Search: “models”

Contrastive Regularization for Accent-Robust ASR

arXiv:2605.03297v1 Announce Type: cross Abstract: ASR systems based on self-supervised acoustic pretraining and CTC fine-tuning achieve strong performance on native speech but remain sensitive to acce

Safety

Disentangling Intent from Role: Adversarial Self-Play for Persona-Invariant Safety Alignment

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DGX agent

arXiv:2605.01899v1 Announce Type: new Abstract: The growing capabilities of large language models (LLMs) have driven their widespread deployment across diverse domains, even in potentially high-risk s

safetyarxiv-cs-ai

6 May 2026

Disentangling Shared and Task-Specific Representations from Multi-Modal Clinical Data

arXiv:2605.03570v1 Announce Type: new Abstract: Real-world clinical data is inherently multimodal, providing complementary evidence that mirrors the practical necessity of jointly assessing multiple r

EO-Gym: A Multimodal, Interactive Environment for Earth Observation Agents

arXiv:2605.01250v1 Announce Type: new Abstract: Earth Observation (EO) analysis is inherently interactive: resolving uncertainty often requires expanding the region of interest, retrieving historical

eOptShrinkQ: Near-Lossless KV Cache Compression Through Optimal Spectral Denoising and Quantization

arXiv:2605.02905v1 Announce Type: new Abstract: We show that the key-value (KV) cache in transformer attention heads admits a natural decomposition into a low-rank shared context component and a full-

Tutorials

Flow Sampling: Learning to Sample from Unnormalized Densities via Denoising Conditional Processes

arXiv:2605.03984v1 Announce Type: new Abstract: Sampling from unnormalized densities is analogous to the generative modeling problem, but the target distribution is defined by a known energy function

tutorialsarxiv-cs-lg

From prompting to evidence-based translation: A RAG+prompt system for Japanese-Chinese translation and its pedagogical potential

arXiv:2605.03387v1 Announce Type: new Abstract: Large language models perform well on high-resource pairs but are less reliable for Japanese-Chinese sentences containing noun-modifying clause construc

researcharxiv-cs-cl

Gated Subspace Inference for Transformer Acceleration

arXiv:2605.03109v1 Announce Type: new Abstract: A method is presented for accelerating inference in transformer language models by exploiting the low effective rank of the token activation manifold at

Safety

HiMAC: Hierarchical Macro-Micro Learning for Long-Horizon LLM Agents

arXiv:2603.00977v2 Announce Type: replace-cross Abstract: Large language model (LLM) agents have recently demonstrated strong capabilities in interactive decision-making, yet they remain fundamentally

safetyarxiv-cs-lg

HistCAD: A Constraint-Aware Parametric History-Based CAD Representation, Dataset, and Benchmark with Industrial Complexity

arXiv:2602.19171v2 Announce Type: replace-cross Abstract: Parametric CAD sequences are reusable because dimensional and geometric constraints govern how parameter changes propagate. Existing CAD gener

Learning to Theorize the World from Observation

arXiv:2605.03413v1 Announce Type: new Abstract: What does it mean to understand the world? Contemporary world models often operationalize understanding as accurate future prediction in latent or obser

Local Ai

Local Truncation Error-Guided Neural ODEs for Large Scale Traffic Forecasting

arXiv:2605.03386v1 Announce Type: new Abstract: Spatiotemporal forecasting in physical systems, such as large-scale traffic networks, requires modeling a dual dynamic: continuous macroscopic rhythms a

local-aiarxiv-cs-lg

MAP-Law: Coverage-Driven Retrieval Control for Multi-Turn Legal Consultation

arXiv:2605.01486v1 Announce Type: new Abstract: Legal consultation is a high-stakes, knowledge-intensive task that requires agents to identify relevant legal issues, retrieve authoritative support, an

Safety

Memorization In Stable Diffusion Is Unexpectedly Driven by CLIP Embeddings

arXiv:2605.02908v1 Announce Type: new Abstract: Understanding how textual embeddings contribute to memorization in text-to-image diffusion models is crucial for both interpretability and safety. This

safetyarxiv-cs-cv

Mitigating the reconstruction-detection trade-off in VAE-based unsupervised anomaly detection

arXiv:2605.02918v1 Announce Type: new Abstract: Variational autoencoders are widely used for unsupervised anomaly detection. Model selection however remains an open-question: to remain fully unsupervi

Multimodal Learning on Low-Quality Data with Conformal Predictive Self-Calibration

model-releasesarxiv-cs-cv

arXiv:2605.03820v1 Announce Type: new Abstract: Multimodal learning often grapples with the challenge of low-quality data, which predominantly manifests as two facets: modality imbalance and noisy cor

