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DERM-3R: A Resource-Efficient Multimodal Agents Framework for Dermatologic Diagnosis and Treatment in Real-World Clinical Settings

arXiv:2604.09596v1 Announce Type: new Abstract: Dermatologic diseases impose a large and growing global burden, affecting billions and substantially reducing quality of life. While modern therapies ca

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Safety

Descriptor-Injected Cross-Modal Learning: A Systematic Exploration of Audio-MIDI Alignment via Spectral and Melodic Features

DGX agent

arXiv:2604.10283v1 Announce Type: cross Abstract: Cross-modal retrieval between audio recordings and symbolic music representations (MIDI) remains challenging because continuous waveforms and discrete

safetyarxiv-cs-lg

14 Apr 2026

Design Experiments to Compare Multi-armed Bandit Algorithms

arXiv:2603.05919v2 Announce Type: replace Abstract: Online platforms routinely compare multi-armed bandit algorithms, such as UCB and Thompson Sampling, to select the best-performing policy. Unlike st

Design Principles for Sequence Models via Coefficient Dynamics

arXiv:2510.09389v2 Announce Type: replace-cross Abstract: Deep sequence models, ranging from Transformers and State Space Models (SSMs) to more recent approaches such as gated linear RNNs, fundamental

Designing Adaptive Digital Nudging Systems with LLM-Driven Reasoning

arXiv:2604.11206v1 Announce Type: cross Abstract: Digital nudging systems lack architectural guidance for translating behavioral science into software design. While research identifies nudge strategie

Detecting Corporate AI-Washing via Cross-Modal Semantic Inconsistency Learning

arXiv:2604.09644v1 Announce Type: cross Abstract: Corporate AI-washing-the strategic misrepresentation of AI capabilities via exaggerated or fabricated cross-channel disclosures-has emerged as a syste

Detecting critical treatment effect bias in small subgroups

model-releasesarxiv-cs-lg

arXiv:2404.18905v3 Announce Type: replace-cross Abstract: Randomized trials are considered the gold standard for making informed decisions in medicine, yet they often lack generalizability to the pati

Detecting Invariant Manifolds in ReLU-Based RNNs

arXiv:2510.03814v4 Announce Type: replace-cross Abstract: Recurrent Neural Networks (RNNs) have found widespread applications in machine learning for time series prediction and dynamical systems recon

Detecting RAG Extraction Attack via Dual-Path Runtime Integrity Game

arXiv:2604.10717v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems augment large language models with external knowledge, yet introduce a critical security vulnerability: R

Detecting Safety Violations Across Many Agent Traces

arXiv:2604.11806v1 Announce Type: new Abstract: To identify safety violations, auditors often search over large sets of agent traces. This search is difficult because failures are often rare, complex,

Detection Is Cheap, Routing Is Learned: Why Refusal-Based Alignment Evaluation Fails

arXiv:2603.18280v2 Announce Type: replace-cross Abstract: Current alignment evaluation mostly measures whether models encode dangerous concepts and whether they refuse harmful requests. Both miss the

Development and evaluation of CADe systems in low-prevalence setting: The RARE25 challenge for early detection of Barrett's neoplasia

model-releasesarxiv-cs-cv

arXiv:2604.11171v1 Announce Type: new Abstract: Computer-aided detection (CADe) of early neoplasia in Barrett's esophagus is a low-prevalence surveillance problem in which clinically relevant findings

Device-Conditioned Neural Architecture Search for Efficient Robotic Manipulation

arXiv:2604.10170v1 Announce Type: cross Abstract: The growing complexity of visuomotor policies poses significant challenges for deployment with heterogeneous robotic hardware constraints. However, mo

safetyarxiv-cs-cv

Diagnosing Failure Modes of Neural Operators Across Diverse PDE Families

arXiv:2601.11428v4 Announce Type: replace Abstract: Neural PDE solvers have shown strong performance on standard benchmarks, but their robustness under deployment-relevant distribution shifts remains

researcharxiv-cs-lg

Agents

Diagnosing Retrieval vs. Utilization Bottlenecks in LLM Agent Memory

arXiv:2603.02473v2 Announce Type: replace Abstract: Memory-augmented LLM agents store and retrieve information from prior interactions, yet the relative importance of how memories are written versus h

agentsarxiv-cs-ai

Dialectic-Med: Mitigating Diagnostic Hallucinations via Counterfactual Adversarial Multi-Agent Debate

arXiv:2604.11258v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) in healthcare suffer from severe confirmation bias, often hallucinating visual details to support initial, pote

safetyarxiv-cs-cl

Dialogue based Interactive Explanations for Safety Decisions in Human Robot Collaboration

arXiv:2604.05896v2 Announce Type: replace Abstract: As robots increasingly operate in shared, safety critical environments, acting safely is no longer sufficient robots must also make their safety dec

safetyarxiv-cs-ro

DIB-OD: Preserving the Invariant Core for Robust Heterogeneous Graph Adaptation via Decoupled Information Bottleneck and Online Distillation

arXiv:2604.10882v1 Announce Type: cross Abstract: Graph Neural Network pretraining is pivotal for leveraging unlabeled graph data. However, generalizing across heterogeneous domains remains a major ch

