Qitai Tan — accepted AI-conference papers

2026

Sculptor: Empowering LLMs with Cognitive Agency via Active Context Management

Mo Li, L.H. Xu, Qitai Tan, Long Ma, Ting Cao, Yunxin Liu +1

ICLR 2026poster

Large Language Models (LLMs) suffer from significant performance degradation when processing long contexts due to proactive interference, where irrelevant information in earlier parts of the context disrupts reasoning and memory recall. While most research focuses on external memory systems to augme…

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2025

SynTSBench: Rethinking Temporal Pattern Learning in Deep Learning Models for Time Series

Qitai Tan, Yiyun Chen, Mo Li, Ruiwen Gu, Yilin Su, Xiao-Ping Zhang

NeurIPS 2025poster

Recent advances in deep learning have driven rapid progress in time series forecasting, yet many state-of-the-art models continue to struggle with robust performance in real-world applications, even when they achieve strong results on standard benchmark datasets. This persistent gap can be attribute…

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