New Bounds for Zarankiewicz Numbers via Reinforced LLM Evolutionary Search

arXiv:2605.01120v1 Announce Type: new Abstract: The Zarankiewicz number extbf{Z}(m, n, s, t) is the maximum number of edges in a bipartite graph G_{m, n} such that there is no complete K_{s, t} bipart

On the Privacy of LLMs: An Ablation Study

arXiv:2605.02255v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in interactive and retrieval-augmented settings, raising significant privacy concerns. While at

researcharxiv-cs-ai

On the Spectral Structure and Objective Equivalence of Orthogonal Multilabel Fisher Discriminants

arXiv:2605.03283v1 Announce Type: cross Abstract: We provide a unified theoretical analysis of Linear Discriminant Analysis with simultaneous multilabel scatter matrix formulations and Stiefel orthogo

Hardware

One Sequence to Segment Them All: Efficient Data Augmentation for CT and MRI Cross-Domain 3D Spine Segmentation

arXiv:2605.03098v1 Announce Type: new Abstract: Deep learning-based medical image segmentation is increasingly used to support clinical diagnosis and develop new treatment strategies. However, model p

hardwarearxiv-cs-cv

Agents

OpenSeeker-v2: Pushing the Limits of Search Agents with Informative and High-Difficulty Trajectories

arXiv:2605.04036v1 Announce Type: cross Abstract: Deep search capabilities have become an indispensable competency for frontier Large Language Model (LLM) agents, yet their development remains dominat

agentsarxiv-cs-cl

Applications

PAMNet: Cycle-aware Phase-Amplitude Modulation Network for Multivariate Time Series Forecasting

arXiv:2605.02938v1 Announce Type: new Abstract: Reliable periodic patterns serve as a fundamental basis for accurate multivariate time series forecasting. However, existing methods either implicitly e

applicationsarxiv-cs-lg

PriorNet: Prior-Guided Engagement Estimation from Face Video

model-releasesarxiv-cs-cv

arXiv:2605.03615v1 Announce Type: new Abstract: Engagement estimation from face video remains challenging because facial evidence is often incomplete, labeled data are limited, and engagement annotati

Rethinking Reasoning-Intensive Retrieval: Evaluating and Advancing Retrievers in Agentic Search Systems

arXiv:2605.04018v1 Announce Type: new Abstract: Reasoning-intensive retrieval aims to surface evidence that supports downstream reasoning rather than merely matching topical similarity. This capabilit

Robust Language Identification for Romansh Varieties

arXiv:2603.15969v2 Announce Type: replace Abstract: The Romansh language has several regional varieties, called idioms, which sometimes have limited mutual intelligibility. Despite this linguistic div

SAM-NER: Semantic Archetype Mediation for Zero-Shot Named Entity Recognition

arXiv:2605.03706v1 Announce Type: new Abstract: Zero-shot Named Entity Recognition (ZS-NER) remains brittle under domain and schema shifts, where unseen label definitions often misalign with a large l

Soft Tournament Equilibrium

arXiv:2604.04328v3 Announce Type: replace-cross Abstract: The evaluation of general-purpose artificial agents, particularly those based on LLMs, presents a significant challenge due to the non-transit

Spatiotemporal Convolutions on EEG signal -- A Representation Learning Perspective on Efficient and Explainable EEG Classification with Convolutional Neural Nets

arXiv:2605.03874v1 Announce Type: new Abstract: Classification of EEG signals using shallow Convolutional Neural Networks (CNNs) is a prevalent and successful approach across a variety of fields. Most

Applications

Synthetic Data Generation for Long-Tail Medical Image Classification: A Case Study in Skin Lesions

arXiv:2605.03221v1 Announce Type: new Abstract: Long-tailed class distributions are pervasive in multi-class medical datasets and pose significant challenges for deep learning models which typically u

applicationsarxiv-cs-cv

The Cost of Consensus: Isolated Self-Correction Prevails Over Unguided Homogeneous Multi-Agent Debate

arXiv:2605.00914v1 Announce Type: cross Abstract: Multi-agent debate, where teams of LLMs iteratively exchange rationales and vote on answers, is widely deployed under the assumption that peer review

Local Ai

The Detector Teaches Itself: Lightweight Self-Supervised Adaptation for Open-Vocabulary Object Detection

arXiv:2605.03642v1 Announce Type: new Abstract: Open-vocabulary object detection aims to recognize objects from an open set of categories, which leverages vision-language models (VLMs) pre-trained on

local-aiarxiv-cs-cv

Towards Agentic Runtime Healing

arXiv:2408.01055v2 Announce Type: replace-cross Abstract: Self-healing systems have long been a focus of research, aiming to enable software to recover from unexpected runtime errors without human int

