1 citations · 1 across the 5 of their papers we have counts for
6 papers
RLHarness: Co-evolving Procedural Skills with Reinforcement Learning for Long-horizon Multimodal Reasoning
Ziqiao Shang, Zian Xu, Ji-Chen Yan +6
Multimodal reasoning requires models to preserve visual evidence through long decision chains while selecting appropriate procedures across diverse scenarios and rules. When learni…
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…
Thinking with Tables: Enhancing Multi-Modal Tabular Understanding via Neuro-Symbolic Reasoning
Kun-Yang Yu, Zhi Zhou, Shi-Yu Tian +6
Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities across modalities such as images and text. However, tabular data, despite being a criti…
A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks
Silin Chen, Yuzhong Chen, Caiwei Wang +9
Whether artificial neural networks organize information comparably to the human brain remains unclear. Prior brain--AI alignment studies are constrained by specific inputs and task…
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…
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,…