Showing cs.CLShow all
3 papers · 1 filter
cs.CL2026
SPEAR: Code-Augmented Agentic Prompt Optimization
Mengyin Lu, Cong Feng, Huimin Han +6
Automatic prompt engineering (APE) rewrites prompts to improve downstream task performance, but existing APE loops treat the optimizer itself as a fixed pipeline. We port the code-…
cs.CL2025
ProCut: LLM Prompt Compression via Attribution Estimation
Zhentao Xu, Fengyi Li, Albert Chen +1
In large-scale industrial LLM systems, prompt templates often expand to thousands of tokens as teams iteratively incorporate sections such as task instructions, few-shot examples,…
cs.CL2025
BP-Seg: A graphical model approach to unsupervised and non-contiguous text segmentation using belief propagation
Fengyi Li, Kayhan Behdin, Natesh Pillai +3
Text segmentation based on the semantic meaning of sentences is a fundamental task with broad utility in many downstream applications. In this paper, we propose a graphical model-b…