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20232026
most citedA Systematic Survey of Automatic Prompt Optimization Techniques

14 citations · 15 across the 9 of their papers we have counts for

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cs.CL2025

BoundRL: Efficient Structured Text Segmentation through Reinforced Boundary Generation

Haoyuan Li, Zhengyuan Shen, Sullam Jeoung +6

Structured texts refer to texts containing structured elements beyond plain texts, such as code snippets and placeholders. Such structured texts increasingly require segmentation i…

cs.CL2025

PromptPrism: A Linguistically-Inspired Taxonomy for Prompts

Sullam Jeoung, Yueyan Chen, Yi Zhang +3

Prompts are the interface for eliciting the capabilities of large language models (LLMs). Understanding their structure and components is critical for analyzing LLM behavior and op…

cs.CL2025★ 14 cited

A Systematic Survey of Automatic Prompt Optimization Techniques

Kiran Ramnath, Kang Zhou, Sheng Guan +18

Since the advent of large language models (LLMs), prompt engineering has been a crucial step for eliciting desired responses for various Natural Language Processing (NLP) tasks. Ho…

cs.CL2025★ 1 cited

Examining Alignment of Large Language Models through Representative Heuristics: The Case of Political Stereotypes

Sullam Jeoung, Yubin Ge, Haohan Wang +1

Examining the alignment of large language models (LLMs) has become increasingly important, e.g., when LLMs fail to operate as intended. This study examines the alignment of LLMs wi…

cs.CL2024

Beyond Binary Gender Labels: Revealing Gender Biases in LLMs through Gender-Neutral Name Predictions

Zhiwen You, HaeJin Lee, Shubhanshu Mishra +4

Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can…

cs.CL2023

StereoMap: Quantifying the Awareness of Human-like Stereotypes in Large Language Models

Sullam Jeoung, Yubin Ge, Jana Diesner

Large Language Models (LLMs) have been observed to encode and perpetuate harmful associations present in the training data. We propose a theoretically grounded framework called Ste…

cs.CL2023

Examining the Causal Effect of First Names on Language Models: The Case of Social Commonsense Reasoning

Sullam Jeoung, Jana Diesner, Halil Kilicoglu

As language models continue to be integrated into applications of personal and societal relevance, ensuring these models' trustworthiness is crucial, particularly with respect to p…