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Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning9h◆Subagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks9h◆Distribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts9h◆In RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning9h◆FrontierChallenge: Evaluating Scientific Workflow Completion9h◆IBIB: A Protocol for Measuring Enterprise AI Systems by Serving Route, Not Model Identifier9h◆AgenticGen: Reward-Guided Agentic Video Generation for Advertising9h◆Strangers to Themselves: What Language Models Say About Themselves Is Generic9h◆Omni Interaction Agent Technical Report9h◆CoGReV: A Confidence-Gated Post-Hoc Non-Monotonic Belief Revision Framework for Phishing Website Classification9h◆Bit-Flip Attacks on Vision-Language-Action Models: Action-Decoding Architecture Shapes the Vulnerability9h◆Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization9h◆RiLM: Parameter-Efficient Language Modeling via Geodesic Decoding9h◆Tracing Computation Density in LLMs9h◆Cultural Binding Heads in Language Models9h◆Direct Diversity Optimization for Diverse Successful Trajectories in Preference Post-Training9h◆Left-Branching Transformers Excel at Right-Branching Languages: Data Shapes Word Order Preferences in Language Models9h◆Palmyra x6 Technical Report: An Agentic, Tool-Use Model Post-Trained via Anchored Supervised Fine-Tuning9h◆'Ghaib in Translation' aka Unseen Harm: Measuring Cross-Script Safety Inconsistency with 'Missed-in-Urdu' Scores in LLM Hate Speech Detection9h◆DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation9h◆Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning9h◆Subagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks9h◆Distribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts9h◆In RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning9h◆FrontierChallenge: Evaluating Scientific Workflow Completion9h◆IBIB: A Protocol for Measuring Enterprise AI Systems by Serving Route, Not Model Identifier9h◆AgenticGen: Reward-Guided Agentic Video Generation for Advertising9h◆Strangers to Themselves: What Language Models Say About Themselves Is Generic9h◆Omni Interaction Agent Technical Report9h◆CoGReV: A Confidence-Gated Post-Hoc Non-Monotonic Belief Revision Framework for Phishing Website Classification9h◆Bit-Flip Attacks on Vision-Language-Action Models: Action-Decoding Architecture Shapes the Vulnerability9h◆Can Foundation Models Moderate Online Content? Evaluating Instruction- vs. Example-Driven Policy Operationalization9h◆RiLM: Parameter-Efficient Language Modeling via Geodesic Decoding9h◆Tracing Computation Density in LLMs9h◆Cultural Binding Heads in Language Models9h◆Direct Diversity Optimization for Diverse Successful Trajectories in Preference Post-Training9h◆Left-Branching Transformers Excel at Right-Branching Languages: Data Shapes Word Order Preferences in Language Models9h◆Palmyra x6 Technical Report: An Agentic, Tool-Use Model Post-Trained via Anchored Supervised Fine-Tuning9h◆'Ghaib in Translation' aka Unseen Harm: Measuring Cross-Script Safety Inconsistency with 'Missed-in-Urdu' Scores in LLM Hate Speech Detection9h◆DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation9h◆
Tag

#diffusion-models

12 articles tagged #diffusion-models

arxivJul 30bullish

Lantern: Conflict-Aware Gradient Blending for Physics-Guided Diffusion Models in Calorimeter Simulation

arXiv:2607.25060v1 Announce Type: cross Abstract: Monte Carlo simulation of calorimeter showers is a principal bottleneck for the High-Luminosity LHC, and diffusion models have emerged as fast, high-fidelity surrogates. Their denoising objective is purely statistical, however: a model can minimize i

LA1 model#machine-learning#diffusion-models#physics-informedRead on arxiv →
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arxivJul 30bullish

ScaleResfusion: Residual Rectified Flow based on Residual Vector Field

arXiv:2607.25275v1 Announce Type: cross Abstract: Real-world Image Restoration (Real-IR) aims to recover high-quality (HQ) images from complex and unknown degradations. Although recent diffusion-based methods have substantially improved perceptual quality, their current designs leave two key challen

SCRE2 models#image-restoration#diffusion-models#pre-trainingRead on arxiv →
arxivJul 30bullish

