16 citations · 36 across the 10 of their papers we have counts for
11 papers
EgoWild2Dex: Learning Dexterous Robotic Manipulation from In-the-Wild Human Experience
Kunyang Lin, Xutao Wen, Jingxi Lin +8
Egocentric human data provide a principled source of supervision for learning dexterous robot manipulation. Unlike prior approaches that often collect such data in constrained or s…
RISE: Self-Improving Robot Policy with Compositional World Model
Jiazhi Yang, Kunyang Lin, Jinwei Li +10
Despite the sustained scaling on model capacity and data acquisition, Vision-Language-Action (VLA) models remain brittle in contact-rich and dynamic manipulation tasks, where minor…
Enhancing User-Oriented Proactivity in Open-Domain Dialogues with Critic Guidance
Yufeng Wang, Jinwu Hu, Ziteng Huang +10
Open-domain dialogue systems aim to generate natural and engaging conversations, providing significant practical value in real applications such as social robotics and personal ass…
Fine-Grained Alignment in Vision-and-Language Navigation through Bayesian Optimization
Yuhang Song, Mario Gianni, Chenguang Yang +4
This paper addresses the challenge of fine-grained alignment in Vision-and-Language Navigation (VLN) tasks, where robots navigate realistic 3D environments based on natural languag…
MAGIC: Map-Guided Few-Shot Audio-Visual Acoustics Modeling
Diwei Huang, Kunyang Lin, Peihao Chen +2
Few-shot audio-visual acoustics modeling seeks to synthesize the room impulse response in arbitrary locations with few-shot observations. To sufficiently exploit the provided few-s…
DCIR: Dynamic Consistency Intrinsic Reward for Multi-Agent Reinforcement Learning
Kunyang Lin, Yufeng Wang, Peihao Chen +4
Learning optimal behavior policy for each agent in multi-agent systems is an essential yet difficult problem. Despite fruitful progress in multi-agent reinforcement learning, the c…
Event-Guided Procedure Planning from Instructional Videos with Text Supervision
An-Lan Wang, Kun-Yu Lin, Jia-Run Du +2
In this work, we focus on the task of procedure planning from instructional videos with text supervision, where a model aims to predict an action sequence to transform the initial…
Learning Vision-and-Language Navigation from YouTube Videos
Kunyang Lin, Peihao Chen, Diwei Huang +3
Vision-and-language navigation (VLN) requires an embodied agent to navigate in realistic 3D environments using natural language instructions. Existing VLN methods suffer from train…
DilateFormer: Multi-Scale Dilated Transformer for Visual Recognition
Jiayu Jiao, Yu-Ming Tang, Kun-Yu Lin +4
As a de facto solution, the vanilla Vision Transformers (ViTs) are encouraged to model long-range dependencies between arbitrary image patches while the global attended receptive f…
Weakly-Supervised Multi-Granularity Map Learning for Vision-and-Language Navigation
Peihao Chen, Dongyu Ji, Kunyang Lin +4
We address a practical yet challenging problem of training robot agents to navigate in an environment following a path described by some language instructions. The instructions oft…
Learning Active Camera for Multi-Object Navigation
Peihao Chen, Dongyu Ji, Kunyang Lin +5
Getting robots to navigate to multiple objects autonomously is essential yet difficult in robot applications. One of the key challenges is how to explore environments efficiently w…