Jingchu Gai

According to our database, Jingchu Gai authored at least 10 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Momentum Streams for Optimizer-Inspired Transformers.

Jingchu Gai, Nai-Chieh Huang, Jiayun Wu

CoRR, May, 2026

Understanding and Mitigating Premature Confidence for Better LLM Reasoning.

Jingchu Gai, Guanning Zeng, Christina Baek, Chen Wu, J. Zico Kolter, Andrej Risteski, Aditi Raghunathan

CoRR, May, 2026

Lossless Anti-Distillation Sampling.

Zibo Diao, Jingchu Gai, Xinyue Ai, Zhang Zhang, Zhenyu He, Di He

CoRR, May, 2026

Taming the Curses of Multiagency in Robust Markov Games with Large State Space through Linear Function Approximation.

Jingchu Gai, Laixi Shi

CoRR, May, 2026

Towards Solving the Gilbert-Pollak Conjecture via Large Language Models.

Yisi Ke, Tianyu Huang, Yankai Shu, Di He, Jingchu Gai, Liwei Wang

CoRR, January, 2026

2025

Differential Smoothing Mitigates Sharpening and Improves LLM Reasoning.

Jingchu Gai, Guanning Zeng, Huaqing Zhang, Aditi Raghunathan

CoRR, November, 2025

Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning.

Laixi Shi, Jingchu Gai, Eric Mazumdar, Yuejie Chi, Adam Wierman

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Homomorphism Expressivity of Spectral Invariant Graph Neural Networks.

Jingchu Gai, Yiheng Du, Bohang Zhang, Haggai Maron, Liwei Wang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Can We Break the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning?

Laixi Shi, Jingchu Gai, Eric Mazumdar, Yuejie Chi, Adam Wierman

CoRR, 2024

Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness.

Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang

Proceedings of the Twelfth International Conference on Learning Representations, 2024