arXiv Machine Learning
Jul 16
Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes
arXiv:2607. 13188v1 Announce Type: new Abstract: Human cognition does not separate understanding and generation.
Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes
Human cognition does not separate understanding and generation. A teacher at a whiteboard speaks and draws $\textit{together}$, each modality reshapes the other.
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Hugging Face Trending Papers
Jun 17
Visual-OPSD: Cross-Modal On-Policy Self-Distillation for Efficient Unified Multimodal Reasoning
Unified multimodal models (UMMs) interleave generated ''visual thoughts'' (VTs) with text reasoning to improve spatial tasks. This incurs roughly an order-of-magnitude inference cost from multi-step diffusion.
arXiv AI
22h ago
Where a New Concept Must Enter: Entry Point Gates Cross-Task Usability in Unified Multimodal Models
arXiv:2608. 17564v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) are motivated by the hope that understanding and generation reinforce each other but controlled ablations repeatedly find that adding a generation objective leaves understanding flat.
arXiv AI
Jul 1
Surprise as a Signal for Plasticity and Metacognition
arXiv:2606. 31495v1 Announce Type: new Abstract: We study a single idea across two settings: that a prediction-error signal, computed by a small predictor over the latent space of a frozen encoder, can serve both as a gate on plasticity and as a substrate for metacognition.
arXiv Machine Learning
Jul 22
Stochastic Meta-Unlearning: Bridging Language Backbone and Multimodal Unlearning
arXiv:2607. 18615v1 Announce Type: cross Abstract: Machine unlearning for vision-language models (VLMs) remains underexplored.
Hugging Face Trending Papers
Jul 21
Stochastic Meta-Unlearning: Bridging Language Backbone and Multimodal Unlearning
Machine unlearning for vision-language models (VLMs) remains underexplored. Unlike language models, VLMs combine a language backbone with visual components, which makes unlearning more complex.
arXiv AI
Jun 26
Reconstruction Alignment Improves Unified Multimodal Models
arXiv:2509. 07295v4 Announce Type: replace-cross Abstract: Unified multimodal models (UMMs) unify visual understanding and generation within a single architecture.
arXiv Machine Learning
Jul 31
Latent-Kernel Discrete Flow Maps for Few-Step Generation
arXiv:2607. 27529v1 Announce Type: new Abstract: Discrete diffusion and flow-matching models denoise a sequence over many steps, but to keep each step cheap, they factorize the transition across positions and decide every token independently.
Hugging Face Trending Papers
Aug 10
Perception Before Supervision: Self-Contained Visual Distillation from Counterfactual Blind Spots
Self-improvement for multimodal large language models (MLLMs) is typically driven by reward-based methods that provide only coarse scalar feedback. Distillation offers a richer alternative through dense token-level supervision, but in the visual domain it usually depends on privileged context constructed using external annotations and tools, or stronger models.
arXiv AI
Aug 5
Balancing Efficiency and Efficacy: Training-Free Attention-Guided Switching Between Explicit and Latent Thoughts for MLLMs
arXiv:2608. 03450v1 Announce Type: cross Abstract: Reasoning in Multimodal Large Language Models (MLLMs) requires both fine-grained visual perception and rigorous logical deduction.
arXiv Machine Learning
Jun 11
Visual-Redundancy-Controlled Parallel Decoding for Diffusion-Based Multimodal Large Language Models
arXiv:2605. 25820v2 Announce Type: replace Abstract: Diffusion-based multimodal large language models (dMLLMs) decode by iteratively predicting tokens at multiple masked positions in parallel.
arXiv AI
Jul 10
Cognitive-structured Multimodal Agent for Multimodal Understanding, Generation, and Editing
arXiv:2607. 08497v1 Announce Type: cross Abstract: Recent unified multimodal models show a single architecture can jointly perform vision/language understanding and image generation/editing.