Conferences · eligible papers
AAAI
2022–2026 LIVE
2025 · 3,028 papers
このEditionに反映済みのmain full research papersのみ掲載しています。著者リンクは日本の大学への著者別所属根拠がある場合に限ります。
- Goal-Driven Reasoning in DatalogMTL with Magic Sets
日本大学: 関与なし(対象大学)
- GraSP: Simple Yet Effective Graph Similarity Predictions
日本大学: 関与なし(対象大学)
- GradQ-ViT: Robust and Efficient Gradient Quantization for Vision Transformers
日本大学: 関与なし(対象大学)
- Gradient Alignment Improves Test-Time Adaptation for Medical Image Segmentation
日本大学: 関与なし(対象大学)
- Gradient Weight-normalized Low-rank Projection for Efficient LLM Training
日本大学: 関与なし(対象大学)
- Gradient-Based Nonlinear Rehearsal Learning with Multivariate Alterations
日本大学: 関与なし(対象大学)
- Gradient-Based Sample Selection for Black-Box Universal Domain Adaptation
日本大学: 関与なし(対象大学)
- Gradient-Guided Credit Assignment and Joint Optimization for Dependency-Aware Spatial Crowdsourcing
日本大学: 関与なし(対象大学)
- Granularity-Adaptive Spatial Evidence Tokenization for Video Question Answering
日本大学: 関与なし(対象大学)
- Graph Agent Network: Empowering Nodes with Inference Capabilities for Adversarial Resilience
日本大学: 関与なし(対象大学)
- Graph Coarsening via Supervised Granular-Ball for Scalable Graph Neural Network Training
日本大学: 関与なし(対象大学)
- Graph Consistency and Diversity Measurement for Federated Multi-View Clustering
日本大学: 関与なし(対象大学)
- Graph Contrastive Learning with Joint Spectral Augmentation of Attribute and Topology
日本大学: 関与なし(対象大学)
- Graph Mixture of Experts and Memory-augmented Routers for Multivariate Time Series Anomaly Detection
日本大学: 関与なし(対象大学)
- Graph Segmentation and Contrastive Enhanced Explainer for Graph Neural Networks
日本大学: 関与なし(対象大学)
- Graph Structure Learning for Spatial-Temporal Imputation: Adapting to Node and Feature Scales
日本大学: 関与なし(対象大学)
- Graph Structure Refinement with Energy-based Contrastive Learning
日本大学: 関与なし(対象大学)
- Graph-Based Cross-Domain Knowledge Distillation for Cross-Dataset Text-to-Image Person Retrieval
日本大学: 関与なし(対象大学)
- GraphAvatar: Compact Head Avatars with GNN-Generated 3D Gaussians
日本大学: 関与なし(対象大学)
- GraphMoRE: Mitigating Topological Heterogeneity via Mixture of Riemannian Experts
日本大学: 関与なし(対象大学)
- Graphic Design with Large Multimodal Model
日本大学: 関与なし(対象大学)
- Grimm: A Plug-and-Play Perturbation Rectifier for Graph Neural Networks Defending Against Poisoning Attacks
日本大学: 関与なし(対象大学)
- Grounded Multi-Hop VideoQA in Long-Form Egocentric Videos
日本大学: 関与なし(対象大学)
- Guaranteeing Out-Of-Distribution Detection in Deep RL via Transition Estimation
日本大学: 関与なし(対象大学)
- GuideNER: Annotation Guidelines Are Better than Examples for In-Context Named Entity Recognition
日本大学: 関与なし(対象大学)
- Guided Real Image Dehazing Using YCbCr Color Space
日本大学: 関与なし(対象大学)
- Guided and Variance-Corrected Fusion with One-shot Style Alignment for Large-Content Image Generation
日本大学: 関与なし(対象大学)
- H-MBA: Hierarchical MamBa Adaptation for Multi-Modal Video Understanding in Autonomous Driving
日本大学: 関与なし(対象大学)
- HC-LLM: Historical-Constrained Large Language Models for Radiology Report Generation
日本大学: 関与なし(対象大学)
- HDLayout: Hierarchical and Directional Layout Planning for Arbitrary Shaped Visual Text Generation
日本大学: 関与なし(対象大学)
- HDT: Hierarchical Discrete Transformer for Multivariate Time Series Forecasting
日本大学: 関与なし(対象大学)
- HEP-NAS: Towards Efficient Few-shot Neural Architecture Search via Hierarchical Edge Partitioning
日本大学: 関与なし(対象大学)
- HEROS-GAN: Honed-Energy Regularized and Optimal Supervised GAN for Enhancing Accuracy and Range of Low-Cost Accelerometers
