activity
20242026
collaborators

8 papers

cs.LG2026

UserToolBench: A User-Profile-Hidden Benchmark for Personalized Decision Making in Tool-Use LLMs

Xuexiong Yin, Zechuan Chen, Yongsen Zheng +5

Tool-use LLMs are increasingly asked to act on users' behalf, but existing benchmarks usually focus on profile recall, style imitation, generic tool use, or response-level personal…

cs.AI2026

AlloSpatial: Agentic Harness Framework for Spatial Reasoning in Foundation Models

Shouwei Ruan, Bin Wang, Zhenyu Wu +5

Multimodal Foundation Models (MFMs) have made substantial progress, yet remain fragile in spatial reasoning over the physical world. A key bottleneck lies in their inability to tra…

cs.AI2026

WorldCoder-Bench: Benchmarking Physically Grounded 3D World Synthesis

Shuo Lu, Yinuo Xu, Kecheng Yu +8

Large language models (LLMs) are increasingly asked not only to write static interfaces, but to construct executable interactive worlds from natural language. Browser-native 3D, co…

cs.CL2026

Extracting and Following Paths for Robust Relational Reasoning with Large Language Models

Ge Zhang, Mohammad Ali Alomrani, Hongjian Gu +7

Large language models (LLMs) possess vast semantic knowledge but often struggle with complex reasoning tasks, particularly in relational reasoning problems such as kinship or spati…

cs.AI2026

World2Mind: Cognition Toolkit for Allocentric Spatial Reasoning in Foundation Models

Shouwei Ruan, Bin Wang, Zhenyu Wu +4

Achieving robust spatial reasoning remains a fundamental challenge for current Multimodal Foundation Models (MFMs). Existing methods either overfit statistical shortcuts via 3D gro…

cs.AI2025

Enhancing the Medical Context-Awareness Ability of LLMs via Multifaceted Self-Refinement Learning

Yuxuan Zhou, Yubin Wang, Bin Wang +4

Large language models (LLMs) have shown great promise in the medical domain, achieving strong performance on several benchmarks. However, they continue to underperform in real-worl…