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DealMaTe: Multi-Dimensional Material Transfer via Diffusion Transformer

arXiv:2605.15681v1 Announce Type: cross Abstract: Recently, diffusion-based material transfer methods rely on image fine-tuning or complex architectures with auxiliary networks but face challenges suc

researcharxiv-cs-cv

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DebiasRAG: A Tuning-Free Path to Fair Generation in Large Language Models through Retrieval-Augmented Generation

DGX agent

arXiv:2605.16113v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved unprecedented success due to their exceptional generative capabilities. However, because they depend on kno

safetyarxiv-cs-ai

18 May 2026

Decentralized LoRA augmented transformer with multi-scale feature learning for secured eye diagnosis

model-releasesarxiv-cs-cv

arXiv:2505.06982v3 Announce Type: replace Abstract: Accurate and privacy-preserving diagnosis of ophthalmic diseases remains a critical challenge in medical imaging, particularly given the limitations

DecomPose: Disentangling Cross-Category Optimization Contention for Category-Level 6D Object Pose Estimation

arXiv:2605.15728v1 Announce Type: cross Abstract: Category-level 6D object pose estimation is typically formulated as a multi-category joint learning problem with fully shared model parameters. Howeve

Decomposed Vision-Language Alignment for Fine-Grained Open-Vocabulary Segmentation

arXiv:2605.15942v1 Announce Type: cross Abstract: Open-vocabulary segmentation models often struggle to generalize to unseen combinations of object categories and attributes, because fine-grained desc

Decouple Searching from Training: Scaling Data Mixing via Model Merging for Large Language Model Pre-training

arXiv:2602.00747v2 Announce Type: replace-cross Abstract: Determining an effective data mixture is a key factor in Large Language Model (LLM) pre-training, where models must balance general competence

Deep Double Q-learning

arXiv:2507.00275v2 Announce Type: replace-cross Abstract: Double Q-learning is a classical control algorithm that mitigates the maximization bias of Q-learning. To do so, it explicitly trains two inde

Tutorials

Deep Learning Alternatives of the Kolmogorov Superposition Theorem

arXiv:2410.01990v3 Announce Type: replace Abstract: This paper explores alternative formulations of the Kolmogorov Superposition Theorem (KST) as a foundation for neural network design. The original K

tutorialsarxiv-cs-lg

Deep Pre-Alignment for VLMs

model-releasesarxiv-cs-cv

arXiv:2605.15300v1 Announce Type: new Abstract: Most Vision Language Models (VLMs) directly map outputs from ViT encoders to the LLM via a lightweight projector. While effective, recent analysis sugge

DeepSlide: From Artifacts to Presentation Delivery

arXiv:2605.15202v1 Announce Type: new Abstract: Presentations are a primary medium for scholarly communication, yet most AI slide generators optimize the artifact (a visually plausible deck) while und

Applications

Defining Cultural Capabilities for AI Evaluation: A Taxonomy Grounded in Intercultural Communication Theory

arXiv:2605.15990v1 Announce Type: new Abstract: Tremendous efforts have been put into evaluating the inclusivity and effectiveness of AI systems across cultures. However, the cultural capabilities con

applicationsarxiv-cs-cl

Degradation-Aware Blur-Segmentation of Brain Tumor

arXiv:2605.15671v1 Announce Type: cross Abstract: Multimodal 3D MRI brain tumor segmentation is a pivotal step in radiotherapy target delineation, surgical planning and post-treatment assessment. Exis

researcharxiv-cs-cv

DeltaPrompts: Escaping the Zero-Delta Trap in Multimodal Distillation

arXiv:2605.15532v1 Announce Type: cross Abstract: Distillation enables compact Vision-Language Models (VLMs) to obtain strong reasoning capabilities, yet the prompts driving this process are typically

Density Estimation via Binless Multidimensional Integration

arXiv:2407.08094v3 Announce Type: replace-cross Abstract: We introduce the Binless Multidimensional Thermodynamic Integration (BMTI) method for nonparametric, robust, and data-efficient density estima

researcharxiv-cs-lg

Designing Datacenter Power Delivery Hierarchies for the AI Era

arXiv:2605.16255v1 Announce Type: cross Abstract: Demand for AI accelerators is rapidly increasing rack power density, with projections approaching 1MW per deployment by 2027. This poses a major chall

