Jiamin Jiang — accepted AI-conference papers

2026

Graph of States: Solving Abductive Tasks with Large Language Models

Yu Luo, Rongchen Gao, Lu Teng, Xidao Wen, Jiamin Jiang, Qingliang Zhang +6

ICML 2026poster

Logical reasoning encompasses deduction, induction, and abduction. However, while Large Language Models (LLMs) have effectively mastered the former two, abductive reasoning remains significantly underexplored. Existing frameworks, predominantly designed for static deductive tasks, fail to generalize…

Cited by 0 Source ↗Scholar ↗

2026

MeshTok: Efficient Multi-Scale Tokenization for Scalable PDE Transformers

Zhao Yanshun, Xiaoyu Peng, Congcong Zhu, Jiamin Jiang, Jingrun Chen

ICML 2026poster

Conventional patchified Transformers operate on uniform spatial partitions, distributing computational effort evenly across the domain irrespective of local features. This inflexible tokenization scheme is inherently limited in its ability to efficiently represent and process solutions to complex PD…

Cited by 0 Source ↗Scholar ↗