most citedSeeing Across Views: Benchmarking Spatial Reasoning of Vision-Language Models in Robotic Scenes

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.MM2026

Audio-Visual World Models: Learning Physically Grounded Multisensory Dynamics

Jiahua Wang, Leqi Zheng, Jialong Wu +2

World models simulate environmental dynamics to enable embodied agents to plan and reason about future states. While real-world perception is inherently multimodal, existing approa…

cs.LG2026

Filter, Then Reweight: Rethinking Optimization Granularity in On-Policy Distillation

Yuying Li, Leqi Zheng, Yongzi Yu +6

On-Policy distillation (OPD) in large language models is shifting from full-trace KL supervision toward more selective training paradigms. Recent OPD methods increasingly focus on…

cs.CL2026

RealChart2Code: Advancing Chart-to-Code Generation with Real Data and Multi-Task Evaluation

Jiajun Zhang, Yuying Li, Zhixun Li +13

Vision-Language Models (VLMs) have demonstrated impressive capabilities in code generation across various domains. However, their ability to replicate complex, multi-panel visualiz…

cs.CV20261 cited

Seeing Across Views: Benchmarking Spatial Reasoning of Vision-Language Models in Robotic Scenes

Zhiyuan Feng, Zhaolu Kang, Qijie Wang +16

Vision-language models (VLMs) are essential to Embodied AI, enabling robots to perceive, reason, and act in complex environments. They also serve as the foundation for the recent V…

cs.CL2026

How Order-Sensitive Are LLMs? OrderProbe for Deterministic Structural Reconstruction

Yingjie He, Zhaolu Kang, Kehan Jiang +19

Large language models (LLMs) excel at semantic understanding, yet their ability to reconstruct internal structure from scrambled inputs remains underexplored. Sentence-level restor…

cs.CL2026

QuantEval: A Benchmark for Financial Quantitative Tasks in Large Language Models

Zhaolu Kang, Junhao Gong, Wenqing Hu +15

Large Language Models (LLMs) have shown strong capabilities across many domains, yet their evaluation in financial quantitative tasks remains fragmented and mostly limited to knowl…