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Evaluating Prompting and Execution-Based Methods for Deterministic Computation in LLMs

arXiv:2605.03227v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated strong capabilities in natural language understanding and reasoning. However, their ability to perform ex

researcharxiv-cs-ai

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Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors

DGX agent

arXiv:2605.05034v1 Announce Type: new Abstract: Despite the strong performance of Convolutional Neural Networks (CNNs) in disease classification, their effectiveness often depends on access to large a

model-releasesarxiv-cs-cv

7 May 2026

From SWE-ZERO to SWE-HERO: Execution-free to Execution-based Fine-tuning for Software Engineering Agents

arXiv:2604.01496v2 Announce Type: replace-cross Abstract: We introduce SWE-ZERO to SWE-HERO, a two-stage SFT recipe that achieves state-of-the-art results on SWE-bench by distilling open-weight fronti

From Video-to-PDE: Data-Driven Discovery of Nonlinear Dye Plume Dynamics

arXiv:2605.04535v1 Announce Type: new Abstract: Inferring continuum models directly from video is hampered by two facts: the recorded field is uncalibrated image intensity rather than a physical state

Gaze4HRI: Zero-shot Benchmarking Gaze Estimation Neural-Networks for Human-Robot Interaction

arXiv:2605.04770v1 Announce Type: new Abstract: While zero-shot appearance-based 3D gaze estimation offers significant cost-efficiency by directly mapping RGB images to gaze vectors, its reliability i

GEM: Graph-Enhanced Mixture-of-Experts with ReAct Agents for Dialogue State Tracking

arXiv:2605.04449v1 Announce Type: new Abstract: Dialogue State Tracking (DST) requires precise extraction of structured information from multi-domain conversations, a task where Large Language Models

agentsarxiv-cs-cl

Geometric Evolution Graph Convolutional Networks: Enhancing Graph Representation Learning via Ricci Flow

arXiv:2603.26178v2 Announce Type: replace Abstract: We introduce the Geometric Evolution Graph Convolutional Network (GEGCN), a novel framework that enhances graph representation learning through expl

Applications

Geometry over Density: Few-Shot Cross-Domain OOD Detection

arXiv:2605.03410v2 Announce Type: new Abstract: Out-of-distribution (OOD) detection identifies test samples that fall outside a model's training distribution, a capability critical for safe deployment

applicationsarxiv-cs-ai

Gradient Scaling Effects in Adaptive Spectral PINNs for Stiff Nonlinear ODEs

arXiv:2605.04502v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) often struggle to train reliably on stiff and oscillatory dynamical systems due to poor optimization conditioni

How Long Does Infinite Width Last? Signal Propagation in Long-Range Linear Recurrences

arXiv:2605.05113v1 Announce Type: new Abstract: We study signal propagation in linear recurrent models at finite width. While existing signal propagation theory relies predominantly on the infinite-wi

HUGO-CS: A Hybrid-Labeled, Uncertainty-Aware, General-Purpose, Observational Dataset for Cold Spray

arXiv:2605.04257v1 Announce Type: new Abstract: Cold spraying is an increasingly common approach for repairing and manufacturing components due to its solid-state manufacturing capabilities. However,

Imagery Dataset for Remaining Useful Life Estimation of Synthetic Fibre Ropes

arXiv:2605.04262v1 Announce Type: new Abstract: Remaining useful life (RUL) estimation of synthetic fibre ropes (SFRs) is critical for safe operation in offshore-crane, wind turbine installation, and

Information Coordination as a Bridge: A Neuro-Symbolic Architecture for Reliable Autonomous Driving Scene Understanding

arXiv:2605.04475v1 Announce Type: new Abstract: Reliable autonomous driving requires scene understanding that is semantically consistent across heterogeneous sensors and verifiable at the reasoning st

KernelBench-X: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

arXiv:2605.04956v1 Announce Type: new Abstract: LLM-based Triton kernel generation has attracted significant interest, yet a fundamental empirical question remains unanswered: where does this capabili

Applications

Learning Time-Inhomogeneous Markov Dynamics in Financial Time Series via Neural Parameterization

arXiv:2605.04690v1 Announce Type: new Abstract: Modeling the dynamics of non-stationary stochastic systems requires balancing the representational power of deep learning with the mathematical transpar

applicationsarxiv-cs-lg

Learning to Orchestrate Agents in Natural Language with the Conductor

arXiv:2512.04388v5 Announce Type: replace Abstract: Powerful large language models (LLMs) from different providers have been expensively trained and finetuned to specialize across varying domains. In

agentsarxiv-cs-lg

Look Once, Beam Twice: Camera-Primed Real-Time Double-Directional mmWave Beam Management for Vehicular Connectivity

arXiv:2605.05071v1 Announce Type: cross Abstract: Millimeter-wave (mmWave) frequencies promise multi-gigabit connectivity for vehicle-to-everything (V2X) networks, but face challenges in terms of seve

safetyarxiv-cs-cv

Low-Cost Black-Box Detection of LLM Hallucinations via Dynamical System Prediction

arXiv:2605.05134v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently generate plausible but non-factual content, a phenomenon known as hallucination. While existing detection method

