230 citations · 262 across the 24 of their papers we have counts for
6 papers · 1 filter
MTMamba++: Enhancing Multi-Task Dense Scene Understanding via Mamba-Based Decoders
Baijiong Lin, Weisen Jiang, Pengguang Chen +2
Multi-task dense scene understanding, which trains a model for multiple dense prediction tasks, has a wide range of application scenarios. Capturing long-range dependency and enhan…
MTMamba: Enhancing Multi-Task Dense Scene Understanding by Mamba-Based Decoders
Baijiong Lin, Weisen Jiang, Pengguang Chen +3
Multi-task dense scene understanding, which learns a model for multiple dense prediction tasks, has a wide range of application scenarios. Modeling long-range dependency and enhanc…
RoboCoder: Robotic Learning from Basic Skills to General Tasks with Large Language Models
Jingyao Li, Pengguang Chen, Sitong Wu +3
The emergence of Large Language Models (LLMs) has improved the prospects for robotic tasks. However, existing benchmarks are still limited to single tasks with limited generalizati…
MR-Ben: A Meta-Reasoning Benchmark for Evaluating System-2 Thinking in LLMs
Zhongshen Zeng, Yinhong Liu, Yingjia Wan +16
Large language models (LLMs) have shown increasing capability in problem-solving and decision-making, largely based on the step-by-step chain-of-thought reasoning processes. Howeve…
VLPose: Bridging the Domain Gap in Pose Estimation with Language-Vision Tuning
Jingyao Li, Pengguang Chen, Xuan Ju +2
Thanks to advances in deep learning techniques, Human Pose Estimation (HPE) has achieved significant progress in natural scenarios. However, these models perform poorly in artifici…
MOODv2: Masked Image Modeling for Out-of-Distribution Detection
Jingyao Li, Pengguang Chen, Shaozuo Yu +2
The crux of effective out-of-distribution (OOD) detection lies in acquiring a robust in-distribution (ID) representation, distinct from OOD samples. While previous methods predomin…