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arXiv:2604.07892v1 Announce Type: new Abstract: Instruction-tuned language models increasingly rely on large multi-turn dialogue corpora, but these datasets are often noisy and structurally inconsiste

local-aiarxiv-cs-cl

Database Querying under Missing Values Governed by Missingness Mechanisms

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DGX agent

arXiv:2604.06520v1 Announce Type: cross Abstract: We address the problems of giving a semantics to- and doing query answering (QA) on a relational database (RDB) that has missing values (MVs). The cau

researcharxiv-cs-ai

10 Apr 2026

Applications

DBMF: A Dual-Branch Multimodal Framework for Out-of-Distribution Detection

arXiv:2604.08261v1 Announce Type: new Abstract: The complex and dynamic real-world clinical environment demands reliable deep learning (DL) systems. Out-of-distribution (OOD) detection plays a critica

applicationsarxiv-cs-cv

DDP-SA: Scalable Privacy-Preserving Federated Learning via Distributed Differential Privacy and Secure Aggregation

model-releasesarxiv-cs-lg

arXiv:2604.07125v1 Announce Type: cross Abstract: This article presents DDP-SA, a scalable privacy-preserving federated learning framework that jointly leverages client-side local differential privacy

DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation

arXiv:2511.19365v2 Announce Type: replace-cross Abstract: Pixel diffusion aims to generate images directly in pixel space in an end-to-end fashion. This approach avoids the limitations of VAE in the t

Decompose, Look, and Reason: Reinforced Latent Reasoning for VLMs

arXiv:2604.07518v1 Announce Type: new Abstract: Vision-Language Models often struggle with complex visual reasoning due to the visual information loss in textual CoT. Existing methods either add the c

safetyarxiv-cs-cl

Deep Learning-Powered Visual SLAM Aimed at Assisting Visually Impaired Navigation

arXiv:2510.20549v2 Announce Type: replace Abstract: Despite advancements in SLAM technologies, robust operation under challenging conditions such as low-texture, motion-blur, or challenging lighting r

safetyarxiv-cs-cv

Demystifying OPD: Length Inflation and Stabilization Strategies for Large Language Models

arXiv:2604.08527v1 Announce Type: new Abstract: On-policy distillation (OPD) trains student models under their own induced distribution while leveraging supervision from stronger teachers. We identify

safetyarxiv-cs-cl

Agents

Density-Driven Optimal Control: Convergence Guarantees for Stochastic LTI Multi-Agent Systems

arXiv:2604.08495v1 Announce Type: cross Abstract: This paper addresses the decentralized non-uniform area coverage problem for multi-agent systems, a critical task in missions with high spatial priori

agentsarxiv-cs-ro

Depression Detection at the Point of Care: Automated Analysis of Linguistic Signals from Routine Primary Care Encounters

arXiv:2604.06193v1 Announce Type: cross Abstract: Depression is underdiagnosed in primary care, yet timely identification remains critical. Recorded clinical encounters, increasingly common with digit

Designing Safe and Accountable GenAI as a Learning Companion with Women Banned from Formal Education

arXiv:2604.07253v1 Announce Type: cross Abstract: In gender-restrictive and surveilled contexts, where access to formal education may be restricted for women, pursuing education involves safety and pr

safetyarxiv-cs-ai

Detecting HIV-Related Stigma in Clinical Narratives Using Large Language Models

model-releasesarxiv-cs-cl

arXiv:2604.07717v1 Announce Type: new Abstract: Human immunodeficiency virus (HIV)-related stigma is a critical psychosocial determinant of health for people living with HIV (PLWH), influencing mental

Development of ML model for triboelectric nanogenerator based sign language detection system

arXiv:2604.06220v1 Announce Type: cross Abstract: Sign language recognition (SLR) is vital for bridging communication gaps between deaf and hearing communities. Vision-based approaches suffer from occ

DHFP-PE: Dual-Precision Hybrid Floating Point Processing Element for AI Acceleration

arXiv:2604.04507v2 Announce Type: replace-cross Abstract: The rapid adoption of low-precision arithmetic in artificial intelligence and edge computing has created a strong demand for energy-efficient

researcharxiv-cs-ro

Diagnosing and Mitigating Sycophancy and Skepticism in LLM Causal Judgment

arXiv:2601.08258v3 Announce Type: replace Abstract: Large language models increasingly fail in a way that scalar accuracy cannot diagnose: they produce a sound reasoning trace and then abandon it unde

