Search: “evaluation”

arXiv:2610.02869v1 Announce Type: cross Abstract: Autonomous penetration testing agents conduct multi-step attacks by continuously adapting their plans and actions to target responses. As a common def

agentsarxiv-cs-ai

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Research

AIBL: Augmented Instance-Based Learning with Structured Memory and Neural Embeddings

DGX agent

arXiv:2610.03413v1 Announce Type: new Abstract: Sequential learning systems often make decisions from accumulated experience while receiving high-dimensional inputs whose distribution may change over

researcharxiv-cs-lg

5 Oct 2026

An AI-Based Multi-Stage Approach for Androgenetic Alopecia Assessment from Low-Magnification Scalp Images

arXiv:2610.02421v1 Announce Type: new Abstract: Androgenetic alopecia (AGA) is characterized by patterned follicular miniaturization, increased single-hair follicular units, and altered hair-shaft dia

An automated pipeline for standardised speech-unit annotation in spontaneous dialogue

model-releasesarxiv-cs-cl

arXiv:2610.03078v1 Announce Type: new Abstract: Quantifying conversational dynamics requires reliable identification of interactional units and their temporal boundaries, but speech activity alone doe

Asymptotic Performance of Time-Varying Bayesian Optimization

arXiv:2505.13012v3 Announce Type: replace-cross Abstract: Time-Varying Bayesian Optimization (TVBO) is the go-to framework for optimizing a time-varying black-box objective function that may be noisy

Applications

Automated Feature Engineering, AutoML, and Decision-Focused Learning for Improved Energy Consumption Forecasting

arXiv:2609.35013v2 Announce Type: replace Abstract: The rising cost and demand for energy, together with environmental sustainability goals, create major challenges for energy management. Energy Consu

applicationsarxiv-cs-ai

Automatic register identification for the open web using multilingual deep learning

arXiv:2406.19892v5 Announce Type: replace Abstract: This article presents multilingual deep learning models for identifying web registers -- text varieties such as news reports and discussion forums -

Agents

Autonomous mobile robot operations logistics: a dataset of jobs, dispatch events and robot states

arXiv:2610.02428v1 Announce Type: new Abstract: Autonomous mobile robots (AMRs) increasingly perform material transport in production logistics, where their operation is governed by job generation, di

agentsarxiv-cs-ro

AVL-JEPA: Preventing Causal Dynamics Information Collapse In Joint Embedding Predictive Architecture World Models

arXiv:2610.03587v1 Announce Type: new Abstract: Joint embedding predictive architectures (JEPAs) predict future latent representations without reconstructing observations, enabling world models to foc

safetyarxiv-cs-ro

AvoKV-E: Payload-Aware KV Cache Eviction for Long Reasoning

arXiv:2610.03007v1 Announce Type: cross Abstract: Long-output reasoning shifts the KV-cache bottleneck from the fixed prompt to the generated trace. Existing reasoning-cache eviction methods largely t

safetyarxiv-cs-ai

Awomo-SimDataEngine: Agentic Simulation-ReadyWorld Generation

arXiv:2610.02274v1 Announce Type: new Abstract: Generating useful robot-training data requires more than visually plausiblescenes: objects must support interaction, placements must remain physicallyva

safetyarxiv-cs-ro

BaCP: Backbone Contrastive Pruning for Preserving Representations in Extremely Sparse Neural Networks

arXiv:2610.02524v1 Announce Type: new Abstract: Unstructured pruning at extreme sparsity often suffers from representational collapse, causing sharp drops in accuracy. To address this, we study Backbo

Applications

Becoming Suspicious Across Borders: Algorithmic Extraterritoriality and AI-Driven Financial Surveillance

arXiv:2610.03425v1 Announce Type: new Abstract: Suspicion is an important, yet elusive concept in anti-money laundering and counter-terrorist financing (AML/CFT), which allows for intervention below t

applicationsarxiv-cs-ai

Below what training size do deep tabular generators stop beating trivial baselines? A preregistered benchmark on a size ladder of clinical and standard datasets

arXiv:2610.03500v1 Announce Type: new Abstract: Deep tabular generative models are benchmarked on datasets with tens of thousands of rows; clinical datasets have hundreds. We preregistered and ran a s

Agents

Beyond Predefined Sinks: Security-Aware Dependency Analysis for LLM Agents

arXiv:2610.03014v1 Announce Type: cross Abstract: Large language model (LLM)-based agents increasingly connect model-generated decisions to security-sensitive software capabilities such as command exe

agentsarxiv-cs-ai

Bifidelity Karhunen-Loeve Expansion Surrogate with Active Learning for Random Fields

arXiv:2511.03756v2 Announce Type: replace-cross Abstract: We present a bifidelity Karhunen--Loeve expansion (KLE) surrogate model for field-valued quantities of interest (QoIs) under uncertain inputs.

