collaborators

7 papers

cs.PF2026

Inference of Component Effect on System Performance

Chenxi Wang, Lei Wang, Wanling Gao +5

In a computer system, multiple components--such as the CPU, memory, and others--work together as a system whose performance can be directly measured. However, the effect of a compo…

cs.LG2026

CombinationTS: A Modular Framework for Understanding Time-Series Forecasting Models

Xiaorui Wang, Fanda Fan, Chenxi Wang +9

Recent progress in time-series forecasting has led to rapidly increasing architectural complexity, yet many reported State-of-the-Art gains are statistically fragile or misattribut…

cs.CL2026

Probing Memes in LLMs: A Paradigm for the Entangled Evaluation World

Luzhou Peng, Zhengxin Yang, Honglu Ji +6

Current evaluation paradigms for large language models (LLMs) characterize models and datasets separately, yielding coarse descriptions: items in datasets are treated as pre-labele…

cs.LG2026

TimeMosaic: Temporal Heterogeneity Guided Time Series Forecasting via Adaptive Granularity Patch and Segment-wise Decoding

Kuiye Ding, Fanda Fan, Chunyi Hou +4

Multivariate time series forecasting is essential in domains such as finance, transportation, climate, and energy. However, existing patch-based methods typically adopt fixed-lengt…

stat.ME2025

On Meta-Evaluation

Hongxiao Li, Chenxi Wang, Fanda Fan +4

Evaluation is the foundation of empirical science, yet the evaluation of evaluation itself -- so-called meta-evaluation -- remains strikingly underdeveloped. While methods such as…

cs.LG2025

KAIROS: Unified Training for Universal Non-Autoregressive Time Series Forecasting

Kuiye Ding, Fanda Fan, Zheya Wang +5

In the World Wide Web, reliable time series forecasts provide the forward-looking signals that drive resource planning, cache placement, and anomaly response, enabling platforms to…