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20242026
most citedAll Robots in One: A New Standard and Unified Dataset for Versatile, General-Purpose Embodied Agents

2 citations · 3 across the 18 of their papers we have counts for

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9 papers · 1 filter

cs.CL2026

INSPIRE: An Internalize-Then-Improve Approach for Example-Driven Mathematical Reasoning

Shuai Wang, Jiayi Kuang, Yinghui Li +4

Mathematical reasoning has seen rapid progress in large language models (LLMs), yet existing methods optimize predominantly for final-answer correctness, raising the question wheth…

cs.AI2026

From Atomic to Agentic: Towards Interpretable Evaluation of LLMs' Agentic Mathematical Capabilities

Jiayi Kuang, Yinghui Li, Yunze Song +11

Large Language Models (LLMs) are evolving from performing end-to-end mathematical reasoning to integrating agentic intelligence. However, most existing math benchmarks evaluate onl…

cs.RO2026

Dream2Reward: Transition-Alignment Reward Models from Positive Demonstrations for Robotic Manipulation

Haoyu Zhang, Zecui Zeng, Bin Wang +3

Learning robotic policies requires dense rewards that remain informative when behavior departs from successful demonstrations. Progress-based rewards estimate how far an observatio…

cs.RO2026

Joint On-and-Off Policy Learning for Vision-and-Language Navigation

Qingrong He, Lin Zhao, Kevin Zheng +1

Vision-and-Language Navigation (VLN) necessitates an embodied agent to navigate in the physical world by adhering to natural language instructions. Recent advancements in Vision-La…

cs.CV2026

Visually-Guided Policy Optimization for Multimodal Reasoning

Zengbin Wang, Feng Xiong, Liang Lin +5

Reinforcement learning with verifiable rewards (RLVR) has significantly advanced the reasoning ability of vision-language models (VLMs). However, the inherent text-dominated nature…

cs.AI2026

Cognitive Mismatch in Multimodal Large Language Models for Discrete Symbol Understanding

Yinghui Li, Jiayi Kuang, Peng Xing +11

Multimodal large language models (MLLMs) perform strongly on natural images, yet their ability to understand discrete visual symbols remains unclear. We present a multi-domain benc…

cs.CL2026

AR-MAP: Are Autoregressive Large Language Models Implicit Teachers for Diffusion Large Language Models?

Liang Lin, Feng Xiong, Zengbin Wang +5

Diffusion Large Language Models (DLLMs) have emerged as a powerful alternative to autoregressive models, enabling parallel token generation across multiple positions. However, pref…

cs.CV2026

TangramPuzzle: Evaluating Multimodal Large Language Models with Compositional Spatial Reasoning

Daixian Liu, Jiayi Kuang, Yinghui Li +8

Multimodal Large Language Models (MLLMs) have achieved remarkable progress in visual recognition and semantic understanding, yet precise compositional spatial reasoning under geome…

cs.RO2026

SHARE: Sharing Human Actions across Robot Embodiments through Unified Retargeting and Tracking

Haoyu Zhang, Junzhe Xu, Shibo Jin +8

The central challenge in reusing human actions across robots is the need to realize shared intent through incompatible kinematics, dynamics, and control interfaces. We present SHAR…