Local Ai

Bridging Frontier Reasoning and Robot Execution: From Autonomous Demonstration Generation to Dense Language Supervision

arXiv:2610.03615v1 Announce Type: new Abstract: Recent advances in frontier models enable robot manipulation from only a few demonstrations, but high inference latency limits their use for real-time r

local-aiarxiv-cs-ro

Budgeted Cache Repair for Cross-Context KV-Cache Reuse

arXiv:2610.02233v1 Announce Type: cross Abstract: Cross-context KV-cache reuse predicts a shared segment's keys and values under a new prefix instead of recomputing them, and has been reported to do s

Applications

Building Interpretable Feature Representations for Resume-Vacancy Matching by Distilling Production LLM Signals

arXiv:2610.03112v1 Announce Type: new Abstract: Matching candidates to vacancies is central to recruitment, and a recruiter needs to see why a candidate fits, not only a single opaque relevance score.

applicationsarxiv-cs-cl

CalCErt: Bin-wise Certification of Confidence Calibration in Medical Image Classification

arXiv:2610.03142v1 Announce Type: new Abstract: Deep neural networks remain vulnerable to adversarial perturbations, which can distort not only predictions but also confidence scores, undermining unce

Cephalonauts One: A deep fMRI dataset for decoding naturalistic speech in the human brain

arXiv:2610.03558v1 Announce Type: cross Abstract: Cephalonauts One is a whole-brain 3 Tesla (3T) functional magnetic resonance imaging (fMRI) dataset recorded while subjects listened to audio podcasts

ChronoSpike: An Adaptive Spiking Graph Neural Network for Dynamic Graphs

arXiv:2602.01124v4 Announce Type: replace Abstract: Dynamic graph representation learning requires capturing both structural relations and temporal evolution, yet existing approaches face a core trade

Co-design Gym: A Unified Benchmark for Embodiment-Policy Co-optimization

arXiv:2610.02366v1 Announce Type: new Abstract: Finding an optimal behaviour policy within a given environment is a widely studied problem in domains as diverse as games, robotics, energy infrastructu

CoLMbo-SV: A Grounded Language Model for Explainable Speaker Verification

arXiv:2609.33212v2 Announce Type: replace Abstract: Speaker verification systems achieve high accuracy but provide little account of the acoustic evidence behind their judgments. Making these systems

CoMemNet: A Continual Memory Network with Drift-Aware Sampling for Traffic Prediction

arXiv:2605.05738v2 Announce Type: replace-cross Abstract: Traffic sensor networks evolve as sensors are added and traffic distributions change, whereas most forecasting models assume a fixed node set

Conditional Capacity and Routing in Mixture-of-Experts Particle Transformers

arXiv:2610.02701v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models can increase parameter capacity without proportionally increasing active computation, but it is unclear how this trade-o

Confidence-Controlled XAI Auditing for Pedestrian Detection under Domain Shift

arXiv:2610.02364v1 Announce Type: new Abstract: Explainability is increasingly required for perception models in intelligent vehicles, yet whether explanations remain faithful under driving domain shi

safetyarxiv-cs-cv

Consecutive Posterior Fusion for Diffusive Recovery of Unobservable Image Structures

arXiv:2610.03261v1 Announce Type: cross Abstract: Solving severely ill-posed imaging inverse problems requires recovering image structures that are unobservable or weakly constrained by the measuremen

Local Ai

Corrupted but Correct: Why Vision-Language Models Lie to Themselves Internally

arXiv:2610.03445v1 Announce Type: cross Abstract: A targeted adversarial perturbation can drive a vision-language model's (VLM's) teacher-forced training loss for a fixed target caption to near zero,

local-aiarxiv-cs-ai

Counterexample Generation via Per-Theorem Symbolic Verifiers: When Imitation Hurts and Reinforcement Repairs

arXiv:2610.02444v1 Announce Type: cross Abstract: Large language models often solve a theorem forward yet fail to disprove a closely related false one: a falsification gap that supervised fine-tuning

CRISP: A Framework for Clause-Reconstructed Interpretable NeuroSymbolic Propositions

arXiv:2610.02431v1 Announce Type: new Abstract: Deep neural networks achieve high accuracy through layered numerical transformations, yet their decisions remain difficult to audit because decision evi