DietDelta: A Vision-Language Approach for Dietary Assessment via Before-and-After Images

arXiv:2604.06352v1 Announce Type: cross Abstract: Accurate dietary assessment is critical for precision nutrition, yet most image-based methods rely on a single pre-consumption image and provide only

Local Ai

Differentially Private Best-Arm Identification

arXiv:2406.06408v2 Announce Type: replace-cross Abstract: Best Arm Identification (BAI) problems are progressively used for data-sensitive applications, such as designing adaptive clinical trials, tun

local-aiarxiv-cs-lg

Differentially Private Language Generation and Identification in the Limit

arXiv:2604.08504v1 Announce Type: cross Abstract: We initiate the study of language generation in the limit, a model recently introduced by Kleinberg and Mullainathan [KM24], under the constraint of d

DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models

arXiv:2306.14685v5 Announce Type: replace-cross Abstract: We demonstrate that pre-trained text-to-image diffusion models, despite being trained on raster images, possess a remarkable capacity to guide

tutorialsarxiv-cs-ai

Diffusion Language Models Know the Answer Before Decoding

arXiv:2508.19982v5 Announce Type: replace Abstract: Diffusion language models (DLMs) have recently emerged as an alternative to autoregressive approaches, offering parallel sequence generation and fle

Diffusion Processes on Implicit Manifolds

arXiv:2604.07213v1 Announce Type: new Abstract: High-dimensional data are often modeled as lying near a low-dimensional manifold. We study how to construct diffusion processes on this data manifold in

tutorialsarxiv-cs-lg

DiffVC: A Non-autoregressive Framework Based on Diffusion Model for Video Captioning

arXiv:2604.08084v1 Announce Type: new Abstract: Current video captioning methods usually use an encoder-decoder structure to generate text autoregressively. However, autoregressive methods have inhere

Digital Skin, Digital Bias: Uncovering Tone-Based Biases in LLMs and Emoji Embeddings

arXiv:2604.06863v1 Announce Type: cross Abstract: Skin-toned emojis are crucial for fostering personal identity and social inclusion in online communication. As AI models, particularly Large Language

DINO-QPM: Adapting Visual Foundation Models for Globally Interpretable Image Classification

arXiv:2604.07166v1 Announce Type: cross Abstract: Although visual foundation models like DINOv2 provide state-of-the-art performance as feature extractors, their complex, high-dimensional representati

researcharxiv-cs-lg

Agents

DinoRADE: Full Spectral Radar-Camera Fusion with Vision Foundation Model Features for Multi-class Object Detection in Adverse Weather

arXiv:2604.08074v1 Announce Type: new Abstract: Reliable and weather-robust perception systems are essential for safe autonomous driving and typically employ multi-modal sensor configurations to achie

agentsarxiv-cs-cv

Direct Segmentation without Logits Optimization for Training-Free Open-Vocabulary Semantic Segmentation

model-releasesarxiv-cs-cv

arXiv:2604.07723v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment arbitrary category regions in images using open-vocabulary prompts, necessitating that exis

DisCEdge: Distributed Context Management for Large Language Models at the Edge

arXiv:2511.22599v2 Announce Type: replace-cross Abstract: Deploying Large Language Model (LLM) services at the edge benefits latency-sensitive and privacy-aware applications. However, the stateless na

researcharxiv-cs-lg

Discrete Flow Matching Policy Optimization

arXiv:2604.06491v1 Announce Type: cross Abstract: We introduce Discrete flow Matching policy Optimization (DoMinO), a unified framework for Reinforcement Learning (RL) fine-tuning Discrete Flow Matchi

safetyarxiv-cs-ai

DISSECT: Diagnosing Where Vision Ends and Language Priors Begin in Scientific VLMs

arXiv:2604.06250v1 Announce Type: cross Abstract: When asked to describe a molecular diagram, a Vision-Language Model correctly identifies ``a benzene ring with an -OH group.'' When asked to reason ab

Distilling Specialized Orders for Visual Generation

arXiv:2504.17069v2 Announce Type: replace Abstract: Autoregressive (AR) image generators are becoming increasingly popular due to their ability to produce high-quality images and their scalability. Ty

Distributed Interpretability and Control for Large Language Models

arXiv:2604.06483v1 Announce Type: cross Abstract: Large language models that require multiple GPU cards to host are usually the most capable models. It is necessary to understand and steer these model

Distributed Multi-Layer Editing for Rule-Level Knowledge in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2604.08284v1 Announce Type: new Abstract: Large language models store not only isolated facts but also rules that support reasoning across symbolic expressions, natural language explanations, an

