In-Context Example Ordering Guided by Label Distributions

18 February 2024

Papers citing "In-Context Example Ordering Guided by Label Distributions"

8 / 8 papers shown

Title
OptiSeq: Ordering Examples On-The-Fly for In-Context Learning R. Bhope Praveen Venkateswaran K. R. Jayaram Vatche Isahagian Vinod Muthusamy N. Venkatasubramanian 52 0 0 20 Feb 2025
Beyond Perplexity: Multi-dimensional Safety Evaluation of LLM Compression Zhichao Xu Ashim Gupta Tao Li Oliver Bentham Vivek Srikumar 40 8 0 06 Jul 2024
Eliminating Position Bias of Language Models: A Mechanistic Approach Ziqi Wang Hanlin Zhang Xiner Li Kuan-Hao Huang Chi Han Shuiwang Ji Sham Kakade Hao Peng Heng Ji 49 12 0 01 Jul 2024
Token-based Decision Criteria Are Suboptimal in In-context Learning Hakaze Cho Yoshihiro Sakai Mariko Kato Kenshiro Tanaka Akira Ishii Naoya Inoue 40 2 0 24 Jun 2024
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 293 4,077 0 24 May 2022
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity Yao Lu Max Bartolo Alastair Moore Sebastian Riedel Pontus Stenetorp AILaw LRM 277 1,117 0 18 Apr 2021
What Makes Good In-Context Examples for GPT- $3$ ? Jiachang Liu Dinghan Shen Yizhe Zhang Bill Dolan Lawrence Carin Weizhu Chen AAML RALM 275 1,312 0 17 Jan 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,916 0 31 Dec 2020