CSIR: Contextually and Socially Informed Robots for Efficient Person Goal Navigation

model-releasesarxiv-cs-ro

arXiv:2610.02750v1 Announce Type: new Abstract: We address the Person Goal Navigation (PersonNav) problem, enabling robots to search for people under realistic constraints on information accessibility

Deep learning-based prediction of time-resolved adhesive forces in viscoelastic Hertzian contacts

arXiv:2607.19060v2 Announce Type: replace-cross Abstract: Fast prediction of the response of adhesive soft viscoelastic contacts represents a current challenge in soft robotics and for gripping and ma

DeepStratNet: A Context-Aware Coordinate Regression Framework for Seismic Horizon Tracking under Sparse Labels

arXiv:2610.02494v1 Announce Type: new Abstract: Automatic horizon tracking is a foundational task in 3D seismic interpretation. Most existing deep learning approaches formulate it as dense semantic se

Depth as Time in One-Step Generative Models

arXiv:2610.03626v1 Announce Type: new Abstract: The recent wave of one-step generative models, which compress the multi-step trajectory of diffusion via either distillation or learned flow maps, has r

Designing the Future of User Feedback for Generative AI

arXiv:2610.02631v1 Announce Type: new Abstract: Post-deployment feedback from users can be a cost-effective, scalable, and representative means to monitor and improve generative AI systems and feature

Detect and Suppress: A Mechanistic Defense against Adversarial Patches in VLA Models

arXiv:2610.03498v1 Announce Type: cross Abstract: Adversarial patches can disrupt Vision-Language-Action (VLA) models by manipulating visual observations, leading to failures in robot control. However

safetyarxiv-cs-ai

Differentiable Koopman Operator for Contrastive Learning on Dynamic Graphs

arXiv:2610.02990v1 Announce Type: new Abstract: Real-world interaction networks are inherently dynamic: edges form and dissolve as node behavior shifts over time. Most snapshot-based contrastive metho

safetyarxiv-cs-lg

DISSOLVR: An Interpretable and Fast Framework for Aqueous and Organic Solubility Prediction

arXiv:2610.02574v1 Announce Type: new Abstract: High-fidelity solubility prediction is fundamental to pharmaceutical development and environmental partitioning, where accurate modeling must couple mol

DNAlign: Dynamic Null-Space Safe Alignment for LLMs

arXiv:2610.02844v1 Announce Type: new Abstract: Ensuring the safe and reliable deployment of large language models (LLMs) remains a fundamental challenge. Existing safety alignment approaches either i

safetyarxiv-cs-ai

Does Every User Need a Private LoRA? Decoupling Personalization from Per-User Adaptation

arXiv:2610.02353v1 Announce Type: cross Abstract: Personalized large language models often require a complete adaptation state for each user. However, this paradigm scales poorly as the user populatio

Efficient Reasoning Training Does Not Always Harm CoT Faithfulness and Monitorability

arXiv:2610.03509v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning allows humans to inspect how large language models reach their answers, and oversee model behaviour. This reasoning com

Emergent Structure in the Marginal Attention Space of Language Models

arXiv:2610.03109v1 Announce Type: new Abstract: While representation similarity across independently trained language models is well-documented, how internal mechanics such as attention behave across

ENCORE: Exact Non-equilibrium COntrol with Replica Exchange for Diffusion Generation

arXiv:2610.02538v1 Announce Type: cross Abstract: Inference-time control steers a pretrained generative model towards a target distribution without retraining. We study tilted targets pi_0propto G_0,p

EpiWorld: Grounding LLM Policy Agents in Epidemiological World Models

arXiv:2610.02744v1 Announce Type: new Abstract: Epidemic intervention policies are textual artefacts that human decision-makers interpret, justify, and revise through natural language, making large la

safetyarxiv-cs-cl

Event-guided Neural Video Compression

arXiv:2610.02265v1 Announce Type: cross Abstract: Neural video codecs derive motion and temporal contexts mainly from RGB frames, leaving room for cross-modal guidance from complementary temporal obse

Local Ai

EviDent-CBCT: Evidence-Bottlenecked Report Generation from Dental CBCT under Non-Exhaustive Report Supervision

arXiv:2610.02375v1 Announce Type: cross Abstract: Dento-maxillofacial cone-beam CT (CBCT) reports may contain dozens of tooth-specific, anatomical, and spatial findings from a single 3D scan. Learning

local-aiarxiv-cs-ai

Exploring the Trade-Off Between Structured Pruning and Fault Tolerance in Deep Neural Networks for Space Applications

arXiv:2610.03117v1 Announce Type: new Abstract: Deep Neural Networks (DNNs) inherently exhibit a degree of robustness to bit-level faults due to their distributed representation of information. As a m