Conferences · eligible papers
AAAI
2022–2026 LIVE
2026 · 4,149 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。
- S2-Boost: Synergistic Semantic Boosting for Coarse-to-Fine Ensemble Learning
日本大学: 関与なし(対象大学)
- S2-UniSeg: Fast Universal Agglomerative Pooling for Scalable Segment Anything Without Supervision
日本大学: 関与なし(対象大学)
- S2C: A Noise-Resistant Difference Learning Framework for Unsupervised Change Detection in VHR Remote Sensing Images
日本大学: 関与なし(対象大学)
- S2D-Align: Shallow-to-Deep Auxiliary Learning for Anatomically-Grounded Radiology Report Generation
日本大学: 関与なし(対象大学)
- S3Net: Spatiotemporally Separated Sparse Network for Neuromorphic Vision Processing
日本大学: 関与なし(対象大学)
- S5: Scalable Semi-Supervised Semantic Segmentation in Remote Sensing
日本大学: 関与なし(対象大学)
- SABER: Switchable and Balanced Training for Efficient LLM Reasoning
日本大学: 関与なし(対象大学)
- SACO: Sequence-Aware Constrained Optimization Framework for Coupon Distribution in E-commerce
日本大学: 関与なし(対象大学)
- SACodec: Asymmetric Quantization with Semantic Anchoring for Low-Bitrate High-Fidelity Neural Speech Codecs
日本大学: 関与なし(対象大学)
- SAFE: Semantic- and Frequency-Enhanced Curriculum for Cross-Domain Deepfake Detection
日本大学: 関与なし(対象大学)
- SAGA: Learning Signal-Aligned Distributions for Improved Text-to-Image Generation
日本大学: 関与なし(対象大学)
- SAGE: Spuriousness-Aware Guided Prompt Exploration for Mitigating Multimodal Bias
日本大学: 関与なし(対象大学)
- SAGE: Structured Attribute-Guided Enhancement for GZSL
日本大学: 関与なし(対象大学)
- SALR: Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models
日本大学: 関与なし(対象大学)
- SAM-DAQ: Segment Anything Model with Depth-guided Adaptive Queries for RGB-D Video Salient Object Detection
日本大学: 関与なし(対象大学)
- SAM2-OV: A Novel Detection-Only Tuning Paradigm for Open-Vocabulary Multi-Object Tracking
日本大学: 関与なし(対象大学)
- SAM2MOT: A Novel Paradigm of Multi-Object Tracking by Segmentation
日本大学: 関与なし(対象大学)
- SAMCL: Empowering SAM to Continually Learn from Dynamic Domains with Extreme Storage Efficiency
日本大学: 関与なし(対象大学)
- SAME: Spatial-Aware Multimodal Egocentric Human Pose Estimation
日本大学: 関与なし(対象大学)
- SAMGTD: Spatial-Aware Masked Graph Transformer-Diffusion Model for Enhanced Cell Type Deconvolution in Spatial Transcriptomics
日本大学: 関与なし(対象大学)
- SAOT: An Enhanced Locality-Aware Spectral Transformer for Solving PDEs
日本大学: 関与なし(対象大学)
- SAPO: Self-Adaptive Process Optimization Makes Small Reasoners Stronger
日本大学: 関与なし(対象大学)
- SAQ-SAM: Semantically-Aligned Quantization for Segment Anything Model
日本大学: 関与なし(対象大学)
- SAR-DisentDM: A Semantic-Disentangled Diffusion Model for Limited-Data SAR Image Synthesis
日本大学: 関与なし(対象大学)
- SAR: A Structure-Aligned Reasoning Framework for Temporal Knowledge Graph Question Answering
日本大学: 関与なし(対象大学)
- SASST: Leveraging Syntax-Aware Chunking and LLMs for Simultaneous Speech Translation
日本大学: 奈良先端科学技術大学院大学 / 沖縄科学技術大学院大学
- SAVER: Mitigating Hallucinations in Large Vision-Language Models via Style-Aware Visual Early Revision
日本大学: 関与なし(対象大学)
- SA²GFM: Enhancing Robust Graph Foundation Models with Structure-Aware Semantic Augmentation
日本大学: 関与なし(対象大学)
- SC-Net: Robust Correspondence Learning via Spatial and Cross-Channel Context
日本大学: 関与なし(対象大学)
- SCALAR: Scale-wise Controllable Visual Autoregressive Learning
日本大学: 関与なし(対象大学)
- SCALE: Selective Resource Allocation for Overcoming Performance Bottlenecks in Mathematical Test-time Scaling
日本大学: 関与なし(対象大学)
- SCAN: Self-Calibrated AutoregressioN for High-Quality Visual Generation
日本大学: 関与なし(対象大学)
- SCIR: A Self-Correcting Iterative Refinement Framework for Enhanced Information Extraction Based on Schema