Magic-Informed Quantum Architecture Search

arXiv:2605.03932v1 Announce Type: cross Abstract: Nonstabilizerness, commonly referred to as magic, is a fundamental resource underpinning quantum advantage. In this paper, we propose a magic-informed

MOSAIC-Bench: Measuring Compositional Vulnerability Induction in Coding Agents

arXiv:2605.03952v1 Announce Type: cross Abstract: Coding agents often pass per-prompt safety review yet ship exploitable code when their tasks are decomposed into routine engineering tickets. The chal

NoisyCausal: A Benchmark for Evaluating Causal Reasoning Under Structured Noise

arXiv:2605.04313v1 Announce Type: new Abstract: Causal reasoning in natural language requires identifying relevant variables, understanding their interactions, and reasoning about effects and interven

Not Every Subject Should Stay: Machine Unlearning for Noisy Engagement Recognition

arXiv:2605.04713v1 Announce Type: new Abstract: Engagement recognition datasets are typically subject-indexed and often contain noisy, subjective supervision, making post-hoc dataset revision a practi

researcharxiv-cs-cv

On the Non-decoupling of Supervised Fine-tuning and Reinforcement Learning in Post-training

arXiv:2601.07389v2 Announce Type: replace Abstract: Post-training of large language models routinely interleaves supervised fine-tuning (SFT) with reinforcement learning (RL). These two methods have d

OpenSearch-VL: An Open Recipe for Frontier Multimodal Search Agents

arXiv:2605.05185v1 Announce Type: new Abstract: Deep search has become a crucial capability for frontier multimodal agents, enabling models to solve complex questions through active search, evidence v

agentsarxiv-cs-cv

Perceive, Verify and Understand Long Video: Multi-Granular Perception and Active Verification via Interactive Agents

arXiv:2509.24943v2 Announce Type: replace Abstract: Long videos, characterized by temporal complexity and sparse task-relevant information, pose significant reasoning challenges for AI systems. Althou

Provable Non-Convex Euclidean Distance Matrix Completion: Geometry, Reconstruction, and Robustness

arXiv:2508.00091v3 Announce Type: replace-cross Abstract: The problem of recovering the configuration of points from their partial pairwise distances, referred to as the Euclidean Distance Matrix Comp

Quantifying Trust: Financial Risk Management for Trustworthy AI Agents

arXiv:2604.03976v2 Announce Type: replace Abstract: Prior work on trustworthy AI emphasizes model-internal properties such as bias mitigation, adversarial robustness, and interpretability. As AI syste

safetyarxiv-cs-ai

Applications

RAMoEA-QA: Hierarchical Specialization for Robust Respiratory Audio Question Answering

arXiv:2603.06542v2 Announce Type: replace-cross Abstract: Conversational generative AI is increasingly explored in healthcare, where models must integrate heterogeneous patient signals and support div

applicationsarxiv-cs-ai

Real-Time Evaluation of Autonomous Systems under Adversarial Attacks

arXiv:2605.03491v1 Announce Type: new Abstract: Most evaluations of autonomous driving policies under adversarial conditions are conducted in simulation, due to cost efficiency and the absence of phys

Redefining AI Red Teaming in the Agentic Era: From Weeks to Hours

arXiv:2605.04019v1 Announce Type: new Abstract: AI systems are entering critical domains like healthcare, finance, and defense, yet remain vulnerable to adversarial attacks. While AI red teaming is a

Regime-Conditioned Evaluation in Multi-Context Bayesian Optimization

arXiv:2605.04895v1 Announce Type: new Abstract: Published transfer-BO comparisons often estimate an average treatment effect of acquisition choice over hidden regime variables, while practitioners nee

RemoteZero: Geospatial Reasoning with Zero Human Annotations

arXiv:2605.04451v1 Announce Type: new Abstract: Geospatial reasoning requires models to resolve complex spatial semantics and user intent into precise target locations for Earth observation. Recent pr

agentsarxiv-cs-cv

SpecPL: Disentangling Spectral Granularity for Prompt Learning

arXiv:2605.04504v1 Announce Type: cross Abstract: Existing prompt learning for VLMs exhibits a modality asymmetry, predominantly optimizing text tokens while still relying on frozen visual encoder as

