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CoQuant: Joint Weight-Activation Subspace Projection for Mixed-Precision LLMs

arXiv:2604.26378v1 Announce Type: new Abstract: Post-training quantization (PTQ) has become an important technique for reducing the inference cost of Large Language Models (LLMs). While recent mixed-p

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Correcting Performance Estimation Bias in Imbalanced Classification with Minority Subconcepts

DGX agent

arXiv:2604.26024v1 Announce Type: cross Abstract: Class-level evaluation can conceal substantial performance disparities across subconcepts within the same class, causing models that perform well on a

safetyarxiv-cs-ai

30 Apr 2026

Crime Hotspot Prediction Using Deep Graph Convolutional Networks

arXiv:2506.13116v2 Announce Type: replace-cross Abstract: Crime hotspot prediction is critical for ensuring urban safety and effective law enforcement, it remains challenging due to complex spatial de

safetyarxiv-cs-cl

Cross-Domain Transfer of Hyperspectral Foundation Models

arXiv:2604.26478v1 Announce Type: new Abstract: Hyperspectral imaging (HSI) semantic segmentation typically relies on in-domain training, but limited data availability often restricts model performanc

Culturally Aware GenAI Risks for Youth: Perspectives from Youth, Parents, and Teachers in a Non-Western Context

arXiv:2604.26494v1 Announce Type: cross Abstract: Generative AI tools are widely used by youth and have introduced new privacy and safety challenges. While prior research has explored youth's safety i

CurEvo: Curriculum-Guided Self-Evolution for Video Understanding

arXiv:2604.26707v1 Announce Type: new Abstract: Recent advances in self-evolution video understanding frameworks have demonstrated the potential of autonomous learning without human annotations. Howev

Data Balancing Strategies: A Systematic Survey of Resampling and Augmentation Methods

arXiv:2505.13518v2 Announce Type: replace-cross Abstract: Imbalanced datasets, where one class significantly outnumbers others, remain a persistent challenge in machine learning, often biasing predict

researcharxiv-cs-ai

Data-Centric Foundation Models in Computational Healthcare: A Survey

arXiv:2401.02458v3 Announce Type: replace-cross Abstract: The advent of foundation models (FMs) as an emerging suite of AI techniques has struck a wave of opportunities in computational healthcare. Th

DB-KSVD: Scalable Alternating Optimization for Disentangling High-Dimensional Embedding Spaces

arXiv:2505.18441v2 Announce Type: replace Abstract: Dictionary learning has recently emerged as a promising approach for mechanistic interpretability of large transformer models. Disentangling high-di

DC-Ada: Reward-Only Decentralized Sensor Adaptation for Heterogeneous Multi-Robot Teams

arXiv:2604.03905v2 Announce Type: replace-cross Abstract: Heterogeneity is a defining feature of deployed multi-robot teams: platforms often differ in sensing modalities, ranges, fields of view, and f

Decide less, communicate more: On the construct validity of end-to-end fact-checking in medicine

arXiv:2506.20876v4 Announce Type: replace Abstract: Technological progress has led to concrete advancements in tasks that were regarded as challenging, such as automatic fact-checking. Interest in ado

researcharxiv-cs-cl

Decoupled Prototype Matching with Vision Foundation Models for Few-Shot Industrial Object Detection

arXiv:2604.26404v1 Announce Type: new Abstract: Industrial object detection systems typically rely on large annotated datasets, which are expensive to collect and challenging to maintain in industrial

Decoupling Knowledge and Task Subspaces for Composable Parametric Retrieval Augmented Generation

model-releasesarxiv-cs-cl

arXiv:2604.26768v1 Announce Type: new Abstract: Parametric Retrieval-Augmented Generation (PRAG) encodes external documents into lightweight parameter modules that can be retrieved and merged at infer

Deep neural networks with ReLU, leaky ReLU, and softplus activation provably overcome the curse of dimensionality for Kolmogorov partial differential equations with Lipschitz nonlinearities in the L^p-sense

arXiv:2309.13722v3 Announce Type: replace-cross Abstract: Recently, several deep learning (DL) methods for approximating high-dimensional partial differential equations (PDEs) have been proposed. The

Deep-testing: the case of dependence detection

arXiv:2604.26558v1 Announce Type: cross Abstract: Deep learning methods have proved highly effective for classification and image recognition problems. In this paper, we ask whether this success can b