日本大学: 関与なし(対象大学)
- SCOPE: Intrinsic Semantic Space Control for Mitigating Copyright Infringement in LLMs
日本大学: 関与なし(対象大学)
- SCORE: Semantic Collage by Optimizing Rendered Elements
日本大学: 関与なし(対象大学)
- SCo-Cloud: Satellite Constellation Collaboration for Cloud-Aware Onboard-Computed Imaging and Transmission
日本大学: 関与なし(対象大学)
- SCoNE: Spherical Consistent Neighborhoods Ensemble for Effective and Efficient Multi-View Anomaly Detection
日本大学: 関与なし(対象大学)
- SCoUT: A Framework for Structured Stereotype Analysis in Language Models
日本大学: 関与なし(対象大学)
- SD-PSFNet: Sequential and Dynamic Point Spread Function Network for Image Deraining
日本大学: 関与なし(対象大学)
- SDA: Steering-Driven Distribution Alignment for Open LLMs Without Fine-Tuning
日本大学: 関与なし(対象大学)
- SDE-HARL: Scalable Distributed Policy Execution for Heterogeneous-Agent Reinforcement Learning
日本大学: 関与なし(対象大学)
- SDEval: Safety Dynamic Evaluation for Multimodal Large Language Models
日本大学: 関与なし(対象大学)
- SDNet: LiDAR Semantic Scene Completion with Sparse-Dense Fusion and Input-Aware Label Refinement
日本大学: 関与なし(対象大学)
- SE360: Semantic Edit in 360° Panoramas via Hierarchical Data Construction
日本大学: 関与なし(対象大学)
- SEA-PACE: Semi-Supervised Underwater Image Enhancement via Gaussian Process–Assisted Self-Paced Learning
日本大学: 関与なし(対象大学)
- SEAP: Sparse Expert Activation Pruning Unlocks the Brainpower of Large Language Models
日本大学: 関与なし(対象大学)
- SEBSFormer: A Spectral-Enhanced Bi-Stream Transformer for Robust EEG Decoding
日本大学: 関与なし(対象大学)
- SEED: Spectral Entropy-Guided Evaluation of Spatial-Temporal Dependencies for Multivariate Time Series Forecasting
日本大学: 関与なし(対象大学)
- SEFEL: A Simple Yet Effective Framework for Fast Event Linking
日本大学: 関与なし(対象大学)
- SELDON: Supernova Explosions Learned by Deep ODE Networks
日本大学: 関与なし(対象大学)
- SEMC: Structure-Enhanced Mixture-of-Experts Contrastive Learning for Ultrasound Standard Plane Recognition
日本大学: 関与なし(対象大学)
- SEQRET: Mining Rule Sets from Event Sequences
日本大学: 関与なし(対象大学)
- SERL: Self-Examining Reinforcement Learning on Open-Domain
日本大学: 関与なし(対象大学)
- SEVADE: Self-Evolving Multi-Agent Analysis with Decoupled Evaluation for Hallucination-Resistant Sarcasm Detection
日本大学: 関与なし(対象大学)
- SFGA: Similarity-Constrained Fusion Learning for Unsupervised Anomaly Detection in Multiplex Graphs
日本大学: 関与なし(対象大学)
- SFedHIFI: Fire Rate-Based Heterogeneous Information Fusion for Spiking Federated Learning
日本大学: 関与なし(対象大学)
- SGAT: Learning Feature Matching with Singularity-enhanced Graph Attention Network
日本大学: 関与なし(対象大学)
- SGMHand: Structure-Guided Modulation for Structure-Aware Hand Inpainting
日本大学: 関与なし(対象大学)
- SGMT: Social Generating with Multiview-Guided Tuning In Recommender Systems
日本大学: 関与なし(対象大学)
- SGP4SR: Separated-Modality Guided User Preference Learning for Multimodal Sequential Recommendation
日本大学: 関与なし(対象大学)
- SGPFeat: Semantic and Geometric Priors for Multi-modal Image Matching
日本大学: 関与なし(対象大学)
- SGS-3D: High-Fidelity 3D Instance Segmentation via Reliable Semantic Mask Splitting and Growing
日本大学: 関与なし(対象大学)
- SGoT-R1: Social Graph of Thought Reasoning-Enhanced Multimodal Large Language Model for Harmful Meme Detection
日本大学: 関与なし(対象大学)
- SHADOW: Dynamic-Aware Credit Assignment Against Long-Horizon Tasks
日本大学: 関与なし(対象大学)
- SIAM: Towards Generalizable Articulated Object Modeling via Single Robot-Object Interaction
日本大学: 関与なし(対象大学)
- SIDE: Surrogate Conditional Data Extraction from Diffusion Models
日本大学: 関与なし(対象大学)
- SIFThinker: Spatially-Aware Image Focus for Visual Reasoning
