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Diffusion Models, Denoiser Architecture and Creativity

arXiv:2605.16415v1 Announce Type: new Abstract: The creativity of diffusion models refers to their ability to generate highly realistic images that are different from their training data. Creativity i

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DiPRL: Learning Discrete Programmatic Policies via Architecture Entropy Regularization

DGX agent

arXiv:2605.18508v1 Announce Type: cross Abstract: Programmatic reinforcement learning (PRL) offers an interpretable alternative to deep reinforcement learning by representing policies as human-readabl

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19 May 2026

DiRotQ: Rotation-Aware Quantization for 4-bit Diffusion Transformers

arXiv:2605.16732v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve state-of-the-art image generation quality but incur substantial memory and computational costs at inference. While

DISA: Offline Importance Sampling for Distribution-Matching LLM-RL

arXiv:2605.17295v1 Announce Type: cross Abstract: Modern reasoning agents are increasingly evaluated on their ability to generate multiple valid solution paths, plans, or tool-use traces for a given i

Distilling Tabular Foundation Models for Structured Health Data

arXiv:2605.18702v1 Announce Type: cross Abstract: Tabular foundation models (TFMs) achieve strong performance on health datasets, but their inference cost and infrastructure requirements limit practic

Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning

arXiv:2605.16776v1 Announce Type: cross Abstract: Mitigating sensitive and harmful outputs is fundamental to ensuring safe deployment of LLMs. Existing approaches typically follow two paradigms: Knowl

Distributed 3D Leader-Follower Formation Control with Field-of-View Safety via Control Barrier Functions

arXiv:2605.17533v1 Announce Type: cross Abstract: This letter proposes a distributed 3D leader-follower formation (3D-LFF) control framework for multi-UAV systems that achieves formation tracking whil

Do LLM Agents Mirror Socio-Cognitive Effects in Power-Asymmetric Conversations?

arXiv:2605.17694v1 Announce Type: new Abstract: Power differences shape human communication through well documented socio cognitive effects, including language coordination, pronoun usage, authority b

Domain Transfer Becomes Identifiable via a Single Alignment

arXiv:2605.17918v1 Announce Type: cross Abstract: Domain transfer (DT) maps source to target distributions and supports tasks such as unsupervised image-to-image translation, single-cell analysis, and

DreamEdit3D: Personalization of Multi-View Diffusion Models for 3D Editing

arXiv:2605.16990v1 Announce Type: new Abstract: While 2D diffusion models have achieved remarkable success in identity-preserving personalization, extending this capability to 3D assets remains a sign

Dual-Space Knowledge Distillation with Key-Query Matching for Large Language Models with Vocabulary Mismatch

arXiv:2603.22056v2 Announce Type: replace Abstract: Large language models (LLMs) achieve state-of-the-art (SOTA) performance across language tasks, but are costly to deploy due to their size and resou

DuIVRS-2: An LLM-based Interactive Voice Response System for Large-scale POI Attribute Acquisition

arXiv:2605.17900v1 Announce Type: new Abstract: Accurate Point of Interest (POI) attribute acquisition is essential for location-based services, yet traditional modular Interactive Voice Response (IVR

DyDiff: Long-Horizon Rollout via Dynamics Diffusion for Offline Reinforcement Learning

arXiv:2405.19189v3 Announce Type: replace Abstract: With the great success of diffusion models (DMs) in generating realistic synthetic vision data, many researchers have investigated their potential i

DyGRO-VLA: Cross-Task Scaling of Vision-Language-Action Models via Dynamic Grouped Residual Optimization

arXiv:2605.17486v1 Announce Type: cross Abstract: Recent progress in Reinforcement Learning (RL) provides a principled approach to optimizing Vision-Language-Action (VLA) models, facilitating a shift

ECG-WM: A Physiology-Informed ECG World Model for Clinical Intervention Simulation

arXiv:2605.17580v1 Announce Type: new Abstract: Electrocardiogram (ECG)-based models have achieved strong performance in diagnostic tasks, yet they remain limited in modeling how cardiac dynamics evol

