19 citations · 21 across the 4 of their papers we have counts for
5 papers
ARISE: Adapting to Evolving Capability Gaps in Agentic Reinforcement Learning
Kun Feng, Yuchen Fang, Yiyang Tan +6
As a long-horizon agent improves through experience, previously observed weaknesses may recede while new limitations emerge, continually changing what it still needs to learn. Yet…
Xihe: Scalable Zero-Shot Time Series Learner Via Hierarchical Interleaved Block Attention
Yinbo Sun, Yuchen Fang, Zhibo Zhu +7
The rapid advancement of time series foundation models (TSFMs) has been propelled by migrating architectures from language models. While existing TSFMs demonstrate impressive perfo…
Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models
Kun Feng, Shaocheng Lan, Yuchen Fang +6
Inherent temporal heterogeneity, such as varying sampling densities and periodic structures, has posed substantial challenges in zero-shot generalization for Time Series Foundation…
ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling
Yuqi Chen, Kan Ren, Yansen Wang +3
Modeling continuous-time dynamics on irregular time series is critical to account for data evolution and correlations that occur continuously. Traditional methods including recurre…
CodeApex: A Bilingual Programming Evaluation Benchmark for Large Language Models
Lingyue Fu, Huacan Chai, Shuang Luo +13
With the emergence of Large Language Models (LLMs), there has been a significant improvement in the programming capabilities of models, attracting growing attention from researcher…