Delineating Knowledge Boundaries for Honest Large Vision-Language Models

arXiv:2604.26419v1 Announce Type: cross Abstract: Large Vision-Language Models (VLMs) have achieved remarkable multimodal performance yet remain prone to factual hallucinations, particularly in long-t

researcharxiv-cs-ai

Delta Score Matters! Spatial Adaptive Multi Guidance in Diffusion Models

arXiv:2604.26503v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in synthesizing complex static and temporal visuals, a breakthrough largely driven by Classifier-Free

safetyarxiv-cs-cv

DenseStep2M: A Scalable, Training-Free Pipeline for Dense Instructional Video Annotation

arXiv:2604.26565v1 Announce Type: new Abstract: Long-term video understanding requires interpreting complex temporal events and reasoning over procedural activities. While instructional video corpora,

DepthPilot: From Controllability to Interpretability in Colonoscopy Video Generation

arXiv:2604.26232v1 Announce Type: cross Abstract: Controllable medical video generation has achieved remarkable progress, but it still lacks interpretability, which requires the alignment of generated

Deterministic Legal Agents: A Canonical Primitive API for Auditable Reasoning over Temporal Knowledge Graphs

arXiv:2510.06002v3 Announce Type: replace Abstract: In high-stakes legal domains, retrieval must preserve not only semantic relevance, but also the hierarchy, temporality, and causal provenance of leg

DiffAnon: Diffusion-based Prosody Control for Voice Anonymization

arXiv:2604.26281v1 Announce Type: cross Abstract: To preserve or not to preserve prosody is a central question in voice anonymization. Prosody conveys meaning and affect, yet is tightly coupled with s

Differentially-Private Text Rewriting reshapes Linguistic Style

arXiv:2604.26656v1 Announce Type: new Abstract: Differential Privacy (DP) for text matured from disjointed word-level substitutions to contiguous sentence-level rewriting by leveraging the generative

researcharxiv-cs-cl

Distill-Belief: Closed-Loop Inverse Source Localization and Characterization in Physical Fields

arXiv:2604.26095v1 Announce Type: new Abstract: {Closed-loop inverse source localization and characterization (ISLC) requires a mobile agent to select measurements that localize sources and infer late

local-aiarxiv-cs-ai

Distribution-Free Stochastic Analysis and Robust Multilevel Vector Field Anomaly Detection

arXiv:2207.06229v3 Announce Type: replace-cross Abstract: Massive vector field datasets are common in multi-spectral optical and radar sensors, among many other emerging areas of application. We devel

Distributional Stability of Tangent-Linearized Gaussian Inference on Smooth Manifolds

arXiv:2602.19179v2 Announce Type: replace Abstract: Gaussian inference on smooth manifolds is central to robotics, but exact marginalization and conditioning are generally non-Gaussian and geometry-de

local-aiarxiv-cs-ro

Do Larger Models Really Win in Drug Discovery? A Benchmark Assessment of Model Scaling in AI-Driven Molecular Property and Activity Prediction

arXiv:2604.26498v1 Announce Type: new Abstract: The rapid growth of molecular foundation models and general-purpose large language models has encouraged a scale-centric view of artificial intelligence

Domain-Adapted Small Language Models for Reliable Clinical Triage

arXiv:2604.26766v1 Announce Type: cross Abstract: Accurate and consistent Emergency Severity Index (ESI) assignment remains a persistent challenge in emergency departments, where highly variable free-

researcharxiv-cs-ai

DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training

arXiv:2604.26256v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a critical paradigm for LLM post-training, yet the rollout phase -- accounting for 50--80% of total step time --

safetyarxiv-cs-lg

Applications

DP-CDA: An Algorithm for Enhanced Privacy Preservation in Dataset Synthesis Through Randomized Mixing

arXiv:2411.16121v3 Announce Type: replace-cross Abstract: In recent years, the growth of data across various sectors, including healthcare, security, finance, and education, has created significant op

applicationsarxiv-cs-lg

Agents

DreamProver: Evolving Transferable Lemma Libraries via a Wake-Sleep Theorem-Proving Agent

arXiv:2604.26311v1 Announce Type: new Abstract: We introduce DreamProver, an agentic framework that leverages a 'wake-sleep' program induction paradigm to discover reusable lemmas for formal theorem p

agentsarxiv-cs-ai

DSIPA: Detecting LLM-Generated Texts via Sentiment-Invariant Patterns Divergence Analysis

arXiv:2604.26328v1 Announce Type: cross Abstract: The rapid advancement of large language models (LLMs) presents new security challenges, particularly in detecting machine-generated text used for misi

