1 citations · 1 across the 6 of their papers we have counts for
8 papers
Thinking in Depth: Retrospective Inference for Tabular Foundation Models
Hao-Run Cai, Si-Yang Liu, Zi-Jian Cheng +8
Tabular foundation models (TFMs) are pretrained across diverse tabular tasks and make predictions on a new table at inference time using its labeled examples as context. Most recen…
SymboLLM-FE: LLM-Accelerated Symbolic Regression for Automated Feature Engineering on Tabular Data
Zi-Jian Cheng, Zi-Yi Jia, Zhi Zhou +2
Tabular data, as a core data format in machine learning, often lacks the discriminative power needed for high-performance modeling due to insufficient feature informativeness. Auto…
Can Agents Generalize to the Open World? Unveiling the Fragility of Static Training in Tool Use
Song-Lin Lv, Weiming Wu, Rui Zhu +2
While Large Language Model (LLM) agents demonstrate proficiency in static benchmarks, their deployment in real-world scenarios is hindered by the dynamic nature of user queries, to…
LifeBench: A Benchmark for Long-Horizon Multi-Source Memory
Zihao Cheng, Weixin Wang, Yu Zhao +15
Long-term memory is fundamental for personalized agents capable of accumulating knowledge, reasoning over user experiences, and adapting across time. However, existing memory bench…
MapTab: A Diagnostic Benchmark for Long-Horizon Multi-Criteria Multimodal Reasoning on Heterogeneous Topological Graphs
Ziqiao Shang, Ling-Yue Ge, Zian Xu +10
Systematically evaluating Multimodal Large Language Models (MLLMs) is essential for advancing Artificial General Intelligence (AGI). Yet existing benchmarks remain inadequate for r…
Realistic Evaluation of TabPFN v2 in Open Environments
Zi-Jian Cheng, Zi-Yi Jia, Zhi Zhou +2
Tabular data, owing to its ubiquitous presence in real-world domains, has garnered significant attention in machine learning research. While tree-based models have long dominated t…
TabularMath: Understanding Math Reasoning over Tables with Large Language Models
Shi-Yu Tian, Zhi Zhou, Wei Dong +5
Mathematical reasoning has long been a key benchmark for evaluating large language models. Although substantial progress has been made on math word problems, the need for reasoning…
TabFSBench: Tabular Benchmark for Feature Shifts in Open Environments
Zi-Jian Cheng, Zi-Yi Jia, Zhi Zhou +2
Tabular data is widely utilized in various machine learning tasks. Current tabular learning research predominantly focuses on closed environments, while in real-world applications,…