Prompting is not a substitute for probability measurements in large language models

22 May 2023

Papers citing "Prompting is not a substitute for probability measurements in large language models"

11 / 11 papers shown

Title
Do Large Language Models know who did what to whom? Joseph M. Denning Xiaohan Bryor Snefjella Idan A. Blank 50 1 0 23 Apr 2025
Language Models Fail to Introspect About Their Knowledge of Language Siyuan Song Jennifer Hu Kyle Mahowald LRM KELM HILM ELM 79 2 0 10 Mar 2025
Do Vision-Language Models Represent Space and How? Evaluating Spatial Frame of Reference Under Ambiguities Zheyuan Zhang Fengyuan Hu Jayjun Lee Freda Shi Parisa Kordjamshidi Joyce Chai Ziqiao Ma 48 11 0 22 Oct 2024
On the Challenges and Opportunities in Generative AI Laura Manduchi Kushagra Pandey Robert Bamler Ryan Cotterell Sina Daubener ... F. Wenzel Frank Wood Stephan Mandt Vincent Fortuin Vincent Fortuin 56 17 0 28 Feb 2024
Evaluating statistical language models as pragmatic reasoners Benjamin Lipkin L. Wong Gabriel Grand J. Tenenbaum 31 12 0 01 May 2023
Large Linguistic Models: Investigating LLMs' metalinguistic abilities G. Beguš M. Dąbkowski Ryan Rhodes LRM 32 18 0 01 May 2023
LMPriors: Pre-Trained Language Models as Task-Specific Priors Kristy Choi Chris Cundy Sanjari Srivastava Stefano Ermon BDL 48 35 0 22 Oct 2022
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 291 4,048 0 24 May 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 303 11,730 0 04 Mar 2022
Controlled Evaluation of Grammatical Knowledge in Mandarin Chinese Language Models Yiwen Wang Jennifer Hu R. Levy Peng Qian 9 3 0 22 Sep 2021
Reducing conversational agents' overconfidence through linguistic calibration Sabrina J. Mielke Arthur Szlam Emily Dinan Y-Lan Boureau 203 152 0 30 Dec 2020