日本大学: 関与なし(対象大学)
- SITA: A Framework for Structure-to-Instance Theorem Autoformalization
日本大学: 関与なし(対象大学)
- SLCFormer: Spectral-Local Context Transformer with Physics-Grounded Flare Synthesis for Nighttime Flare Removal
日本大学: 関与なし(対象大学)
- SLD-L2S: Hierarchical Subspace Latent Diffusion for High-Fidelity Lip to Speech Synthesis
日本大学: 関与なし(対象大学)
- SM3Det: A Unified Model for Multi-Modal Remote Sensing Object Detection
日本大学: 関与なし(対象大学)
- SMART: A Surrogate Model for Predicting Application Runtime in Dragonfly Systems
日本大学: 関与なし(対象大学)
- SMIDT: High-Performance Inference Framework for MoE Models with Dynamic Top-K Routing
日本大学: 関与なし(対象大学)
- SMoFi: Step-wise Momentum Fusion for Split Federated Learning on Heterogeneous Data
日本大学: 関与なし(対象大学)
- SNN-Driven Event-Based Flow and Rotation Estimation with SO(3) Refinement
日本大学: 関与なし(対象大学)
- SNS-Grasp: Semantic-guided Noise Scaling for Grasp Generation
日本大学: 関与なし(対象大学)
- SOAR: Semi-Supervised Open-Vocabulary Aerial Object Detection via Dual-Aware Enhanced Prior Denoising
日本大学: 関与なし(対象大学)
- SODiff:Semantic-Oriented Diffusion Model for JPEG Compression Artifacts Removal
日本大学: 関与なし(対象大学)
- SOM Directions Are Better than One: Multi-Directional Refusal Suppression in Language Models
日本大学: 関与なし(対象大学)
- SOMA: Feature Gradient Enhanced Affine-Flow Matching for SAR-Optical Registration
日本大学: 関与なし(対象大学)
- SOSControl: Enhancing Human Motion Generation Through Saliency-Aware Symbolic Orientation and Timing Control
日本大学: 関与なし(対象大学)
- SPA: Achieving Consensus in LLM Alignment via Self-Priority Optimization
日本大学: 関与なし(対象大学)
- SPAN: Benchmarking and Improving Cross-Calendar Temporal Reasoning of Large Language Models
日本大学: 関与なし(対象大学)
- SPARD: Single-step Inference with Adaptive Sampling in Residual Diffusion for Human Motion Prediction
日本大学: 関与なし(対象大学)
- SPARE: Single-Pass Annotation with Reference-Guided Evaluation for Automatic Process Supervision and Reward Modelling
日本大学: 関与なし(対象大学)
- SPEED-Q: Staged Processing with Enhanced Distillation Towards Efficient Low-Bit On-Device VLM Quantization
日本大学: 関与なし(対象大学)
- SPIRAL: Symbolic LLM Planning via Grounded and Reflective Search
日本大学: 関与なし(対象大学)
- SPJFNet: Self-Mining Prior-Guided Joint Frequency Enhancement for Ultra-Efficient Dark Image Restoration
日本大学: 関与なし(対象大学)
- SPP-SCL: Semi-Push-Pull Supervised Contrastive Learning for Image-Text Sentiment Analysis and Beyond
日本大学: 関与なし(対象大学)
- SPSC: Sparse and Scalable Multi-Modal 3D Occupancy Prediction for Autonomous Driving
日本大学: 関与なし(対象大学)
- SR-KI: Scalable and Real-Time Knowledge Integration into LLMs via Supervised Attention
日本大学: 関与なし(対象大学)
- SRACG: A Code Generation Framework with Selective Retrieval Augmentation
日本大学: 関与なし(対象大学)
- SRD: Reinforcement-Learned Semantic Perturbation for Backdoor Defense in VLMs
日本大学: 関与なし(対象大学)
- SRSplat: Feed-Forward Super-Resolution Gaussian Splatting from Sparse Multi-View Images
日本大学: 関与なし(対象大学)
- SSCL: Adversarially Guided Image Compression via Semantic and Spectral Consistency Learning
日本大学: 関与なし(対象大学)
- SSHPool: The Separated Subgraph-based Hierarchical Pooling
日本大学: 関与なし(対象大学)
- SSL-CST: Cell Segmentation for Single-Cell Spatial Transcriptome Based on Self-Supervised Learning
日本大学: 関与なし(対象大学)
- SSR-SAM: Retrieval-Style Segment Anything Model for Semi-Supervised Ultra-High-Resolution Image Segmentation
日本大学: 関与なし(対象大学)
- SSR: Semantic and Spatial Rectification for CLIP-based Weakly Supervised Segmentation
日本大学: 関与なし(対象大学)
- ST-LLM: Spatial Transcriptomics Embedding with Large Language Models
日本大学: 関与なし(対象大学)