activity
20232026
most citedTSGBench: Time Series Generation Benchmark

2 citations · 3 across the 15 of their papers we have counts for

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5 papers · 1 filter

cs.AI2026

EvoTS-Agent: A Self-Evolving LLM Agent for Financial Time Series Change Point Detection

Lei Jiang, Ye Wei, Xinyu Xi +7

Financial time series exhibit non-stationary and heterogeneous statistical properties, making change-point detection challenging because no single unsupervised algorithm performs c…

cs.AI2026

MOSAIC: Modular Orchestration for Structured Agentic Intelligence and Composition

Yifan Bao, Xinyu Xi, Xinyu Liu +8

Automated data science is a structured model-selection problem. A solution must choose data transformations, feature representations, architecture, training procedure, evaluation p…

cs.LG2026

De-attribute to Forget for LLM Unlearning

Xinyang Lu, Jiabao Pan, Rachael Hwee Ling Sim +3

The rapid development of large language models (LLMs) has raised concerns on the use of inappropriate data for training, which has led to a growing interest in LLM unlearning. Many…

cs.LG2026

Weight-Informed Self-Explaining Clustering for Mixed-Type Tabular Data

Lehao Li, Qiang Huang, Yihao Ang +3

Clustering mixed-type tabular data is fundamental for exploratory analysis, yet remains challenging due to misaligned numerical-categorical representations, uneven and context-depe…

cs.CL2026

IDRBench: Benchmarking the Interactive Capabilities of Deep Research Agents

Yingchaojie Feng, Qiang Huang, Xiaoya Xie +4

Large Language Model (LLM)-based deep research agents perform multi-step reasoning, web exploration, and long-form report generation. In these long-horizon workflows, early deviati…