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Ye Shi

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 14, 2026, 10:11 PM AMS

21

papers

465

total citations

papers (21)

Unified Optimal Transport Framework for Universal Domain Adaptation

NEURIPS 2022arXiv

Guidance with Spherical Gaussian Constraint for Conditional Diffusion

NeuralDome: A Neural Modeling Pipeline on Multi-View Human-Object Interactions

Global and Local Prompts Cooperation via Optimal Transport for Federated Learning

Harmonizing Generalization and Personalization in Federated Prompt Learning

AffordDP: Generalizable Diffusion Policy with Transferable Affordance

Knowledge-Aware Federated Active Learning with Non-IID Data

HybridGait: A Benchmark for Spatial-Temporal Cloth-Changing Gait Recognition with Hybrid Explorations

CSOT: Curriculum and Structure-Aware Optimal Transport for Learning with Noisy Labels

NEURIPS 2023arXiv

A Unified Diffusion Framework for Scene-aware Human Motion Estimation from Sparse Signals

Unsupervised Cross-Domain Image Retrieval via Prototypical Optimal Transport

Contextually Affinitive Neighborhood Refinery for Deep Clustering

NEURIPS 2023arXiv

SeqAfford: Sequential 3D Affordance Reasoning via Multimodal Large Language Model

Reduced Policy Optimization for Continuous Control with Hard Constraints

NEURIPS 2023arXiv

GenPO: Generative Diffusion Models Meet On-Policy Reinforcement Learning

NEURIPS 2025arXiv

Towards Immersive Human-X Interaction: A Real-Time Framework for Physically Plausible Motion Synthesis

NLPrompt: Noise-Label Prompt Learning for Vision-Language Models

FreqPolicy: Frequency Autoregressive Visuomotor Policy with Continuous Tokens

NEURIPS 2025arXiv

Fed-CO$_{2}$: Cooperation of Online and Offline Models for Severe Data Heterogeneity in Federated Learning

Two Sides of The Same Coin: Bridging Deep Equilibrium Models and Neural ODEs via Homotopy Continuation

NEURIPS 2023arXiv

HOI-M^3: Capture Multiple Humans and Objects Interaction within Contextual Environment