Triangle Splatting+: Differentiable Rendering with Opaque Triangles

Kavli Affiliate: Yi Zhou | First 5 Authors: Jan Held, Jan Held, , , | Summary: Reconstructing 3D scenes and synthesizing novel views has seen rapid progress in recent years. Neural Radiance Fields demonstrated that continuous volumetric radiance fields can achieve high-quality image synthesis, but their long training and rendering times limit practicality. 3D Gaussian […]


Continue.. Triangle Splatting+: Differentiable Rendering with Opaque Triangles

Agentic Services Computing

Kavli Affiliate: Cheng Peng | First 5 Authors: Shuiguang Deng, Shuiguang Deng, , , | Summary: The rise of large language model (LLM)-powered agents is transforming services computing, moving it beyond static, request-driven functions toward dynamic, goal-oriented, and socially embedded multi-agent ecosystems. We propose Agentic Services Computing (ASC), a paradigm that reimagines services as autonomous, […]


Continue.. Agentic Services Computing

RADAR: A Risk-Aware Dynamic Multi-Agent Framework for LLM Safety Evaluation via Role-Specialized Collaboration

Kavli Affiliate: Zheng Zhu | First 5 Authors: Xiuyuan Chen, Xiuyuan Chen, , , | Summary: Existing safety evaluation methods for large language models (LLMs) suffer from inherent limitations, including evaluator bias and detection failures arising from model homogeneity, which collectively undermine the robustness of risk evaluation processes. This paper seeks to re-examine the risk […]


Continue.. RADAR: A Risk-Aware Dynamic Multi-Agent Framework for LLM Safety Evaluation via Role-Specialized Collaboration

RADAR: A Risk-Aware Dynamic Multi-Agent Framework for LLM Safety Evaluation via Role-Specialized Collaboration

Kavli Affiliate: Zheng Zhu | First 5 Authors: Xiuyuan Chen, Xiuyuan Chen, , , | Summary: Existing safety evaluation methods for large language models (LLMs) suffer from inherent limitations, including evaluator bias and detection failures arising from model homogeneity, which collectively undermine the robustness of risk evaluation processes. This paper seeks to re-examine the risk […]


Continue.. RADAR: A Risk-Aware Dynamic Multi-Agent Framework for LLM Safety Evaluation via Role-Specialized Collaboration

EgoDemoGen: Novel Egocentric Demonstration Generation Enables Viewpoint-Robust Manipulation

Kavli Affiliate: Zheng Zhu | First 5 Authors: Yuan Xu, Yuan Xu, , , | Summary: Imitation learning based policies perform well in robotic manipulation, but they often degrade under *egocentric viewpoint shifts* when trained from a single egocentric viewpoint. To address this issue, we present **EgoDemoGen**, a framework that generates *paired* novel egocentric demonstrations […]


Continue.. EgoDemoGen: Novel Egocentric Demonstration Generation Enables Viewpoint-Robust Manipulation

EMMA: Generalizing Real-World Robot Manipulation via Generative Visual Transfer

Kavli Affiliate: Zheng Zhu | First 5 Authors: Zhehao Dong, Zhehao Dong, , , | Summary: Vision-language-action (VLA) models increasingly rely on diverse training data to achieve robust generalization. However, collecting large-scale real-world robot manipulation data across varied object appearances and environmental conditions remains prohibitively time-consuming and expensive. To overcome this bottleneck, we propose Embodied […]


Continue.. EMMA: Generalizing Real-World Robot Manipulation via Generative Visual Transfer

MimicDreamer: Aligning Human and Robot Demonstrations for Scalable VLA Training

Kavli Affiliate: Zheng Zhu | First 5 Authors: Haoyun Li, Haoyun Li, , , | Summary: Vision Language Action (VLA) models derive their generalization capability from diverse training data, yet collecting embodied robot interaction data remains prohibitively expensive. In contrast, human demonstration videos are far more scalable and cost-efficient to collect, and recent studies confirm […]


Continue.. MimicDreamer: Aligning Human and Robot Demonstrations for Scalable VLA Training

MimicDreamer: Aligning Human and Robot Demonstrations for Scalable VLA Training

Kavli Affiliate: Zheng Zhu | First 5 Authors: Haoyun Li, Haoyun Li, , , | Summary: Vision Language Action (VLA) models derive their generalization capability from diverse training data, yet collecting embodied robot interaction data remains prohibitively expensive. In contrast, human demonstration videos are far more scalable and cost-efficient to collect, and recent studies confirm […]


Continue.. MimicDreamer: Aligning Human and Robot Demonstrations for Scalable VLA Training

Revealing Adversarial Smart Contracts through Semantic Interpretation and Uncertainty Estimation

Kavli Affiliate: Gang Su | First 5 Authors: Yating Liu, Yating Liu, , , | Summary: Adversarial smart contracts, mostly on EVM-compatible chains like Ethereum and BSC, are deployed as EVM bytecode to exploit vulnerable smart contracts for financial gain. Detecting such malicious contracts at the time of deployment is an important proactive strategy to […]


Continue.. Revealing Adversarial Smart Contracts through Semantic Interpretation and Uncertainty Estimation

Consistency-Aware Parameter-Preserving Knowledge Editing Framework for Multi-Hop Question Answering

Kavli Affiliate: Long Zhang | First 5 Authors: Lingwen Deng, Lingwen Deng, , , | Summary: Parameter-Preserving Knowledge Editing (PPKE) enables updating models with new or corrected information without retraining or parameter adjustment. Recent PPKE approaches based on knowledge graphs (KG) to extend knowledge editing (KE) capabilities to multi-hop question answering (MHQA). However, these methods […]


Continue.. Consistency-Aware Parameter-Preserving Knowledge Editing Framework for Multi-Hop Question Answering