in Unpredictable Ways Shubham Atreja Joshua Ashkinaze Lingyao Li Julia Mendelsohn Libby Hemphill 31 12 0 17 Jun 2024
Generative Agents: Interactive Simulacra of Human Behavior J. Park Joseph C. O'Brien Carrie J. Cai Meredith Ringel Morris Percy Liang Michael S. Bernstein LM&Ro AI4CE 204 1,701 0 07 Apr 2023
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 291 2,712 0 24 May 2022
With Little Power Comes Great Responsibility Dallas Card Peter Henderson Urvashi Khandelwal Robin Jia Kyle Mahowald Dan Jurafsky 214 115 0 13 Oct 2020