Local Ai

Did they stop the free cloud tier?

This Reddit thread on r/ollama discusses community questions around whether Ollama discontinued or changed its free cloud tier. Ollama Cloud launched in preview in September 2025 with fixed-price subs

local-air-ollama

Applications

DiffClean: Diffusion-based Makeup Removal for Accurate Age Estimation

arXiv:2507.13292v3 Announce Type: replace Abstract: Accurate age verification can protect underage users from unauthorized access to online platforms and e-commerce sites that provide age-restricted s

applicationsarxiv-cs-cv

Local Ai

Different types of syntactic agreement recruit the same units within large language models

arXiv:2512.03676v2 Announce Type: replace Abstract: Large language models (LLMs) can reliably distinguish grammatical from ungrammatical sentences, but how grammatical knowledge is represented within

local-aiarxiv-cs-cl

Differentiable free energy surface: a variational approach to directly observing rare events using generative deep-learning models

arXiv:2604.09769v1 Announce Type: cross Abstract: Rare events are central to the evolution of complex many-body systems, characterized as key transitional configurations on the free energy surface (FE

Differentiable Vector Quantization for Rate-Distortion Optimization of Generative Image Compression

arXiv:2604.10546v1 Announce Type: new Abstract: The rapid growth of visual data under stringent storage and bandwidth constraints makes extremely low-bitrate image compression increasingly important.

researcharxiv-cs-cv

Differentially Private Verification of Distribution Properties

model-releasesarxiv-cs-lg

arXiv:2604.10819v1 Announce Type: cross Abstract: A recent line of work initiated by Chiesa and Gur and further developed by Herman and Rothblum investigates the sample and communication complexity of

Diffusion-Based Generative Priors for Efficient Beam Alignment in Directional Networks

arXiv:2604.09653v1 Announce Type: cross Abstract: Beam alignment is a key challenge in directional mmWave and THz systems, where narrow beams require accurate yet low-overhead training. Existing learn

Diffusion-CAM: Faithful Visual Explanations for dMLLMs

arXiv:2604.11005v1 Announce Type: new Abstract: While diffusion Multimodal Large Language Models (dMLLMs) have recently achieved remarkable strides in multimodal generation, the development of interpr

Diffusion Denoiser Achievable Analysis for Finite Blocklength Unsourced Random Access

arXiv:2604.09904v1 Announce Type: cross Abstract: Polyanskiy proposed a framework for the unsourced multiple access channel (MAC) problem where users employ a common codebook in the finite blocklength

Applications

Diffusion Reinforcement Learning Based Online 3D Bin Packing Spatial Strategy Optimization

arXiv:2604.10953v1 Announce Type: new Abstract: The online 3D bin packing problem is important in logistics, warehousing and intelligent manufacturing, with solutions shifting to deep reinforcement le

applicationsarxiv-cs-ro

Digital hybridity and relics in cultural heritage: using corpus linguistics to inform design in emerging technologies from AI to VR

arXiv:2604.09669v1 Announce Type: cross Abstract: Hybrid technologies enable the blending of physical and digital elements, creating new ways to experience and interact with the world. Such technologi

DiningBench: A Hierarchical Multi-view Benchmark for Perception and Reasoning in the Dietary Domain

model-releasesarxiv-cs-cv

arXiv:2604.10425v1 Announce Type: new Abstract: Recent advancements in Vision-Language Models (VLMs) have revolutionized general visual understanding. However, their application in the food domain rem

DINO_4D: Semantic-Aware 4D Reconstruction

arXiv:2604.09877v1 Announce Type: cross Abstract: In the intersection of computer vision and robotic perception, 4D reconstruction of dynamic scenes serve as the critical bridge connecting low-level g