Echoes in Filter Bubble: Diagnosing and Curing Popularity Bias in Generative Recommenders

arXiv:2605.16825v1 Announce Type: cross Abstract: Recently, Generative Recommenders (GRs), characterized by a unified end-to-end framework, have exhibited astonishing potential in transforming the rec

Edit-GRPO: A Locality-Preserving Policy Optimization Framework for Image Editing

arXiv:2605.16951v1 Announce Type: new Abstract: A fundamental challenge in image editing lies in preserving spatial locality: edits should improve targeted content without inadvertently altering surro

Efficient Bilevel Optimization for Meta Label Correction in Noisy Label Learning

arXiv:2605.17833v1 Announce Type: cross Abstract: Training a deep neural network with noisy labels could reduce data annotation cost but may introduce noise into the learned model. In meta label corre

Enabling Off-Policy Imitation Learning with Deep Actor Critic Stabilization

arXiv:2511.07288v2 Announce Type: replace-cross Abstract: Learning complex policies with Reinforcement Learning (RL) is often hindered by instability and slow convergence, a problem exacerbated by the

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos

arXiv:2605.18233v1 Announce Type: new Abstract: Without incurring significant computational overhead, train-free long video generation aims to enable foundation video generation models to produce long

Entropy-Gradient Inversion: Moving Toward Internal Mechanism of Large Reasoning Models

arXiv:2605.17770v1 Announce Type: new Abstract: The advancement of Large Reasoning Models (LRMs) has catalyzed a paradigm shift from reactive ``fast thinking'' text generation to systematic, step-by-s

Equilibrium Selection in Multi-Agent Policy Gradients via Opponent-Aware Basin Entry

arXiv:2605.18078v1 Announce Type: new Abstract: Multi-agent policy-gradient methods have been shown to converge locally near stable Nash equilibria. Local convergence, however, does not determine whic

Estimating Item Difficulty with Large Language Models as Experts

arXiv:2605.18562v1 Announce Type: cross Abstract: Accurate estimates of item difficulty are essential for valid assessment and effective adaptive learning. However, for newly created tasks, response d

Ethical Hyper-Velocity (EHV): A Provably Deterministic Governance-Aware JIT Compiler Architecture for Agentic Systems

arXiv:2605.17909v1 Announce Type: new Abstract: As autonomous agentic systems scale across regulated critical infrastructures, the lack of mechanistic, hardware-rooted enforcement for high-frequency p

Evaluating AI Alignment in LLMs: Output Analysis of Value Priorities Across 75 Models with Human Benchmarking

arXiv:2506.12617v4 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in human-AI interaction research and practice, yet existing capability and safety benchmarks reve

Event-Grounded Sparse Autoencoders for Vision-Language-Action Policies

arXiv:2605.17204v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies translate language and visual inputs into robot actions, where their hidden representations directly shape close

Experiment-as-Code Labs: A Declarative Stack for AI-Driven Scientific Discovery

arXiv:2605.04375v2 Announce Type: replace-cross Abstract: To unleash the full potential of AI for Science, we must untether the agents from a purely digital environment. The agent's ability to control

Face inpainting with Identity Preserving Latent Diffusion Models

arXiv:2605.16696v1 Announce Type: new Abstract: Face inpainting techniques recover missing or occluded facial regions in a visually realistic manner, but preserving the identity in the final output re

Factored Causal Representation Learning for Robust Reward Modeling in RLHF

arXiv:2601.21350v2 Announce Type: replace Abstract: A reliable reward model is essential for aligning large language models with human preferences through reinforcement learning from human feedback. H

Factual Inconsistencies in Multilingual Wikipedia Tables

arXiv:2507.18406v2 Announce Type: replace Abstract: Wikipedia serves as a globally accessible knowledge source with content in over 300 languages. Despite covering the same topics, the different versi

Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent

arXiv:2605.17767v1 Announce Type: cross Abstract: We study feature learning in two-layer neural networks within the linear-width regime, where the number of hidden neurons, sample size, and input dime

FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction

arXiv:2605.18055v1 Announce Type: cross Abstract: Predicting spatial gene expression from routine H&E enables large-scale molecular profiling, yet current models treat this as isolated pointwise tasks

