3 papers
cs.CL2026
Why Prompt Optimization Works, and Why It Sometimes Doesn't: A Causal-Inspired Edit-Level Analysis
Shuzhi Gong, Hechuan Wen
Automated prompt optimization methods (e.g., DSpy, TextGrad) can substantially improve the performance of large language model (LLM), however, their generalization ability across d…
cs.CV2025
Lay-Your-Scene: Natural Scene Layout Generation with Diffusion Transformers
Divyansh Srivastava, Xiang Zhang, He Wen +2
We present Lay-Your-Scene (shorthand LayouSyn), a novel text-to-layout generation pipeline for natural scenes. Prior scene layout generation methods are either closed-vocabulary or…
cs.IR2025
Automated Query-Product Relevance Labeling using Large Language Models for E-commerce Search
Jayant Sachdev, Sean D Rosario, Abhijeet Phatak +3
Accurate query-product relevance labeling is indispensable to generate ground truth dataset for search ranking in e-commerce. Traditional approaches for annotating query-product pa…