Designing for Robot Wranglers: A Synthesis of Literature and Practice

arXiv:2605.15892v1 Announce Type: new Abstract: Robots are increasingly present in human spaces, such as for conducting deliveries in hospitals, interacting with visitors at museums, and stocking item

researcharxiv-cs-ro

Detecting Heel Strike and toe off Events Using Kinematic Methods and LSTM Models

arXiv:2503.00794v2 Announce Type: replace Abstract: Accurate gait event detection is crucial for gait analysis, rehabilitation, and assistive technology, particularly in exoskeleton control, where pre

safetyarxiv-cs-ro

Local Ai

Detecting Localized Density Anomalies in Multivariate Data via Coin-Flip Statistics

arXiv:2503.23927v3 Announce Type: replace-cross Abstract: Detecting localized differences between two samples is a central task in scientific data analysis, required for the identification of signal e

local-aiarxiv-cs-lg

Detecting Privilege Escalation in Polyglot Microservices via Agentic Program Analysis

arXiv:2605.15569v1 Announce Type: cross Abstract: Microservices are widely adopted in modern cloud systems due to their scalability and fault tolerance. However, microservice architectures introduce s

agentsarxiv-cs-ai

DetectRL-X: Towards Reliable Multilingual and Real-World LLM-Generated Text Detection

model-releasesarxiv-cs-cl

arXiv:2605.15518v1 Announce Type: new Abstract: The effective detection and governance of Large Language Model (LLM) generated content has become increasingly critical due to the growing risk of misus

Deterministic Coreset for Lp Subspace

model-releasesarxiv-cs-lg

arXiv:2601.00361v3 Announce Type: replace-cross Abstract: We introduce the first iterative algorithm for constructing a arepsilon-coreset that guarantees deterministic ell_p subspace embedding for any

Deterministic Event-Graph Substrates as World Models for Counterfactual Reasoning

arXiv:2605.15967v1 Announce Type: new Abstract: We study event-graph substrates: a class of world models that represent agent state as an append-only log of typed RDF triples and answer counterfactual

DexJoCo: A Benchmark and Toolkit for Task-Oriented Dexterous Manipulation on MuJoCo

model-releasesarxiv-cs-ro

arXiv:2605.16257v1 Announce Type: new Abstract: Achieving human-level manipulation requires dexterous robotic hands capable of complex object interactions. Advancing such capabilities further demands

Diagonal Adaptive Non-local Observables on Quantum Neural Networks

arXiv:2605.15410v1 Announce Type: cross Abstract: Adaptive Non-local Observables (ANOs) have shown that making quantum observables dynamic can substantially enlarge the function space of Variational Q

Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models

arXiv:2605.15706v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existi

agentsarxiv-cs-lg

Differentially Private Motif-Preserving Multi-modal Hashing

arXiv:2605.15460v1 Announce Type: cross Abstract: Cross-modal hashing enables efficient retrieval by encoding images and text into compact binary codes. State-of-the-art methods rely on semantic simil

Diffusion Policy for Coordinated Control of a Nonholonomic Mobile Base and Dual Arms in Door Opening and Passing

arXiv:2605.15352v1 Announce Type: new Abstract: Opening heavy, self closing doors, especially those that require pulling remains a long standing challenge in robotics. Humans naturally employ both arm

safetyarxiv-cs-ro

DiffVAS: Diffusion-Guided Visual Active Search in Partially Observable Environments

arXiv:2605.15519v1 Announce Type: cross Abstract: Visual active search (VAS) has been introduced as a modeling framework that leverages visual cues to direct aerial (e.g., UAV-based) exploration and p

DiLA: Disentangled Latent Action World Models

arXiv:2605.15725v1 Announce Type: cross Abstract: Latent Action Models (LAMs) enable the learning of world models from unlabeled video by inferring abstract actions between consecutive frames. However

DimMem: Dimensional Structuring for Efficient Long-Term Agent Memory

model-releasesarxiv-cs-cl

arXiv:2605.15759v1 Announce Type: new Abstract: Large language model (LLM) agents require long-term memory to leverage information from past interactions. However, existing memory systems often face a

DIPA: Distilled Preconditioned Algorithms for Solving Imaging Inverse Problems

arXiv:2605.15456v1 Announce Type: cross Abstract: Solving imaging inverse problems has usually been addressed by designing proper prior models of the underlying signal. However, minimizing the data fi

researcharxiv-cs-cv

DiscoExplorer: An Open Interface for the Study of Multilingual Discourse Relations

arXiv:2605.15304v1 Announce Type: new Abstract: The relations connecting propositions in discourse such as cause (A because B) or concession (A although B) are a subject of intense interest in Computa

researcharxiv-cs-cl

Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space

arXiv:2605.15368v1 Announce Type: new Abstract: Group-convolutional neural networks (GCNNs) are among the most important methods for introducing symmetry as an inductive bias in deep learning: In each

safetyarxiv-cs-cv

Tutorials

DiscussLLM: Teaching Large Language Models When to Speak

arXiv:2508.18167v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in understanding and generating human-like text, yet they largely operate as

tutorialsarxiv-cs-cl

Do Biological Structural Guarantees Earn Their Complexity?

