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DFKI-MLT at SemEval-2026 TASK 7: Steering Multilingual Models Towards Cultural Knowledge

model-releasesarxiv-cs-cl

arXiv:2605.23069v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used across diverse linguistic and cultural contexts, yet their cultural knowledge remains uneven across r

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Hardware

DFSAttn: Dynamic Fine-grained Sparse Attention for Efficient Video Generation

DGX agent

arXiv:2605.23445v1 Announce Type: new Abstract: Diffusion transformers have achieved remarkable success in high-quality video generation, yet their reliance on spatiotemporal 3D full attention incurs

hardwarearxiv-cs-cv

25 May 2026

Local Ai

Did Ollama Cloud silently nerf the usage limits?

This discussion likely addresses concerns about whether Ollama has quietly reduced its cloud usage limits, as the platform has revised limits twice since launch. Ollama Cloud usage is governed by sess

local-air-ollama

Differences in Typological Alignment in Language Models' Treatment of Differential Argument Marking

arXiv:2602.17653v2 Announce Type: replace Abstract: Recent work has shown that language models (LMs) trained on synthetic corpora can exhibit typological preferences that resemble cross-linguistic reg

safetyarxiv-cs-cl

Diffusion and Flow Matching Models for Tabular Data: A Survey

arXiv:2502.17119v2 Announce Type: replace-cross Abstract: Deep generative models have made rapid progress in image, text, audio, and video generation, and are increasingly being applied to structured

Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation

model-releasesarxiv-cs-lg

arXiv:2605.22950v1 Announce Type: cross Abstract: Score matching is an alternative to maximum likelihood estimation when the normalizing constant is unknown or too costly to evaluate. However, vanilla

Diffusion Domain Expansion: Learning to Coordinate Pre-trained Diffusion Models

arXiv:2605.23275v1 Announce Type: new Abstract: In this paper, we propose Diffusion Domain Expansion (DDE), a method that efficiently extends pre-trained diffusion models to generate larger objects an

DiLaDiff: Distilled Latent-Augmented Diffusion for Language Modeling

arXiv:2605.23605v1 Announce Type: cross Abstract: Diffusion language models intrinsically fail to capture correlations between decoded tokens, which leads to a harsh trade-off between sampling quality

Direct Dynamic Retargeting for Humanoid Imitation Learning from Videos

arXiv:2605.23762v1 Announce Type: new Abstract: Imitation Learning from monocular video demonstrations provides a scalable approach for teaching complex skills to humanoid robots. However, translating

safetyarxiv-cs-ro

Dirichlet-Based Monte Carlo Dropout for Uncertainty Estimation in Neural Networks

arXiv:2605.23635v1 Announce Type: cross Abstract: Traditional neural networks provide deterministic predictions without inherent uncertainty estimates. While Bayesian Neural Networks (BNNs) offer a pr

Discontinuous Galerkin Neural Operator for Pathology Defocus Deblurring

model-releasesarxiv-cs-cv

arXiv:2605.23282v1 Announce Type: cross Abstract: Defocus deblurring in pathological microscopy remains challenging due to the spatially varying and locally discontinuous nature of optical blur induce

Disentangling Interaction and Bias Effects in Opinion Dynamics of Large Language Models

arXiv:2509.06858v2 Announce Type: replace-cross Abstract: Large Language Models are increasingly used to simulate human opinion dynamics, yet the effect of genuine interaction is often obscured by sys

Dithering Defense: Adversarial Robustness of Vision Foundation Models via Multi-Level Floyd-Steinberg Dithering

arXiv:2605.23065v1 Announce Type: cross Abstract: Vision foundation models are widely used as frozen backbones across many downstream tasks, making them a single point of failure under adversarial att

Do Language Models Know What Not to Say? Causal Evidence for Statistical Preemption in LLMs

arXiv:2605.23039v1 Announce Type: cross Abstract: How do learners acquire knowledge of what is unacceptable without negative evidence? Construction Grammar proposes statistical preemption: exposure to

Do Synthetic Brain MRIs Reliably Improve Tumour Classification? A StyleGAN2-ADA Class-Plane Augmentation Study on BRISC 2025

arXiv:2605.23094v1 Announce Type: cross Abstract: Generative augmentation is often proposed as a remedy for small medical-image datasets, but synthetic images are only useful when they improve downstr

Tools

Do you have your coding agents include automated tests for the code that they write?