Flow Matching with Optimized Subclass Priors for Medical Image Augmentation

arXiv:2605.16469v1 Announce Type: cross Abstract: Rare diseases dominate the diagnostic challenge in medical imaging yet are severely underrepresented in clinical datasets, causing classifiers to fail

For a long time, academic researchers being at the cutting edge of new technologies has been a great social equilibrium. Neutral, unbiased t…

For a long time, academic researchers being at the cutting edge of new technologies has been a great social equilibrium. Neutral, unbiased technologists have been the people to spread new ideas to the

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Forget Many, Forget Right: Scalable and Precise Concept Unlearning in Diffusion Models

arXiv:2601.06162v4 Announce Type: replace-cross Abstract: Text-to-image diffusion models have achieved remarkable progress, yet their use raises copyright and misuse concerns, prompting research into

Forgetting is Competition: Rethinking Unlearning as Representation Interference in Diffusion Models

arXiv:2603.00975v2 Announce Type: replace-cross Abstract: Deployed text-to-image diffusion models increasingly require post-hoc concept unlearning for copyright claims, artist opt-outs, safety updates

From a Single Demonstration to a General Policy for Contact-Rich Manipulation

arXiv:2605.17601v1 Announce Type: new Abstract: We present a Learning from Demonstration (LfD) framework that achieves one-shot generalization in multi-stage, contact-rich manipulation tasks. Central

From Demographics to Survey Anchors: Evaluating LLM Agents for Modeling Retirement Attitudes

arXiv:2605.16303v1 Announce Type: cross Abstract: Large language models (LLM) agents may offer tools to predict human responses to surveys. A common technique for defining these agents uses only demog

From Reactive to Proactive: A Multi-Regulatory Empirical Analysis of 480 AI Incidents and a Data-Driven Governance Compliance Framework

arXiv:2605.16281v1 Announce Type: cross Abstract: Artificial intelligence systems are increasingly deployed in high-stakes domains, yet it remains unclear whether existing governance frameworks ensure

FUNCanon: Learning Pose-Aware Action Primitives via Functional Object Canonicalization for Generalizable Robotic Manipulation

arXiv:2509.19102v2 Announce Type: replace-cross Abstract: General-purpose robotic skills from end-to-end demonstrations often leads to task-specific policies that fail to generalize beyond the trainin

FUSE: A Framework for Unified State Estimation in Robotic SLAM Systems

arXiv:2605.18047v1 Announce Type: new Abstract: Tightly coupled SLAM formulations under mixed-rate sensing often bind temporal processing, local geometric association, estimator formulation, and map-u

GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation

arXiv:2512.23180v3 Announce Type: replace Abstract: Driving World Models (DWMs) have been developing rapidly with the advances of generative models. However, existing DWMs lack 3D scene understanding

Generating Physically Consistent Molecules with Energy-Based Models

arXiv:2605.18381v1 Announce Type: new Abstract: Molecules in equilibrium follow a Boltzmann distribution, making the underlying energy landscape a physically grounded modeling objective. However, such

Generating Realistic Safety-Critical Scenarios for Vehicle-Pedestrian Interactions

arXiv:2605.17229v1 Announce Type: new Abstract: Automated driving system deployment requires rigorous validation across safety-critical vehicle-pedestrian interactions, yet real-world datasets rarely

Generation Navigator: A State-Aware Agentic Framework for Image Generation

arXiv:2605.17969v1 Announce Type: new Abstract: Despite rapid advances in text-to-image generation, faithfully realizing user intent remains challenging, often requiring manual multi-turn trial and er

Geometry-aware 4D Video Generation for Robot Manipulation

arXiv:2507.01099v4 Announce Type: replace-cross Abstract: Understanding and predicting dynamics of the physical world can enhance a robot's ability to plan and interact effectively in complex environm

GeoWorld-VLM: Geometry from World Models for Vision-Language Models

arXiv:2605.16713v1 Announce Type: cross Abstract: Modern Vision-Language Models (VLMs) achieve strong semantic recognition, yet remain brittle on elementary spatial relations such as left of, on, behi

Goal-Conditioned Supervised Learning for LLM Fine-Tuning

arXiv:2605.16345v1 Announce Type: cross Abstract: Large language models often require fine-tuning to better align their behavior with user intent at deployment. Existing approaches are commonly divide