Directional Mollification for Knot-Preserving C^{infty} Smoothing of Polygonal Chains with Explicit Curvature Bounds

arXiv:2603.21831v2 Announce Type: replace Abstract: Starting from a polygonal chain (a first-order polynomial spline) through prescribed knots (vertices), we introduce the extit{directional mollificat

researcharxiv-cs-ro

Disambiguation-Centric Finetuning Makes Enterprise Tool-Calling LLMs More Realistic and Less Risky

arXiv:2507.03336v4 Announce Type: replace Abstract: Large language models (LLMs) are increasingly tasked with invoking enterprise APIs, yet they routinely falter when near-duplicate tools vie for the

DisCo-FLoc: Using Dual-Level Visual-Geometric Contrasts to Disambiguate Depth-Aware Visual Floorplan Localization

arXiv:2601.01822v2 Announce Type: replace-cross Abstract: Since floorplan data is readily available, long-term persistent, and robust to changes in visual appearance, visual Floorplan Localization (FL

researcharxiv-cs-cv

Local Ai

Disco-RAG: Discourse-Aware Retrieval-Augmented Generation

arXiv:2601.04377v4 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as an important means of enhancing the performance of large language models (LLMs) in knowled

local-aiarxiv-cs-ai

Discourse Coherence and Response-Guided Context Rewriting for Multi-Party Dialogue Generation

arXiv:2604.06784v2 Announce Type: replace Abstract: Previous research on multi-party dialogue generation has predominantly leveraged structural information inherent in dialogues to directly inform the

researcharxiv-cs-cl

Discourse Diversity in Multi-Turn Empathic Dialogue

arXiv:2604.11742v1 Announce Type: cross Abstract: Large language models (LLMs) produce responses rated as highly empathic in single-turn settings (Ayers et al., 2023; Lee et al., 2024), yet they are a

Discrete Bayesian Sample Inference for Graph Generation

arXiv:2511.03015v2 Announce Type: replace Abstract: Generating graph-structured data is crucial in applications such as molecular generation, knowledge graphs, and network analysis. However, their dis

researcharxiv-cs-lg

Discrete Flow Maps

arXiv:2604.09784v1 Announce Type: cross Abstract: The sequential nature of autoregressive next-token prediction imposes a fundamental speed limit on large language models. While continuous flow models

Applications

Disentangled Point Diffusion for Precise Object Placement

arXiv:2604.11793v1 Announce Type: new Abstract: Recent advances in robotic manipulation have highlighted the effectiveness of learning from demonstration. However, while end-to-end policies excel in e

applicationsarxiv-cs-ro

DiSPA: Differential Substructure-Pathway Attention for Drug Response Prediction

arXiv:2601.14346v2 Announce Type: replace-cross Abstract: Accurate prediction of drug response in precision medicine requires models that capture how specific chemical substructures interact with cell

DistDF: Time-Series Forecasting Needs Joint-Distribution Wasserstein Alignment

arXiv:2510.24574v2 Announce Type: replace-cross Abstract: Training time-series forecasting models requires aligning the conditional distribution of model forecasts with that of the label sequence. The

Distributionally Robust K-Means Clustering

arXiv:2604.11118v1 Announce Type: new Abstract: K-means clustering is a workhorse of unsupervised learning, but it is notoriously brittle to outliers, distribution shifts, and limited sample sizes. Vi

researcharxiv-cs-lg

Distributionally Robust PAC-Bayesian Control

arXiv:2604.10588v1 Announce Type: new Abstract: We present a distributionally robust PAC-Bayesian framework for certifying the performance of learning-based finite-horizon controllers. While existing

Do Agent Rules Shape or Distort? Guardrails Beat Guidance in Coding Agents

arXiv:2604.11088v1 Announce Type: new Abstract: Developers increasingly guide AI coding agents through natural language instruction files (e.g., CLAUDE.md, .cursorrules), yet no controlled study has m

Industry

Do anyone have this feature?

A Reddit post from the r/ChatGPT community where a user inquires whether other users have access to a specific ChatGPT feature, likely a newly rolled-out or experimental capability not yet available t

industryr-chatgpt

Do BERT Embeddings Encode Narrative Dimensions? A Token-Level Probing Analysis of Time, Space, Causality, and Character in Fiction

arXiv:2604.10786v1 Announce Type: cross Abstract: Narrative understanding requires multidimensional semantic structures. This study investigates whether BERT embeddings encode dimensions of fictional

Do Instance Priors Help Weakly Supervised Semantic Segmentation?

arXiv:2604.11170v1 Announce Type: new Abstract: Semantic segmentation requires dense pixel-level annotations, which are costly and time-consuming to acquire. To address this, we present SeSAM, a frame

researcharxiv-cs-cv