Simon Willison discusses whether coding agents should automatically generate tests alongside the code they produce, addressing a key quality assurance consideration in AI-assisted development. This li

toolssimon-willison--x

DrawVideo: Generating Long Video from Storyboard Keyframe Sketches

arXiv:2605.23508v1 Announce Type: cross Abstract: Long video generation requires high-fidelity synthesis, coherent narrative structure, and user control over extended time spans. Existing text-to-vide

DreamerNLplus: Interpretable Modeling of Mental Health Dynamics from Social Media Timelines using Hybrid Rule-Based and RAG Methods

arXiv:2605.23052v1 Announce Type: cross Abstract: We present DreamerNLplus, a hybrid framework for modeling mental health dynamics from social media timelines in the CLPsych 2026 shared task. Our syst

Dreaming Smoothly and Sample Efficiently with Gradient Penalized Latent Dynamics

arXiv:2605.23089v1 Announce Type: cross Abstract: Model-based reinforcement learning improves sample efficiency by learning a world model. However, existing latent world models such as DreamerV3 do no

DRIVESPATIAL: A Benchmark for Spatiotemporal Intelligence in VLMs for Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2605.23176v1 Announce Type: new Abstract: Spatiotemporal intelligence in autonomous driving (AD) requires an agent to integrate multi-view observations into a coherent scene representation, main

DRL-Driven Edge-Aware Utility Optimization for Multi-Slice 6G Networks

arXiv:2605.23056v1 Announce Type: cross Abstract: Virtual Reality (VR) services delivered over 6G networks demand ultra-low latency and high bandwidth to ensure seamless user experiences. This paper p

Droneulator: A Portable UAV Simulator for Agricultural Workflows with RotorPy and Godot 4

arXiv:2605.23386v1 Announce Type: new Abstract: Agricultural UAV research requires simulators that integrate realistic 3D scenes, high-fidelity vehicle dynamics, and robotics middleware, while remaini

safetyarxiv-cs-ro

DualMem: Bypassing the Objectness Bottleneck for Calibrated Unknown-Stream Filtering in Open-World Object Detection

arXiv:2605.23634v1 Announce Type: cross Abstract: Open-world object detection (OWOD) requires detectors to localize known classes while identifying unknown objects for future incremental learning. We

Dynamic Weight-based Temporal Aggregation for Low-light Video Enhancement Under Extreme Noise

arXiv:2510.09450v2 Announce Type: replace Abstract: Low-light video enhancement (LLVE) is challenging due to noise, low contrast, and color degradation. While learning-based methods enable fast infere

safetyarxiv-cs-cv

Applications

Edge Assisted Multi-Camera Vehicle Tracking Framework for Real-Time and Scalable Deployment

arXiv:2511.13904v2 Announce Type: replace Abstract: Cameras are a core sensing modality in modern intelligent transportation systems (ITS), providing rich visual information on road-user activities. M

applicationsarxiv-cs-cv

EDGE-OPD: Internalizing Privileged Context with Evidence Guided On-Policy Distillation

arXiv:2605.23493v1 Announce Type: new Abstract: On-Policy Distillation (OPD) has gained wide attraction as an LLM post-training paradigm due to its effectiveness in improving capabilities without intr

Efficient and Transferable Agentic Knowledge Graph RAG via Reinforcement Learning

arXiv:2509.26383v5 Announce Type: replace-cross Abstract: Knowledge-graph retrieval-augmented generation (KG-RAG) couples large language models (LLMs) with structured, verifiable knowledge graphs (KGs

Efficient Gradient Estimation for Parameterized Quantum Systems with Lie Algebraic Symmetries

model-releasesarxiv-cs-lg

arXiv:2404.05108v3 Announce Type: replace-cross Abstract: Gradient estimation is a central challenge in training parameterized quantum circuits (PQCs) for hybrid quantum-classical optimization and lea

Efficient Learned Image Compression without Entropy Coding

arXiv:2605.23323v1 Announce Type: cross Abstract: Entropy coding is widely used in typical learned image compression (LIC) that converts latents into a compact bitstream. However, entropy coding is ty

researcharxiv-cs-cv

Efficient One-Step Diffusion Restoration Model with Compact Token Compression and Linear Attention

model-releasesarxiv-cs-cv

arXiv:2605.23451v1 Announce Type: new Abstract: Real-world image super-resolution aims to recover high-quality images from complex and unknown real-world degradations. However, existing generative Rea

EM-Vid: Training-Free Entity-Centric Memory for Efficient and Consistent Multi-Shot Video Generation

arXiv:2605.23610v1 Announce Type: cross Abstract: Multi-shot video generation requires maintaining a consistent appearance of recurring entities across shots while remaining faithful to shot-specific

