4 papers
Teach2Eval: An Indirect Evaluation Method for LLM by Judging How It Teaches
Yuhang Zhou, Xutian Chen, Yixin Cao +8
Recent progress in large language models (LLMs) has outpaced the development of effective evaluation methods. Traditional benchmarks rely on task-specific metrics and static datase…
Human2Robot: Learning Robot Actions from Paired Human-Robot Videos
Sicheng Xie, Haidong Cao, Zejia Weng +6
Distilling knowledge from human demonstrations is a promising way for robots to learn and act. Existing methods, which often rely on coarsely-aligned video pairs, are typically con…
VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks
Shiduo Zhang, Zhe Xu, Peiju Liu +8
General-purposed embodied agents are designed to understand the users' natural instructions or intentions and act precisely to complete universal tasks. Recently, methods based on…
ForgerySleuth: Empowering Multimodal Large Language Models for Image Manipulation Detection
Zhihao Sun, Haoran Jiang, Haoran Chen +4
Multimodal large language models have unlocked new possibilities for various multimodal tasks. However, their potential in image manipulation detection remains unexplored. When dir…