4 citations · 12 across the 22 of their papers we have counts for
27 papers
Adaptive Role Assignment and Controlled Feature Reconstruction for Federated Image Semantic Communication
Yuxuan Chen, Jiao Bie, Hang Qi +1
Hybrid federated semantic communication enables user equipment (UEs) to contribute model updates or semantic features under a shared training framework. However, heterogeneous role…
Continual Humanoid Motion Learning
Zhewen He, Hao Huang, Geeta Chandra Raju Bethala +4
Humanoid whole-body controllers can now track a diverse set of dynamic motions, but they are typically trained offline and then frozen, so teaching such a controller a new skill te…
DINO Eats Geometry: Self-Supervised Sign Representations that Absorb Articulated Hand Geometry
Junyi Hu, Zhewen He, Haomian Huang +4
Handshape and orientation are geometric components of sign language, yet many sign encoders learn from appearance alone. We introduce SignDEG (DINO Eats Geometry), a temporal sign…
Focus Where It Counts: A Salience-Driven Vision-Language Model for Low Vision Assistance
Jiazhao Liang, Hao Huang, Shuaihang Yuan +8
Vision-language models (VLMs) are rapidly progressing and offer promising capabilities for assistive technologies supporting persons with blindness or low vision. However, existing…
VTaMo: Video-Text Alignment Model for Sign Language Translation
Junyi Hu, Zhewen He, Haomian Huang +2
Sign language translation (SLT) converts continuous sign videos into spoken language text. Gloss-free approaches leverage pre-trained visual encoders and language models but rely o…
SignNet-1M: Large-Scale Multilingual Sign Language Video Dataset with Downstream Benchmarks
Zhewen He, Junyi Hu, Haomian Huang +3
Sign language models are typically trained on datasets captured under constrained conditions, with limited viewpoint, background, and signer-identity diversity, leading to poor rob…
One-shot Adaptation of Humanoid Whole-body Motion with Walking Priors
Hao Huang, Geeta Chandra Raju Bethala, Shuaihang Yuan +4
Whole-body humanoid motion represents a fundamental challenge in robotics, requiring balance, coordination, and adaptability to enable human-like behaviors. However, existing metho…
CurveFlow: Curvature-Guided Flow Matching for Image Generation
Yan Luo, Drake Du, Hao Huang +2
Existing rectified flow models are based on linear trajectories between data and noise distributions. This linearity enforces zero curvature, which can inadvertently force the imag…
FairFedMed: Benchmarking Group Fairness in Federated Medical Imaging with FairLoRA
Minghan Li, Congcong Wen, Yu Tian +5
Fairness remains a critical concern in healthcare, where unequal access to services and treatment outcomes can adversely affect patient health. While Federated Learning (FL) presen…
Wavelet Policy: Lifting Scheme for Policy Learning in Long-Horizon Tasks
Hao Huang, Shuaihang Yuan, Geeta Chandra Raju Bethala +3
Policy learning focuses on devising strategies for agents in embodied artificial intelligence systems to perform optimal actions based on their perceived states. One of the key cha…
FastMap: Real-Time Semantic Map Completion via Bitwise Masked Modeling
Yijie Deng, Shuaihang Yuan, Congcong Wen +4
Semantic map completion, which predicts the layout of unobserved regions from partial observations, is a critical capability for indoor robot navigation. Existing approaches either…
H2-COMPACT: Human-Humanoid Co-Manipulation via Adaptive Contact Trajectory Policies
Geeta Chandra Raju Bethala, Hao Huang, Niraj Pudasaini +5
We present a hierarchical policy-learning framework that enables a legged humanoid to cooperatively carry extended loads with a human partner using only haptic cues for intent infe…
Humanoid Agent via Embodied Chain-of-Action Reasoning with Multimodal Foundation Models for Zero-Shot Loco-Manipulation
Congcong Wen, Geeta Chandra Raju Bethala, Yu Hao +8
Humanoid loco-manipulation, which integrates whole-body locomotion with dexterous manipulation, remains a fundamental challenge in robotics. Beyond whole-body coordination and bala…
A Chain-of-Thought Subspace Meta-Learning for Few-shot Image Captioning with Large Vision and Language Models
Hao Huang, Shuaihang Yuan, Yu Hao +2
A large-scale vision and language model that has been pretrained on massive data encodes visual and linguistic prior, which makes it easier to generate images and language that are…
Integrating Retrospective Framework in Multi-Robot Collaboration
Jiazhao Liang, Hao Huang, Yu Hao +4
Recent advancements in Large Language Models (LLMs) have demonstrated substantial capabilities in enhancing communication and coordination in multi-robot systems. However, existing…
On Demographic Group Fairness Guarantees in Deep Learning
Yan Luo, Congcong Wen, Min Shi +3
We present a theoretical framework analyzing the relationship between data distributions and fairness guarantees in equitable deep learning. We establish novel bounds that account…
GAMap: Zero-Shot Object Goal Navigation with Multi-Scale Geometric-Affordance Guidance
Shuaihang Yuan, Hao Huang, Yu Hao +3
Zero-Shot Object Goal Navigation (ZS-OGN) enables robots or agents to navigate toward objects of unseen categories without object-specific training. Traditional approaches often le…
Reliable Semantic Understanding for Real World Zero-shot Object Goal Navigation
Halil Utku Unlu, Shuaihang Yuan, Congcong Wen +3
We introduce an innovative approach to advancing semantic understanding in zero-shot object goal navigation (ZS-OGN), enhancing the autonomy of robots in unfamiliar environments. T…
Exploring the Reliability of Foundation Model-Based Frontier Selection in Zero-Shot Object Goal Navigation
Shuaihang Yuan, Halil Utku Unlu, Hao Huang +3
In this paper, we present a novel method for reliable frontier selection in Zero-Shot Object Goal Navigation (ZS-OGN), enhancing robotic navigation systems with foundation models t…
Zero-shot Object Navigation with Vision-Language Models Reasoning
Congcong Wen, Yisiyuan Huang, Hao Huang +6
Object navigation is crucial for robots, but traditional methods require substantial training data and cannot be generalized to unknown environments. Zero-shot object navigation (Z…
Curvature Diversity-Driven Deformation and Domain Alignment for Point Cloud
Mengxi Wu, Hao Huang, Yi Fang +1
Unsupervised Domain Adaptation (UDA) is crucial for reducing the need for extensive manual data annotation when training deep networks on point cloud data. A significant challenge…
Socially-Aware Robot Navigation Enhanced by Bidirectional Natural Language Conversations Using Large Language Models
Congcong Wen, Yifan Liu, Geeta Chandra Raju Bethala +7
Robot navigation is crucial across various domains, yet traditional methods focus on efficiency and obstacle avoidance, often overlooking human behavior in shared spaces. With the…
FairDomain: Achieving Fairness in Cross-Domain Medical Image Segmentation and Classification
Yu Tian, Congcong Wen, Min Shi +6
Addressing fairness in artificial intelligence (AI), particularly in medical AI, is crucial for ensuring equitable healthcare outcomes. Recent efforts to enhance fairness have intr…
FairCLIP: Harnessing Fairness in Vision-Language Learning
Yan Luo, Min Shi, Muhammad Osama Khan +9
Fairness is a critical concern in deep learning, especially in healthcare, where these models influence diagnoses and treatment decisions. Although fairness has been investigated i…