arXiv:2605.15225v1 Announce Type: cross Abstract: Biologically-inspired AI agent frameworks claim reliability benefits through structural guarantees adapted from gene regulatory networks, immune syste

agentsarxiv-cs-ai

Do Chinese models speak Chinese languages?

arXiv:2504.00289v3 Announce Type: replace-cross Abstract: The release of top-performing open-weight LLMs has cemented China's role as a leading force in AI development. Do these models support languag

Do Less, Achieve More: Do We Need Every-Step Optimization for RL Fine-tuning of Diffusion Models?

arXiv:2605.15855v1 Announce Type: new Abstract: Despite strong image-generation performance, diffusion models' reconstruction objectives limit alignment with human preferences. RL enables such alignme

safetyarxiv-cs-cv

Applications

Does Theory of Mind Improvement Really Benefit Human-AI Interactions? Empirical Findings from Interactive Evaluations

arXiv:2605.15205v1 Announce Type: new Abstract: Improving the Theory of Mind (ToM) capability of Large Language Models (LLMs) is crucial for effective social interactions between these AI models and h

applicationsarxiv-cs-ai

Applications

Domain-Independent Game Abstraction using Word Embedding Techniques

arXiv:2605.15543v1 Announce Type: cross Abstract: Many games of interest in the real world are often intractably large, thereby necessitating the use of game abstraction to shrink them in size, typica

applicationsarxiv-cs-ai

Local Ai

Don't Stop Me Yet: Sampling Loss Minima via Dissipative Riemannian Mechanics

arXiv:2605.15459v1 Announce Type: new Abstract: The minima of modern neural network loss functions are typically not isolated, rather they form connected components of reparameterization invariant sol

local-aiarxiv-cs-lg

DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research

arXiv:2511.19399v3 Announce Type: replace-cross Abstract: Deep research agents perform multi-step research to produce long-form, well-attributed answers. However, most open deep research agents are tr

Drawback of Enforcing Equivariance and its Compensation via the Lens of Expressive Power

arXiv:2512.09673v3 Announce Type: replace-cross Abstract: Equivariant neural networks encode the intrinsic symmetry of data as an inductive bias, which has achieved impressive performance in wide doma

Local Ai

DreamSR: Towards Ultra-High-Resolution Image Super-Resolution via a Receptive-Field Enhanced Diffusion Transformer

arXiv:2605.15682v1 Announce Type: new Abstract: Large-scale pre-trained diffusion models have been extensively adopted for real-world image Super-Resolution because of their powerful generative priors

local-aiarxiv-cs-cv

Driving Through the Network: Performance and Workload Under Latency and Video Impairment

arXiv:2605.15952v1 Announce Type: cross Abstract: Teleoperation promises to extend the operational envelope of automated vehicles, yet it critically depends on network latency and video quality. We re

safetyarxiv-cs-ro

DRS-GUI: Dynamic Region Search for Training-Free GUI Grounding

arXiv:2605.15542v1 Announce Type: new Abstract: GUI agents powered by Multimodal Large Language Models (MLLMs) have demonstrated impressive capability in understanding and executing user instructions.

DrugSAGE:Self-evolving Agent Experience for Efficient State-of-the-Art Drug Discovery

arXiv:2605.15461v1 Announce Type: cross Abstract: Building state-of-the-art (SOTA) predictive models for drug discovery requires expensive search over tools, architectures, and training strategies. Cu

agentsarxiv-cs-ai

DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts

arXiv:2605.15422v1 Announce Type: new Abstract: Modern RL post-training methods such as GRPO and DAPO train on N response sequences of R tokens sampled from a shared prompt of P tokens, but standard F

safetyarxiv-cs-lg

DualReg: Dual-Space Filtering and Reinforcement for Rigid Registration

arXiv:2508.17034v2 Announce Type: cross Abstract: Noisy, partially overlapping data and the need for real-time processing pose major challenges for rigid registration. Considering that feature-based m

safetyarxiv-cs-cv