3 citations · 3 across the 1 of their papers we have counts for
4 papers
SPRIG: Improving Large Language Model Performance by System Prompt Optimization
Lechen Zhang, Tolga Ergen, Lajanugen Logeswaran +2
Large Language Models (LLMs) have shown impressive capabilities in many scenarios, but their performance depends, in part, on the choice of prompt. Past research has focused on opt…
Cross-Lingual Prompt Steerability: Towards Accurate and Robust LLM Behavior across Languages
Lechen Zhang, Yusheng Zhou, Tolga Ergen +3
System prompts provide a lightweight yet powerful mechanism for conditioning large language models (LLMs) at inference time. While prior work has focused on English-only settings,…
MapExplorer: New Content Generation from Low-Dimensional Visualizations
Xingjian Zhang, Ziyang Xiong, Shixuan Liu +6
Low-dimensional visualizations, or "projection maps," are widely used in scientific and creative domains to interpret large-scale and complex datasets. These visualizations not onl…
Clear Preferences Leave Traces: Reference Model-Guided Sampling for Preference Learning
Nirav Diwan, Tolga Ergen, Dongsub Shim +1
Direct Preference Optimization (DPO) has emerged as a de-facto approach for aligning language models with human preferences. Recent work has shown DPO's effectiveness relies on tra…