Projects

Can Tabular Foundation Models Amortize Statistical Inference?

Ye, K., Gong, S., Zhou, H., Zangirolami, V. and Shi, C.

TabCon: amortized confidence intervals with tabular foundation models.

Detecting LLM-Generated Tokens in Human–LLM Coauthored Text

Lu, Y., Zhou, H., Spill, F., Ye, K., Shi, C. and Zhu, J.

Token-level detection in text coauthored by humans and LLMs.

READER: Reasoning-Enhanced AI-Generated Text Detection

Su, P^*., Ye, K^*., Gong, S., Xu, E., Zhu, J., Livieri, G. and Shi, C.

READER.

Kernelized Advantage Estimation: From Nonparametric Statistics to LLM Reasoning

Gong, S^*., Ye, K^*., Zhu, J., Zhang, X., Zhou, H. and Shi, C.

KAE.

Demystifying Group Relative Policy Optimization: Its Policy Gradient is a U-Statistic

Zhou, H^*., Ye, K^*., Xu, E., Zhu, J., Yang, Y., Gong, S. and Shi, C.

Demystifying GRPO

Robust Reinforcement Learning from Human Feedback for Large Language Models Fine-Tuning

Ye, K^*., Zhou, H^*., Zhu, J^*., Quinzan, F. and Shi, C.

VRPO.

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BASIS: Batchwise Advantage Estimation from Single-Rollout Information Sharing for LLM Reasoning (EMNLP (Findings) 2026 · Accepted)

Gong, S^*., Xu, E^*., Ye, K^*., Livieri, G., Quinzan, F. and Shi, C.

BASIS: single-rollout information sharing for LLM reasoning.

A Difference-in-Difference Approach to Detecting AI-Generated Images (CVPR 2026)

Qi, X^*., Ye, K^*., Shi, C., Yang, Y., Zhu, J. and Zhou, H.

DID detection for AI-Generated Images.

Learn-to-Distance: Distance Learning for Detecting LLM-Generated Text (ICLR 2026)

Zhou, H^*., Zhu, J^*., Xu, E., Ye, K., Yang, Y. and Shi, C.

Learn-to-Distance.

Doubly Robust Alignment for Large Language Models (NeurIPS 2025)

Xu, E^*., Ye, K^*., Zhou, H^*., Zhu, L., Quinzan, F. and Shi, C.

DRPO4LLM.

AdaDetectGPT: Adaptive Detection of LLM-Generated Text with Statistical Guarantees (NeurIPS 2025)

Zhou, H^*., Zhu, J^*., Su, P., Ye, K., Yang, Y., Gavioli-Akilagun, S. and Shi, C.

AdaDetectGPT.