DiffIML applies score-based generative modeling to image manipulation localization, recovering coherent masks iteratively from noise to improve generalization on unseen manipulation types.
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ResetEdit embeds a recoverable discrepancy signal during image generation in diffusion models to reconstruct an approximate original latent for high-fidelity text-guided editing.
ZODIAC enables zero-shot inference of conflict-inducing conditions in O-RAN xApps from marginal offline data alone via uncertainty-penalized compositional diffusion reasoning.
OTCA improves GRPO training for visual generation by estimating step importance in trajectories and adaptively weighting multiple reward objectives.
DFAlign uses diffusion-based denoising to generate foreground knowledge prompts that improve cross-modal alignment for detecting unseen actions in untrimmed videos, reporting state-of-the-art results on OV-TAD benchmarks.
UniEditBench unifies image and video editing evaluation with a nine-plus-eight operation taxonomy and cost-effective 4B/8B distilled MLLM evaluators that align with human judgments.
SynHAT uses a novel two-stage spatio-temporal diffusion framework with Latent Spatio-Temporal U-Net to synthesize realistic human activity traces, outperforming baselines by 52% on spatial and 33% on temporal metrics across four cities.
GeoLink uses offline 3D scene reconstruction to guide 2D feature refinement and relation distillation for improved generalization in cross-view geo-localization.
A replay method for continual face forgery detection condenses real-fake distribution discrepancies into compact maps and synthesizes compatible samples from current real faces to reduce forgetting under tight memory budgets without storing historical images.
IAD-Unify unifies industrial anomaly segmentation, region-grounded language understanding, and mask-guided generation in one framework using DINOv2 token injection into Qwen3.5, supported by the new Anomaly-56K dataset of 59,916 images.
PhysGen uses video models to learn physics for robots, outperforming baselines by up to 13.8% on Libero and matching specialized models in real-world tasks.
Authors link memorization to internal instability in diffusion models via latent norms, propose step-wise detection and mitigation achieving AUC >0.999 and 0% memorization rate on Stable Diffusion 1.4.
SENSE is a controllable diffusion model that jointly generates realistic urban satellite imagery and aligned building energy consumption and height maps from road networks and density inputs, improving downstream tasks with under 20% labeled data.
A new interests burn-down diffusion process models decaying user interests for personalized collaborative filtering and outperforms prior generative methods in the StageCF implementation.
A detector that trains a separate LoRA adapter per generator and mixes them with a learned router reports the best mean accuracy on AIGIBench and Chameleon, with weaker per-dataset results on several subsets.
SpatialFusion internalizes 3D geometric awareness into unified image generation models by pairing an MLLM with a spatial transformer that produces depth maps to constrain diffusion generation.
EAD-Net uses a diffusion model with new spatio-temporal attention, graph-based temporal reasoning, and LLM-derived semantic descriptions to generate emotionally expressive talking head videos with improved lip-sync and coherence over prior methods.
A latent denoising objective with saliency-aware corruption and contrastive distillation improves visual alignment and corruption robustness in large multimodal models.
Task-aware localization via attention cues and feature centroids from source/target streams in IIE models improves non-edit consistency while preserving instruction following.
A two-stage semi-supervised flow matching framework with random voting and conflict-free guidance fuses mosaiced hyperspectral and panchromatic images to generate superior high-resolution hyperspectral results on benchmarks.
Long-CODE isolates long-context video evaluation with a new benchmark dataset and shot-dynamics metric that correlates better with human judgments on narrative richness and global consistency than short-video metrics.
RF-CMG synthesizes high-quality mmWave and RFID signals from WiFi using a diffusion model with Modality-Guided Embedding for high-frequency details and Low-Frequency Modality Consistency to preserve physical structure.
ARGen generates high-fidelity dynamic facial expression videos using affective semantic injection and adaptive reinforcement diffusion to improve emotion recognition models facing data scarcity and long-tail distributions.
VersaVogue unifies garment generation and virtual dressing via trait-routing attention with mixture-of-experts and an automated multi-perspective preference optimization pipeline that uses DPO without human labels.
citing papers explorer
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Towards Generalized Image Manipulation Localization via Score-based Model
DiffIML applies score-based generative modeling to image manipulation localization, recovering coherent masks iteratively from noise to improve generalization on unseen manipulation types.
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ResetEdit: Precise Text-guided Editing of Generated Image via Resettable Starting Latent
ResetEdit embeds a recoverable discrepancy signal during image generation in diffusion models to reconstruct an approximate original latent for high-fidelity text-guided editing.
