Automated Primary Hyperparathyroidism Screening with Neural Networks. - Noah Ziems; Shaoen Wu; Jim Norman (GLOBECOM, 2021)

Security Vulnerability Detection Using Deep Learning Natural Language Processing. - Noah Ziems; Shaoen Wu (INFOCOM Workshops, 2021)

Human Health Activity Intelligence Based on mmWave Sensing and Attention Learning. - Yichen Gao; Noah Ziems; Shaoen Wu; Honggang Wang 001; Mahmoud Daneshmand (GLOBECOM, 2022)

CodeDSI: Differentiable Code Search. - Usama Nadeem; Noah Ziems; Shaoen Wu (CoRR, 2022)

Large Language Models are Built-in Autoregressive Search Engines. - Noah Ziems; Wenhao Yu 002; Zhihan Zhang 001; Meng Jiang 001 (ACL (Findings), 2023)

Embedding Mental Health Discourse for Community Recommendation. - Hy Dang; Bang Nguyen; Noah Ziems; Meng Jiang 001 (CoRR, 2023)

Explaining Tree Model Decisions in Natural Language for Network Intrusion Detection. - Noah Ziems; Gang Liu 025; John Flanagan; Meng Jiang 001 (CoRR, 2023)

TOWER: Tree Organized Weighting for Evaluating Complex Instructions. - Noah Ziems; Zhihan Zhang 001; Meng Jiang 001 (EMNLP (Findings), 2024)

Optimizing Decomposition for Optimal Claim Verification. - Yining Lu; Noah Ziems; Hy Dang; Meng Jiang 001 (ACL (1), 2025)

Limitations of the LLM-as-a-Judge Approach for Evaluating LLM Outputs in Expert Knowledge Tasks. - Annalisa Szymanski; Noah Ziems; Heather A. Eicher-Miller; Toby Jia-Jun Li; Meng Jiang 001; Ronald A. Metoyer (IUI, 2025)

GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning. - Lakshya A. Agrawal; Shangyin Tan; Dilara Soylu; Noah Ziems; Rishi Khare; Krista Opsahl-Ong; Arnav Singhvi; Herumb Shandilya; Michael J. Ryan; Meng Jiang; Christopher Potts; Koushik Sen; et al. (CoRR, 2025)

Multi-module GRPO: Composing Policy Gradients and Prompt Optimization for Language Model Programs. - Noah Ziems; Dilara Soylu; Lakshya A. Agrawal; Isaac Miller; Liheng Lai; Chen Qian; Kaiqiang Song; Meng Jiang; Daniel Klein 001; Matei Zaharia; Karel D'Oosterlinck; Christopher Potts; et al. (CoRR, 2025)