activity
20222026
most citedOpen X-Embodiment: Robotic Learning Datasets and RT-X Models

103 citations · 120 across the 14 of their papers we have counts for

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Showing 2025Show all

7 papers · 1 filter

cs.RO2025★ 1 cited

Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer

Gemini Robotics Team, Abbas Abdolmaleki, Saminda Abeyruwan +169

General-purpose robots need a deep understanding of the physical world, advanced reasoning, and general and dexterous control. This report introduces the latest generation of the G…

cs.CV2025

OraPO: Oracle-educated Reinforcement Learning for Data-efficient and Factual Radiology Report Generation

Zhuoxiao Chen, Hongyang Yu, Ying Xu +3

Radiology report generation (RRG) aims to automatically produce clinically faithful reports from chest X-ray images. Prevailing work typically follows a scale-driven paradigm, by m…

cs.LG2025

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling

Zeyu Huang, Tianhao Cheng, Zihan Qiu +4

Existing LLMs-post-training techniques are broadly categorized into supervised fine-tuning (SFT) and reinforcement fine-tuning (RFT). Each paradigm presents a distinct trade-off: (…

cs.CV2025

DrVD-Bench: Do Vision-Language Models Reason Like Human Doctors in Medical Image Diagnosis?

Tianhong Zhou, Yin Xu, Yingtao Zhu +4

Vision-language models (VLMs) exhibit strong zero-shot generalization on natural images and show early promise in interpretable medical image analysis. However, existing benchmarks…

cs.RO2025

Towards Embodiment Scaling Laws in Robot Locomotion

Bo Ai, Liu Dai, Nico Bohlinger +7

Cross-embodiment generalization underpins the vision of building generalist embodied agents for any robot, yet its enabling factors remain poorly understood. We investigate embodim…

cs.RO2025★ 6 cited

Gemini Robotics: Bringing AI into the Physical World

Gemini Robotics Team, Saminda Abeyruwan, Joshua Ainslie +115

Recent advancements in large multimodal models have led to the emergence of remarkable generalist capabilities in digital domains, yet their translation to physical agents such as…

cs.SI2025★ 2 cited

STEC-Net: A Spatiotemporal Graph Neural Framework for Community Discovery in Dynamic Social Networks

Yingnan Xu, Shuangshuang Chu

Community discovery is a central problem in the analysis of dynamic social networks. Traditional community discovery methods mainly focus on the formation and dissolution of links…