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ZODIAC: Zero-shot Offline Diffusion for Inferring Multi-xApps Conflicts in Open Radio Access Networks
ZODIAC enables zero-shot inference of conflict-inducing conditions in O-RAN xApps from marginal offline data alone via uncertainty-penalized compositional diffusion reasoning.
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Learning to Credit the Right Steps: Objective-aware Process Optimization for Visual Generation
OTCA improves GRPO training for visual generation by estimating step importance in trajectories and adaptively weighting multiple reward objectives.
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Denoise and Align: Diffusion-Driven Foreground Knowledge Prompting for Open-Vocabulary Temporal Action Detection
DFAlign uses diffusion-based denoising to generate foreground knowledge prompts that improve cross-modal alignment for detecting unseen actions in untrimmed videos, reporting state-of-the-art results on OV-TAD benchmarks.
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UniEditBench: A Unified and Cost-Effective Benchmark for Image and Video Editing via Distilled MLLMs
UniEditBench unifies image and video editing evaluation with a nine-plus-eight operation taxonomy and cost-effective 4B/8B distilled MLLM evaluators that align with human judgments.
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SynHAT: A Two-stage Coarse-to-Fine Diffusion Framework for Synthesizing Human Activity Traces
SynHAT uses a novel two-stage spatio-temporal diffusion framework with Latent Spatio-Temporal U-Net to synthesize realistic human activity traces, outperforming baselines by 52% on spatial and 33% on temporal metrics across four cities.
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GeoLink: A 3D-Aware Framework Towards Better Generalization in Cross-View Geo-Localization
GeoLink uses offline 3D scene reconstruction to guide 2D feature refinement and relation distillation for improved generalization in cross-view geo-localization.
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Direct Discrepancy Replay: Distribution-Discrepancy Condensation and Manifold-Consistent Replay for Continual Face Forgery Detection
A replay method for continual face forgery detection condenses real-fake distribution discrepancies into compact maps and synthesizes compatible samples from current real faces to reduce forgetting under tight memory budgets without storing historical images.
-
IAD-Unify: A Region-Grounded Unified Model for Industrial Anomaly Segmentation, Understanding, and Generation
IAD-Unify unifies industrial anomaly segmentation, region-grounded language understanding, and mask-guided generation in one framework using DINOv2 token injection into Qwen3.5, supported by the new Anomaly-56K dataset of 59,916 images.
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Learning Physics from Pretrained Video Models: A Multimodal Continuous and Sequential World Interaction Models for Robotic Manipulation
PhysGen uses video models to learn physics for robots, outperforming baselines by up to 13.8% on Libero and matching specialized models in real-world tasks.
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Broken Memories: Detecting and Mitigating Memorization in Diffusion Models with Degraded Generations
Authors link memorization to internal instability in diffusion models via latent norms, propose step-wise detection and mitigation achieving AUC >0.999 and 0% memorization rate on Stable Diffusion 1.4.
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SENSE: Satellite-based ENergy Synthesis for Sustainable Environment
SENSE is a controllable diffusion model that jointly generates realistic urban satellite imagery and aligned building energy consumption and height maps from road networks and density inputs, improving downstream tasks with under 20% labeled data.
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Interests Burn-down Diffusion Process for Personalized Collaborative Filtering
A new interests burn-down diffusion process models decaying user interests for personalized collaborative filtering and outperforms prior generative methods in the StageCF implementation.
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LEGO: LoRA-Enabled Generator-Oriented Framework for Synthetic Image Detection
A detector that trains a separate LoRA adapter per generator and mixes them with a learned router reports the best mean accuracy on AIGIBench and Chameleon, with weaker per-dataset results on several subsets.
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SpatialFusion: Endowing Unified Image Generation with Intrinsic 3D Geometric Awareness
SpatialFusion internalizes 3D geometric awareness into unified image generation models by pairing an MLLM with a spatial transformer that produces depth maps to constrain diffusion generation.
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EAD-Net: Emotion-Aware Talking Head Generation with Spatial Refinement and Temporal Coherence
EAD-Net uses a diffusion model with new spatio-temporal attention, graph-based temporal reasoning, and LLM-derived semantic descriptions to generate emotionally expressive talking head videos with improved lip-sync and coherence over prior methods.
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Latent Denoising Improves Visual Alignment in Large Multimodal Models
A latent denoising objective with saliency-aware corruption and contrastive distillation improves visual alignment and corruption robustness in large multimodal models.