DUAL-BLADE: Dual-Path NVMe-Direct KV-Cache Offloading for Edge LLM Inference

arXiv:2604.26557v1 Announce Type: cross Abstract: The increasing deployment of Large Language Model (LLM) inference on edge AI systems demands efficient execution under tight memory budgets. A key cha

local-aiarxiv-cs-ai

Dynamically Extensible and Retractable Robotic Leg Linkages for Multi-task Execution in Search and Rescue Scenarios

arXiv:2511.10816v3 Announce Type: replace Abstract: Search and rescue (SAR) robots are required to quickly traverse terrain and perform high-force rescue tasks, necessitating both terrain adaptability

researcharxiv-cs-ro

Edge AI for Automotive Vulnerable Road User Safety: Deployable Detection via Knowledge Distillation

arXiv:2604.26857v1 Announce Type: new Abstract: Deploying accurate object detection for Vulnerable Road User (VRU) safety on edge hardware requires balancing model capacity against computational const

local-aiarxiv-cs-cv

eDySec: A Deep Learning-based Explainable Dynamic Analysis Framework for Detecting Malicious Packages in PyPI Ecosystem

arXiv:2604.26219v1 Announce Type: cross Abstract: The security of open-source software repositories is increasingly threatened by next-gen software supply chain attacks. These attacks include multipha

Efficient and Interpretable Transformer for Counterfactual Fairness

arXiv:2604.26188v1 Announce Type: new Abstract: The growing reliance of machine learning models in high-stakes, highly regulated domains such as finance and insurance has created a growing tension bet

safetyarxiv-cs-lg

Tutorials

Efficient Traffic Forecasting on Large-Scale Road Network by Regularized Adaptive Graph Convolution

arXiv:2506.07179v2 Announce Type: replace-cross Abstract: Traffic prediction is a critical task in spatial-temporal forecasting with broad applications in travel planning and urban management. To mode

tutorialsarxiv-cs-ai

Efficient, VRAM-Constrained xLM Inference on Clients

arXiv:2604.26334v1 Announce Type: cross Abstract: To usher in the next round of client AI innovation, there is an urgent need to enable efficient, lossless inference of high-accuracy large language mo

Efficient Zero-Shot Inpainting with Decoupled Diffusion Guidance

arXiv:2512.18365v2 Announce Type: replace Abstract: Diffusion models have emerged as powerful priors for image editing tasks such as inpainting and local modification, where the objective is to genera

local-aiarxiv-cs-cv

Electricity price forecasting across Norway's five bidding zones in the post-crisis era

arXiv:2604.26634v1 Announce Type: new Abstract: Norway's electricity market is heavily dominated by hydropower, but the 2021--2022 energy crisis and stronger integration with Continental Europe have f

ELIQ: A Label-Free Framework for Quality Assessment of Evolving AI-Generated Images

arXiv:2602.03558v2 Announce Type: replace-cross Abstract: Generative text-to-image models are advancing at an unprecedented pace, continuously shifting the perceptual quality ceiling and rendering pre

Emergent Coordination in Multi-Agent Language Models

arXiv:2510.05174v4 Announce Type: replace-cross Abstract: When are multi-agent LLM systems merely a collection of individual agents versus an integrated collective with higher-order structure? We intr

local-aiarxiv-cs-ai

Agents

EmoTransCap: Dataset and Pipeline for Emotion Transition-Aware Speech Captioning in Discourses

arXiv:2604.26417v1 Announce Type: new Abstract: Emotion perception and adaptive expression are fundamental capabilities in human-agent interaction. While recent advances in speech emotion captioning (

agentsarxiv-cs-cl

EnerGS: Energy-Based Gaussian Splatting with Partial Geometric Priors

arXiv:2604.26238v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has been widely adopted for scene reconstruction, where training inherently constitutes a highly coupled and non-convex opt

researcharxiv-cs-cv

Enforcing Benign Trajectories: A Behavioral Firewall for Structured-Workflow AI Agents

arXiv:2604.26274v1 Announce Type: cross Abstract: Structured-workflow agents driven by large language models execute tool calls against sensitive external environments. We propose odename, a telemetry

Entropy Centroids as Intrinsic Rewards for Test-Time Scaling

arXiv:2604.26173v1 Announce Type: cross Abstract: An effective way to scale up test-time compute of large language models is to sample multiple responses and then select the best one, as in Grok Heavy

Evaluating Strategic Reasoning in Forecasting Agents

arXiv:2604.26106v1 Announce Type: new Abstract: Forecasting benchmarks produce accuracy leaderboards but little insight into why some forecasters are more accurate than others. We introduce Bench to t

Evaluating the Alignment Between GeoAI Explanations and Domain Knowledge in Satellite-Based Flood Mapping

arXiv:2604.26051v1 Announce Type: cross Abstract: The increasing number of satellites has improved the temporal resolution of Earth observation, making satellite-based flood mapping a promising approa