Applications

Emotion Recognition in Sign Language Conversation

arXiv:2605.23328v1 Announce Type: new Abstract: Emotion Recognition in Conversation is a core component of affective computing, while current resources of sign language emotion datasets primarily focu

applicationsarxiv-cs-cl

Empirical Bayes Conformal Prediction for Vision and Language Models

arXiv:2605.23189v1 Announce Type: new Abstract: Conformal prediction (CP) gives distribution-free coverage for modern vision and language models, but it is often forced to make a ranking decision from

Empowering 9-1-1 Calltaking Training with Generative AI: Experiences and Lessons Learned

arXiv:2602.13241v2 Announce Type: replace-cross Abstract: Emergency call-takers form the first operational link in public safety response, handling over 240 million calls annually while facing a susta

Encrypted Neural Networks without Overflows

arXiv:2605.23096v1 Announce Type: cross Abstract: Fully homomorphic encryption (FHE) enables private inference by evaluating neural networks on encrypted data. In this way, we can delegate the computa

Industry

Encyclical Letter of His Holiness Leo XIV Magnifica Humanitas (15 May 2026) http://www.vatican.va/content/leo-xiv/en/encyclicals/documents/2…

I cannot provide a summary of this document because Pope Leo XIV and an encyclical from 2026 do not exist—this is a fictional future date. The current pope is Francis (elected 2013), and no encyclical

industrysonya-huang--x

Energy-Guided Generative Modeling for Low-Energy Molecular Structure Discovery

arXiv:2512.22597v2 Announce Type: replace Abstract: Exploring molecular energy landscapes and identifying ground-state conformations are central challenges in computational chemistry. However, generat

Energy per Successful Goal: Goal-Level Energy Accounting for Agentic AI Systems

arXiv:2605.22883v1 Announce Type: new Abstract: Current AI energy benchmarks measure consumption at the granularity of a single model invocation or training run. For classical single-turn workloads th

Enhancing 3D Semantic Scene Completion with a Refinement Module

arXiv:2512.18363v2 Announce Type: replace Abstract: We propose ESSC-RM, a plug-and-play Enhancing framework for Semantic Scene Completion with a Refinement Module, which can be seamlessly integrated i

researcharxiv-cs-cv

Enhancing Blood Cells Classification using Hybrid Quantum Neural Networks

arXiv:2605.23324v1 Announce Type: new Abstract: Accurate classification of microscopic blood cells is still a critical task in medical image analysis, where subtle variations and limited data can chal

researcharxiv-cs-cv

Enhancing Deep Neural Network Reliability with Refinement and Calibration

arXiv:2605.23249v1 Announce Type: cross Abstract: Although deep neural networks (DNNs) achieve high predictive accuracy, their confidence estimates are often unreliable, potentially compromising user

Entropy-Aware On-Policy Distillation of Language Models

arXiv:2603.07079v2 Announce Type: replace-cross Abstract: On-policy distillation is a promising approach for transferring knowledge between language models, where a student learns from dense token-lev

safetyarxiv-cs-cl

Entropy Equivalence Testing

model-releasesarxiv-cs-lg

arXiv:2605.23225v1 Announce Type: cross Abstract: We introduce the problem of entropy equivalence testing for probability distributions, a relaxation of the well-studied closeness testing problem, whe

Entrywise Error Bounds for Spectral Ranking with Semi-Random Adversaries

arXiv:2605.23854v1 Announce Type: new Abstract: Bradley-Terry-Luce (BTL) model estimation is a well-established strategy to rank a collection of items given a dataset of pairwise comparisons. Although

EquiSumm : A Gender Bias-Aware Framework for Inclusive Tweet Summarization

arXiv:2605.23412v1 Announce Type: new Abstract: While social media platforms, such as Twitter, provide a medium for large-scale opinion sharing during news events, it is manually impossible for indivi

safetyarxiv-cs-cl

ETCHR: Editing To Clarify and Harness Reasoning

arXiv:2605.23897v1 Announce Type: cross Abstract: Multimodal Large Language Models have advanced visual reasoning, yet a purely textual chain of thought remains a bottleneck for questions that require

Industry

EU reportedly plans to fine Google over search practices

The European Commission, the European Union’s executive arm, reportedly plans to issue a record fine to Google LLC over its practices in the search market. German newspaper Handelsblatt today cited so

industrysiliconangle

Evaluating Counterfactual Strategic Reasoning in Large Language Models

arXiv:2603.19167v2 Announce Type: replace Abstract: We evaluate Large Language Models (LLMs) in repeated game-theoretic settings to assess whether strategic performance reflects genuine reasoning or r

researcharxiv-cs-cl