日本大学: 関与なし(対象大学)
- HFF-Tracker: A Hierarchical Fine-grained Fusion Tracker for Referring Multi-Object Tracking
日本大学: 関与なし(対象大学)
- HGSFusion: Radar-Camera Fusion with Hybrid Generation and Synchronization for 3D Object Detection
日本大学: 関与なし(対象大学)
- HHAN: Comprehensive Infectious Disease Source Tracing via Heterogeneous Hypergraph Neural Network
日本大学: 関与なし(対象大学)
- HI-DR: Exploiting Health Status-Aware Attention and an EHR Graph+ for Effective Medication Recommendation
日本大学: 関与なし(対象大学)
- HLMEA: Unsupervised Entity Alignment Based on Hybrid Language Models
日本大学: 関与なし(対象大学)
- HOGSA: Bimanual Hand-Object Interaction Understanding with 3D Gaussian Splatting Based Data Augmentation
日本大学: 関与なし(対象大学)
- HOIMamba: Efficient Mamba-based Disentangled Progressive Learning for HOI Detection
日本大学: 関与なし(対象大学)
- HS-FPN: High Frequency and Spatial Perception FPN for Tiny Object Detection
日本大学: 関与なし(対象大学)
- HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven Harmony Search and Genetic Algorithm Using LLMs
日本大学: 関与なし(対象大学)
- HSOD-BIT-V2: A Challenging Benchmark for Hyperspectral Salient Object Detection
日本大学: 関与なし(対象大学)
- HSRDiff: A Hierarchical Self-Regulation Diffusion Model for Stochastic Semantic Segmentation
日本大学: 関与なし(対象大学)
- HUANG: A Robust Diffusion Model-based Targeted Adversarial Attack Against Deep Hashing Retrieval
日本大学: 関与なし(対象大学)
- HVAdam: A Full-Dimension Adaptive Optimizer
日本大学: 関与なし(対象大学)
- HVDualformer: Histogram-Vision Dual Transformer for White Balance
日本大学: 関与なし(対象大学)
- HVIS: A Human-like Vision and Inference System for Human Motion Prediction
日本大学: 関与なし(対象大学)
- HYBOOD: A Hybrid Generative Model for Out-of-Distribution Detection with Corruption Estimation
日本大学: 関与なし(対象大学)
- HYGENE: A Diffusion-Based Hypergraph Generation Method
日本大学: 関与なし(対象大学)
- HaCore: Efficient Coreset Construction with Locality Sensitive Hashing for Vertical Federated Learning
日本大学: 関与なし(対象大学)
- Hand1000: Generating Realistic Hands from Text with Only 1,000 Images
日本大学: 関与なし(対象大学)
- HandDiffuse: Generative Controllers for Two-Hand Interactions via Diffusion Models
日本大学: 関与なし(対象大学)
- Hansel: Output Length Controlling Framework for Large Language Models
日本大学: 関与なし(対象大学)
- Harmonious Music-driven Group Choreography with Trajectory-Controllable Diffusion
日本大学: 関与なし(対象大学)
- Harmonizing Visual and Textual Embeddings for Zero-Shot Text-to-Image Customization
日本大学: 関与なし(対象大学)
- Harnessing Event Sensory Data for Error Pattern Prediction in Vehicles: A Language Model Approach
日本大学: 関与なし(対象大学)
- Harnessing Language Model for Cross-Heterogeneity Graph Knowledge Transfer
日本大学: 関与なし(対象大学)
- Harnessing Large Language Models for Knowledge Graph Question Answering via Adaptive Multi-Aspect Retrieval-Augmentation
日本大学: 関与なし(対象大学)
- Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation
日本大学: 関与なし(対象大学)
- HeGTa: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understanding
日本大学: 関与なし(対象大学)
- HeMeNet: Heterogeneous Multichannel Equivariant Network for Protein Multi-task Learning
日本大学: 関与なし(対象大学)
- HePa: Heterogeneous Graph Prompting for All-Level Classification Tasks
日本大学: 関与なし(対象大学)
- Hedging and Approximate Truthfulness in Traditional Forecasting Competitions
日本大学: 関与なし(対象大学)
- HeterGP: Bridging Heterogeneity in Graph Neural Networks with Multi-View Prompting
日本大学: 関与なし(対象大学)
- Heterogeneous Graph Neural Network on Semantic Tree
日本大学: 関与なし(対象大学)
- Heterogeneous Multi-Agent Bandits with Parsimonious Hints
日本大学: 関与なし(対象大学)
