All entries

DeepSlide: From Artifacts to Presentation Delivery

model-releasesarxiv-cs-ai

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

DGX agent

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

18 May 2026

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

Dell + Nvidia

model-releasesclem-delangue--x

Dell + Nvidia Media 'We give you model choice, without infrastructure chaos' — @MichaelDell, live from #DellTechWorld 🎤 Kimi K2.6, DeepSeek V4 Pro, GLM 5.1, MiniMax M2.7 & DeepSeek V4 Flash are now on

Dell targets enterprise AI execution gap with local agentic AI systems and integrated AI infrastructure

Dell Technologies Inc. today is kicking off its Dell Technologies World conference by expanding its artificial intelligence portfolio with enhancements aimed at helping enterprises move AI projects fr

local-aisiliconangle

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

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

model-releasesarxiv-cs-ai

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

model-releasesarxiv-cs-ai

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

Industry

Did Artemis II break through? Registrations at Space Camp double afterward.

Artemis II sent four astronauts on a lunar flyby in 2026, becoming the first crewed flight beyond low Earth orbit since the Apollo program. The successful mission appears to have generated significant

industryars-technica

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

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

researcharxiv-cs-ai

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

Industry

Distributed training is hard. We adopted DTensor at Runway to prevent silent gradient bugs and it delivered. But we traded performance for c…

industrycristobal-valenzuela--x

Distributed training is hard. We adopted DTensor at Runway to prevent silent gradient bugs and it delivered. But we traded performance for correctness, hitting dispatch overhead, recompilation storms,

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

researcharxiv-cs-ai

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

Do we have to look at a billion of these Yann LeCun saying things Gary Marcus said all along videos, @haider1, or might you run some where I…

Do we have to look at a billion of these Yann LeCun saying things Gary Marcus said all along videos, @haider1, or might you run some where I said the same things? He might have more press than I do bu

agentsgary-marcus--x

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

Domain-specific AI is rewriting the rules of workforce management

The rise of agentic AI is reshaping what enterprise partnerships must deliver — and domain-specific AI is proving to be the real differentiator between systems that advise and systems that act. As AI

agentssiliconangle

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

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

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.

researcharxiv-cs-ai

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

Dust, which helps enterprises design and deploy specialized AI agents that work alongside humans, raised a $40M Series B led by Abstract and Sequoia (Chris Metinko/Axios)

Chris Metinko / Axios: Dust, which helps enterprises design and deploy specialized AI agents that work alongside humans, raised a 40M Series B led by Abstract and Sequoia — Dust, a human-agent collabo

agentstechmeme

Dynamic Chunking for Diffusion Language Models

model-releasesarxiv-cs-cl

arXiv:2605.15676v1 Announce Type: new Abstract: Block discrete diffusion language models factorize a sequence autoregressively over fixed-size positional blocks, decoupling within-block parallel denoi

Dynamic Plasma Shape Control with Arbitrary Sensor Subsets

arXiv:2605.15935v1 Announce Type: new Abstract: Plasma shape control in tokamaks requires a real-time controller that tracks dynamically changing shape targets while tolerating diagnostic failures. Cl