Towards Multi-Agent Autonomous Reasoning in Hydrodynamics

arXiv:2605.01102v1 Announce Type: new Abstract: Single-agent systems (SAS) have become the default pattern for LLM-driven scientific workflows, but routing planning, tool use, and synthesis through a

When Stress Becomes Signal: Detecting Antifragility-Compatible Regimes in Multi-Agent LLM Systems

arXiv:2605.02463v1 Announce Type: cross Abstract: Multi-agent LLM systems are increasingly used to solve complex tasks through decomposition, debate, specialization, and ensemble reasoning. However, t

Workspace-Bench 1.0: Benchmarking AI Agents on Workspace Tasks with Large-Scale File Dependencies

arXiv:2605.03596v1 Announce Type: cross Abstract: Workspace learning requires AI agents to identify, reason over, exploit, and update explicit and implicit dependencies among heterogeneous files in a

A Hybrid Windkessel-Neural Approach for Improved Noninvasive Blood Pressure Monitoring

arXiv:2605.00858v1 Announce Type: cross Abstract: Owing to the recent advancements in wearable devices for health care, the importance of BP estimation without cuffs increases. Cuff technologies are i

A Novel Preprocessing-Driven Approach to Remaining Useful Life (RUL) Prediction Using Temporal Convolutional Networks (TCN)

arXiv:2605.02507v1 Announce Type: new Abstract: Accurate prediction of Remaining Useful Life (RUL) in aero-engines is vital for predictive maintenance, improved operational reliability, and reduced li

Act2See: Emergent Active Visual Perception for Video Reasoning

arXiv:2605.01657v1 Announce Type: new Abstract: Vision-Language Models (VLMs) typically rely on static initial frames for video reasoning, restricting their ability to incorporate essential dynamic in

researcharxiv-cs-cv

AdamO: A Collapse-Suppressed Optimizer for Offline RL

arXiv:2605.01968v1 Announce Type: new Abstract: Offline reinforcement learning (RL) can fail spectacularly when bootstrapped temporal-difference (TD) updates amplify their own errors, driving the crit

Agents

AgentXRay: White-Boxing Agentic Systems via Workflow Reconstruction

arXiv:2602.05353v3 Announce Type: replace-cross Abstract: Large Language Models have shown strong capabilities in complex problem solving, yet many agentic systems remain difficult to interpret and co

agentsarxiv-cs-cl

An ALE-Consistent Graph Neural Operator-Transformer Framework for Fluid-Structure Interaction

arXiv:2605.00937v1 Announce Type: cross Abstract: We propose an arbitrary Lagrangian-Eulerian (ALE)-consistent machine learning framework for long-term fluid-structure interaction (FSI) prediction on

Tutorials

An Information-theoretic Propagation Denoising and Fusion Framework for Fake News Detection

arXiv:2605.02259v1 Announce Type: new Abstract: Incomplete propagation data significantly hinders robust fake news detection. Recent approaches leverage large language models to simulate missing user

tutorialsarxiv-cs-cl

AnchorD: Metric Grounding of Monocular Depth Using Factor Graphs

model-releasesarxiv-cs-cv

arXiv:2605.02667v1 Announce Type: cross Abstract: Dense and accurate depth estimation is essential for robotic manipulation, grasping, and navigation, yet currently available depth sensors are prone t

ARA: Agentic Reproducibility Assessment For Scalable Support Of Scientific Peer-Review

arXiv:2605.02651v1 Announce Type: cross Abstract: Scientific peer review increasingly struggles to assess reproducibility at the scale and complexity of modern research output. Evaluating reproducibil

Arithmetic in the Wild: Llama uses Base-10 Addition to Reason About Cyclic Concepts

arXiv:2605.01148v1 Announce Type: cross Abstract: Does structure in representations imply structure in computation? We study how Llama-3.1-8B reasons over cyclic concepts (e.g., 'what month is six mon

Agents

AutoFocus: Uncertainty-Aware Active Visual Search for GUI Grounding

arXiv:2605.02630v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have enabled autonomous GUI agents that translate natural language instructions into executable screen coordinates. Howeve

agentsarxiv-cs-cv

Benchmarking local Hebbian learning rules for memory storage and prototype extraction

arXiv:2605.01074v1 Announce Type: cross Abstract: Associative memory or content-addressable memory is an important component function in computer science and information processing, and at the same ti

Benchmarking Single-Pose Docking, Consensus Rescoring, and Supervised ML on the LIT-PCBA Library: A Critical Evaluation of DiffDock, AutoDock-GPU, GNINA, and DiffDock-NMDN

arXiv:2605.01681v1 Announce Type: new Abstract: Virtual screening performance depends heavily on the chosen docking and scoring methods. Recent AI-based tools such as DiffDock and NMDN have reported s