- Heterogeneous Multi-Robot Graph Coverage with Proximity and Movement Constraints
日本大学: 関与なし(対象大学)
- Heterogeneous Prompt-Guided Entity Inferring and Distilling for Scene-Text Aware Cross-Modal Retrieval
日本大学: 関与なし(対象大学)
- Heuristic-free Knowledge Distillation for Streaming ASR via Multi-modal Training
日本大学: 関与なし(対象大学)
- HiCM²: Hierarchical Compact Memory Modeling for Dense Video Captioning
日本大学: 関与なし(対象大学)
- HiGDA: Hierarchical Graph of Nodes to Learn Local-to-Global Topology for Semi-Supervised Domain Adaptation
日本大学: 関与なし(対象大学)
- HiPoser: 3D Human Pose Estimation with Hierarchical Shared Learning at Parts-Level Using Inertial Measurement Units
日本大学: 関与なし(対象大学)
- HiRED: Attention-Guided Token Dropping for Efficient Inference of High-Resolution Vision-Language Models
日本大学: 関与なし(対象大学)
- HieraFashDiff: Hierarchical Fashion Design with Multi-stage Diffusion Models
日本大学: 関与なし(対象大学)
- Hierarchical Alignment-enhanced Adaptive Grounding Network for Generalized Referring Expression Comprehension
日本大学: 関与なし(対象大学)
- Hierarchical Classification Auxiliary Network for Time Series Forecasting
日本大学: 関与なし(対象大学)
- Hierarchical Consensus Network for Multiview Feature Learning
日本大学: 関与なし(対象大学)
- Hierarchical Context Pruning: Optimizing Real-World Code Completion with Repository-Level Pretrained Code LLMs
日本大学: 関与なし(対象大学)
- Hierarchical Cross-Modal Alignment for Open-Vocabulary 3D Object Detection
日本大学: 関与なし(対象大学)
- Hierarchical Divide-and-Conquer for Fine-Grained Alignment in LLM-Based Medical Evaluation
日本大学: 関与なし(対象大学)
- Hierarchical Gradient-Based Genetic Sampling for Accurate Prediction of Biological Oscillations
日本大学: 関与なし(対象大学)
- Hierarchical Mixture of Experts: Generalizable Learning for High-Level Synthesis
日本大学: 関与なし(対象大学)
- Hierarchical Multi-Source Uncertainty Aggregation for Interactive Video Captioning
日本大学: 関与なし(対象大学)
- Hierarchical Vector Quantization for Unsupervised Action Segmentation
日本大学: 関与なし(対象大学)
- Hierarchically Controlled Deformable 3D Gaussians for Talking Head Synthesis
日本大学: 関与なし(対象大学)
- Hierarchically-Structured Open-Vocabulary Indoor Scene Synthesis with Pre-trained Large Language Model
日本大学: 関与なし(対象大学)
- High-Fidelity Polarimetric Implicit 3D Reconstruction with View-Dependent Physical Representation
日本大学: 関与なし(対象大学)
- High-Resolution Frame Interpolation with Patch-based Cascaded Diffusion
日本大学: 関与なし(対象大学)
- Higher Order Structures for Graph Explanations
日本大学: 関与なし(対象大学)
- Highly Efficient Rotation-Invariant Spectral Embedding for Scalable Incomplete Multi-View Clustering
日本大学: 関与なし(対象大学)
- Highly Imperceptible Black-Box Graph Injection Attacks with Reinforcement Learning
日本大学: 関与なし(対象大学)
- Highly Parallelized Reinforcement Learning Training with Relaxed Assignment Dependencies
日本大学: 関与なし(対象大学)
- Holistic Correction with Object Prototype for Video Object Segmentation
日本大学: 関与なし(対象大学)
- Holistic Semantic Representation for Navigational Trajectory Generation
日本大学: 関与なし(対象大学)
- HomeDiffusion: Zero-Shot Object Customization with Multi-View Representation Learning for Indoor Scenes
日本大学: 関与なし(対象大学)
- HomoMatcher: Achieving Dense Feature Matching with Semi-Dense Efficiency by Homography Estimation
日本大学: 関与なし(対象大学)
- HoneypotNet: Backdoor Attacks Against Model Extraction
日本大学: 関与なし(対象大学)
- How Do Position Encodings Affect Length Generalization? Case Studies On In-Context Function Learning
日本大学: 関与なし(対象大学)
- How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning?
日本大学: 関与なし(対象大学)