StableI2I: Spotting Unintended Changes in Image-to-Image Transition

arXiv:2605.04453v1 Announce Type: new Abstract: In most real-world image-to-image (I2I) scenarios, existing evaluations primarily focus on instruction following and the perceptual quality or aesthetic

Storage Is Not Memory: A Retrieval-Centered Architecture for Agent Recall

arXiv:2605.04897v1 Announce Type: new Abstract: Extraction at ingestion is the wrong primitive for agent memory: content discarded before the query is known cannot be recovered at retrieval time. We p

Syntax- and Compilation-Preserving Evasion of LLM Vulnerability Detectors

arXiv:2602.00305v2 Announce Type: replace-cross Abstract: LLM-based vulnerability detectors are increasingly deployed in CI/CD security gating, yet their resilience to evasion under syntax- and compil

Tightly-Coupled Estimation and Guidance for Robust Low-Thrust Rendezvous via Adaptive Homotopy

model-releasesarxiv-cs-ro

arXiv:2605.04481v1 Announce Type: new Abstract: Minimum-fuel low-thrust rendezvous guidance yields bang-bang control structures highly sensitive to estimation errors, sensor anomalies, and solver regu

Transformed Latent Variable Multi-Output Gaussian Processes

arXiv:2605.05133v1 Announce Type: new Abstract: Multi-Output Gaussian Processes (MOGPs) provide a principled probabilistic framework for modelling correlated outputs but face scalability bottlenecks w

Local Ai

Uncovering Cross-Objective Interference in Multi-Objective Alignment

arXiv:2602.06869v2 Announce Type: replace Abstract: We study a persistent failure mode in multi-objective alignment for large language models (LLMs): training improves performance on only a subset of

local-aiarxiv-cs-cl

Local Ai

UniVer: A Unified Perspective for Multi-step and Multi-draft Speculative Decoding

arXiv:2605.04543v1 Announce Type: new Abstract: Speculative decoding accelerates Large Language Models via draft-then-verify, where verification can be framed as an Optimal Transport (OT) problem. Exi

local-aiarxiv-cs-cl

Why Expert Alignment Is Hard: Evidence from Subjective Evaluation

arXiv:2605.04972v1 Announce Type: new Abstract: Aligning large language models with expert judgment is especially difficult in subjective evaluation tasks, where experts may disagree, rely on tacit cr

safetyarxiv-cs-cl

A Low-Latency Fraud Detection Layer for Detecting Adversarial Interaction Patterns in LLM-Powered Agents

arXiv:2605.01143v1 Announce Type: new Abstract: Large Language Model (LLM)-powered agents demonstrate strong capabilities in autonomous task execution, tool use, and multi-step reasoning. However, the

agentsarxiv-cs-ai

AI Safety as Control of Irreversibility: A Systems Framework for Decision-Energy and Sovereignty Boundaries

arXiv:2605.01415v1 Announce Type: new Abstract: Recent AI systems compress the distance between capability growth and capability deployment. Earlier high-risk technologies were slowed by capital inten

An explainable hypothesis-driven approach to Drug-Induced Liver Injury with HADES

arXiv:2605.02669v1 Announce Type: new Abstract: Drug-induced liver injury (DILI) remains a leading cause of late-stage clinical trial attrition. However, existing computational predictors primarily re

AutoRAGTuner: A Declarative Framework for Automatic Optimization of RAG Pipelines

arXiv:2605.02967v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances LLMs, but performance is highly sensitive to complex architecture designs and hyper-parameter configurat

Bridging the Embodiment Gap: Disentangled Cross-Embodiment Video Editing

model-releasesarxiv-cs-ro

arXiv:2605.03637v1 Announce Type: new Abstract: Learning robotic manipulation from human videos is a promising solution to the data bottleneck in robotics, but the distribution shift between humans an

Claw-Eval: Towards Trustworthy Evaluation of Autonomous Agents

arXiv:2604.06132v2 Announce Type: replace Abstract: Large language models are increasingly deployed as autonomous agents for multi-step workflows in real-world software environments. However, existing

safetyarxiv-cs-ai

Coherent Hierarchical Multi-Label Learning to Defer for Medical Imaging

arXiv:2605.02734v1 Announce Type: new Abstract: Learning to Defer (L2D) enables a model to predict autonomously or defer to an expert, but prior work largely assumes flat label spaces. We study the fi

safetyarxiv-cs-ai