Distributional Open-Ended Evaluation of LLM Cultural Value Alignment Based on Value Codebook

arXiv:2604.06210v2 Announce Type: cross Abstract: As LLMs are globally deployed, aligning their cultural value orientations is critical for safety and user engagement. However, existing benchmarks fac

safetyarxiv-cs-ai

DIVERSED: Relaxed Speculative Decoding via Dynamic Ensemble Verification

arXiv:2604.07622v1 Announce Type: new Abstract: Speculative decoding is an effective technique for accelerating large language model inference by drafting multiple tokens in parallel. In practice, its

DMin: Scalable Training Data Influence Estimation for Diffusion Models

arXiv:2412.08637v4 Announce Type: replace Abstract: Identifying the training data samples that most influence a generated image is a critical task in understanding diffusion models (DMs), yet existing

Do MLLMs Really Understand Space? A Mathematical Reasoning Evaluation

arXiv:2602.11635v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have achieved strong performance on perception-oriented tasks, yet their ability to perform mathematical sp

Do We Need Distinct Representations for Every Speech Token? Unveiling and Exploiting Redundancy in Large Speech Language Models

arXiv:2604.06871v1 Announce Type: cross Abstract: Large Speech Language Models (LSLMs) typically operate at high token rates (tokens/s) to ensure acoustic fidelity, yet this results in sequence length

Domain-Contextualized Inference: A Computable Graph Architecture for Explicit-Domain Reasoning

arXiv:2604.04344v2 Announce Type: replace Abstract: We establish a computation-substrate-agnostic inference architecture in which domain is an explicit first-class computational parameter. This produc

'Don't Be Afraid, Just Learn': Insights from Industry Practitioners to Prepare Software Engineers in the Age of Generative AI

arXiv:2604.06342v1 Announce Type: cross Abstract: Although tension between university curricula and industry expectations has existed in some form for decades, the rapid integration of generative AI (

tutorialsarxiv-cs-ai

'Don't Do That!': Guiding Embodied Systems through Large Language Model-based Constraint Generation

arXiv:2506.04500v3 Announce Type: replace-cross Abstract: Recent advancements in large language models (LLMs) have spurred interest in robotic navigation that incorporates complex spatial, mathematica

researcharxiv-cs-ro

Don't Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget

arXiv:2402.02249v3 Announce Type: replace Abstract: We study how to best spend a budget of noisy labels to compare the accuracy of two binary classifiers. It's common practice to collect and aggregate

tutorialsarxiv-cs-lg

Don't Overthink It: Inter-Rollout Action Agreement as a Free Adaptive-Compute Signal for LLM Agents

model-releasesarxiv-cs-cl

arXiv:2604.08369v1 Announce Type: cross Abstract: Inference-time compute scaling has emerged as a powerful technique for improving the reliability of large language model (LLM) agents, but existing me

DosimeTron: Automating Personalized Monte Carlo Radiation Dosimetry in PET/CT with Agentic AI

arXiv:2604.06280v1 Announce Type: cross Abstract: Purpose: To develop and evaluate DosimeTron, an agentic AI system for automated patient-specific MC internal radiation dosimetry in PET/CT examination

Double: Breaking the Acceleration Limit via Double Retrieval Speculative Parallelism

arXiv:2601.05524v2 Announce Type: replace Abstract: Parallel Speculative Decoding (PSD) accelerates traditional Speculative Decoding (SD) by overlapping draft generation with verification. However, it

DP-DeGauss: Dynamic Probabilistic Gaussian Decomposition for Egocentric 4D Scene Reconstruction

arXiv:2604.07986v1 Announce Type: new Abstract: Egocentric video is crucial for next-generation 4D scene reconstruction, with applications in AR/VR and embodied AI. However, reconstructing dynamic fir

Applications

DQA: Diagnostic Question Answering for IT Support

arXiv:2604.05350v2 Announce Type: replace Abstract: Enterprise IT support interactions are fundamentally diagnostic: effective resolution requires iterative evidence gathering from ambiguous user repo

applicationsarxiv-cs-cl

Draw-In-Mind: Rebalancing Designer-Painter Roles in Unified Multimodal Models Benefits Image Editing

arXiv:2509.01986v4 Announce Type: replace-cross Abstract: In recent years, integrating multimodal understanding and generation into a single unified model has emerged as a promising paradigm. While th

Drift-Based Policy Optimization: Native One-Step Policy Learning for Online Robot Control

arXiv:2604.03540v2 Announce Type: replace Abstract: Although multi-step generative policies achieve strong performance in robotic manipulation by modeling multimodal action distributions, they require

safetyarxiv-cs-ro