Amortized Moment Matching for Visual Generation

arXiv:2607.26860v1 Announce Type: new Abstract: We propose amortized moment matching, utilizing neural networks to learn data moments as distributional training signals. By casting diffusion denoisers through polynomial projections, we establish a general framework for moment amortization, revealing

#machine-learning#generative-models#neural-networksRead on arxiv →
arxivJun 12bullish

From Uniform to Learned Graph Priors: Diffusion for Structure Discovery

arXiv:2606.11831v1 Announce Type: new Abstract: Neural relational inference (NRI) methods discover interaction graphs from trajectories through variational reasoning on discrete potential edges. However, these methods typically rely on oversimplified, factorized graph priors. Such priors, typically

DI1 model#neural-relational-inference#graph-priors#diffusion-modelsRead on arxiv →
arxivJun 6bullish

Edit-R2: Context-Aware Reinforcement Learning for Multi-Turn Image Editing

arXiv:2606.05950v1 Announce Type: new Abstract: Text-guided image editing has advanced rapidly with diffusion models and unified multimodal foundation models. However, most existing methods remain confined to single-turn settings, overlooking the more realistic scenario of multi-turn in-context edit

ED1 model#image-editing#diffusion-models#multimodal-modelsRead on arxiv →
arxivMay 29

Finding DoRI: Discovery of Retained Images in Diffusion Models

arXiv:2507.16880v3 Announce Type: replace-cross Abstract: Text-to-image diffusion models (DMs) have achieved remarkable success in image generation. However, concerns about data privacy and intellectual property remain due to their potential to inadvertently memorize and replicate training data. Rec

#mitigation#memorization#diffusion-modelsRead on arxiv →
arxivMay 28

Compositional Generalization in Autoregressive Models via Logit Composition

arXiv:2605.28304v1 Announce Type: new Abstract: Composing autoregressive models remains a core challenge in understanding how large language models can combine behaviors or skills learned across tasks. We introduce a new and principled composition strategy for autoregressive systems, inspired by com

#machine-learning#autoregressive-models#diffusion-modelsRead on arxiv →
arxivMay 7bullish

Joint Relational Database Generation via Graph-Conditional Diffusion Models

arXiv:2505.16527v3 Announce Type: replace Abstract: Building generative models for relational databases (RDBs) is important for many applications, such as privacy-preserving data release and augmenting real datasets. However, most prior works either focus on single-table generation or adapt single-t

GR1 model#relational-databases#generative-models#graph-neural-networksRead on arxiv →
arxivApr 30bullish

DiffAnon: Diffusion-based Prosody Control for Voice Anonymization

arXiv:2604.26281v1 Announce Type: cross Abstract: To preserve or not to preserve prosody is a central question in voice anonymization. Prosody conveys meaning and affect, yet is tightly coupled with speaker identity. Existing methods either discard prosody for privacy or lack a principled mechanism

DI1 model#voice-anonymization#prosody-preservation#diffusion-modelsRead on arxiv →
arxivApr 24

Reasoning on the Manifold: Bidirectional Consistency for Self-Verification in Diffusion Language Models

arXiv:2604.16565v2 Announce Type: replace-cross Abstract: While Diffusion Large Language Models (dLLMs) offer structural advantages for global planning, efficiently verifying that they arrive at correct answers via valid reasoning traces remains a critical challenge. In this work, we propose a geome

#machine-learning#artificial-intelligence#researchRead on arxiv →
arxivApr 24bullish

Video-Robin: Autoregressive Diffusion Planning for Intent-Grounded Video-to-Music Generation

arXiv:2604.17656v2 Announce Type: replace-cross Abstract: Video-to-music (V2M) is the fundamental task of creating background music for an input video. Recent V2M models achieve audiovisual alignment by typically relying on visual conditioning alone and provide limited semantic and stylistic control

VI1 model#music-generation#video-processing#diffusion-modelsRead on arxiv →
arxivApr 16

Guided Transfer Learning for Discrete Diffusion Models

arXiv:2512.10877v4 Announce Type: replace Abstract: Discrete diffusion models (DMs) have achieved strong performance in language and other discrete domains, offering a compelling alternative to autoregressive modeling. Yet this performance typically depends on large training datasets, challenging th

#diffusion-models#transfer-learning#language-modelingRead on arxiv →