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Rethinking Where to Edit: Task-Aware Localization for Instruction-Based Image Editing
Task-aware localization via attention cues and feature centroids from source/target streams in IIE models improves non-edit consistency while preserving instruction following.
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Semi-Supervised Flow Matching for Mosaiced and Panchromatic Fusion Imaging
A two-stage semi-supervised flow matching framework with random voting and conflict-free guidance fuses mosaiced hyperspectral and panchromatic images to generate superior high-resolution hyperspectral results on benchmarks.
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Long-CODE: Isolating Pure Long-Context as an Orthogonal Dimension in Video Evaluation
Long-CODE isolates long-context video evaluation with a new benchmark dataset and shot-dynamics metric that correlates better with human judgments on narrative richness and global consistency than short-video metrics.
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Cross-Modal Generation: From Commodity WiFi to High-Fidelity mmWave and RFID Sensing
RF-CMG synthesizes high-quality mmWave and RFID signals from WiFi using a diffusion model with Modality-Guided Embedding for high-frequency details and Low-Frequency Modality Consistency to preserve physical structure.
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ARGen: Affect-Reinforced Generative Augmentation towards Vision-based Dynamic Emotion Perception
ARGen generates high-fidelity dynamic facial expression videos using affective semantic injection and adaptive reinforcement diffusion to improve emotion recognition models facing data scarcity and long-tail distributions.
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VersaVogue: Visual Expert Orchestration and Preference Alignment for Unified Fashion Synthesis
VersaVogue unifies garment generation and virtual dressing via trait-routing attention with mixture-of-experts and an automated multi-perspective preference optimization pipeline that uses DPO without human labels.
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InsTraj: Instructing Diffusion Models with Travel Intentions to Generate Real-world Trajectories
InsTraj generates realistic, instruction-faithful GPS trajectories by using an LLM to parse natural-language travel intent and a multimodal diffusion transformer to produce the paths.
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User-Aware Conditional Generative Total Correlation Learning for Multi-Modal Recommendation
GTC improves multi-modal recommendation by using user-conditional diffusion-based feature filtering and total correlation optimization, achieving up to 28.3% gains in NDCG@5 on benchmarks.
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SHARP: Spectrum-aware Highly-dynamic Adaptation for Resolution Promotion in Remote Sensing Synthesis
A domain-tuned FLUX prior plus a time-varying RoPE decay schedule (SHARP) beats static positional extrapolation for high-resolution remote-sensing image synthesis.
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Enhancing Foundation VLM Robustness to Missing Modality: Scalable Diffusion for Bi-directional Feature Restoration
A diffusion model with dynamic modality gating and cross-modal mutual learning restores missing features in VLMs bi-directionally while preserving the original model's generalization.
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Generative Bid Shading in Real-Time Bidding Advertising
GBS replaces two-stage bid landscape modeling with an autoregressive generative model plus reward-aligned policy optimization to improve short- and long-term advertiser surplus in real-time bidding.
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From Snapshots to Trajectories: Learning Single-Cell Gene Expression Dynamics via Conditional Flow Matching
scFM learns bidirectional velocity fields from entropically regularized OT couplings between snapshots, with added alignment and regularization to reduce drift in long-horizon predictions of single-cell trajectories.
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MAEPose: Self-Supervised Spatiotemporal Learning for Human Pose Estimation on mmWave Video
MAEPose is a self-supervised masked autoencoder operating on mmWave spectrogram videos that learns motion representations and decodes multi-frame poses, outperforming baselines by up to 22.1% MPJPE.
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SubFlow: Sub-mode Conditioned Flow Matching for Diverse One-Step Generation
SubFlow restores full mode coverage in one-step flow matching by conditioning on sub-modes from semantic clustering, yielding higher diversity on ImageNet-256 while preserving FID.
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Sampling Parallelism for Fast and Efficient Bayesian Learning
Sampling parallelism distributes Bayesian sample evaluations across GPUs for near-perfect scaling, lower memory use, and faster convergence via per-GPU data augmentations, outperforming pure data parallelism in diversity.
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TIGFlow-GRPO: Trajectory Forecasting via Interaction-Aware Flow Matching and Reward-Guided Optimization
TIGFlow-GRPO uses a Trajectory-Interaction-Graph in conditional flow matching plus Flow-GRPO optimization to produce more accurate, socially compliant, and physically feasible trajectory forecasts on ETH/UCY and SDD datasets.
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Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects
A survey organizing AI methods for inverse PDE problems into inverse problems, inverse design, and control categories, covering applications and future challenges like physics-informed models and uncertainty quantification.