Search: “evaluation”

The Ball and the Box: Two Geometries of Computation in Superposition

arXiv:2610.11744v1 Announce Type: new Abstract: Neural representations can encode more features than they have dimensions, a phenomenon known as superposition. We study the dimension needed to compute

researcharxiv-cs-lg

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Local Ai

The Harness as the Only Mutable Surface: Compliance-Bounded Self-Evolution of LLM Agents in Credit Pipelines, with a Measured Admission Gate

DGX agent

arXiv:2610.10629v1 Announce Type: new Abstract: Self-improving LLM agents can adapt a credit pipeline to a changed rule, but an agent that rewrites itself destroys the artefact a supervisor reviews: a

local-aiarxiv-cs-ai

9 Oct 2026

The Kinetics Observer: A Tightly Coupled Estimator for Legged Robots

arXiv:2406.13267v2 Announce Type: replace Abstract: This paper presents the Kinetics Observer, a novel proprioceptive state estimator for legged robots designed to provide the feedback required for ve

researcharxiv-cs-ro

The optimal information complexity of VC learning

arXiv:2610.10600v1 Announce Type: cross Abstract: Steinke and Zakynthinou(2020) introduces the Conditional Mutual Information (CMI) framework of analyzing the information complexity of learning algori

researcharxiv-cs-lg

Toward Optimal Regret in Adversarial MDPs with Stochastic Hard Constraints

arXiv:2610.12153v1 Announce Type: new Abstract: We study episodic constrained Markov decision processes with adversarial losses under stochastic hard constraints. Specifically, starting from a known s

Towards Path-Creative Navigation: Robot Navigation through Embodied Interaction

arXiv:2610.11072v1 Announce Type: new Abstract: Autonomous navigation in cluttered and constrained environments typically assumes a fixed environment and searches only for paths within existing free s

agentsarxiv-cs-ro

TRACE: A Governance Framework for Measuring Explainability Debt in Production AI Systems

arXiv:2610.10957v1 Announce Type: cross Abstract: Production AI systems deployed in high-stakes domains accumulate a governance liability that existing monitoring frameworks fail to detect: the progre

safetyarxiv-cs-ai

Hardware

Traceable World State: A Provenance-Aware State Representation and Deterministic Replay Framework for Robotic Systems

arXiv:2610.12033v1 Announce Type: cross Abstract: Robotic systems operating over extended tasks must maintain a world state assembled from observations arriving at different times, with varying confid

hardwarearxiv-cs-ai

Local Ai

TraceRelay: Attention-Aligned Recurrence over Rolling Traces

arXiv:2610.11743v1 Announce Type: new Abstract: We present TraceRelay, an attention-aligned recurrent architecture that distributes persistent representations over a rolling sequence of low-dimensiona

local-aiarxiv-cs-lg

Tracing the Thoughts of a Coding Agent Playing ARC-AGI-3: Lessons for Continual Learning

arXiv:2610.11450v1 Announce Type: new Abstract: We study how a coding agent learns across a sequence of abstract reasoning tasks. The agent runs on a frozen foundation model inside a fixed harness and

agentsarxiv-cs-ai

Applications

Trust, Don't Trust, or Flip: Robust Preference-Based Reinforcement Learning with Multi-Expert Feedback

arXiv:2601.18751v2 Announce Type: replace-cross Abstract: Preference-based reinforcement learning (PBRL) offers a promising alternative to explicit reward engineering by learning from pairwise traject

applicationsarxiv-cs-ai

Uncertainty-Aware Optimization for Physics-Aware Highway Trajectory Prediction

arXiv:2610.11580v1 Announce Type: new Abstract: Accurate trajectory forecasting and well-defined predictive uncertainty are crucial for reliable, safety-critical applications such as autonomous drivin

Using Weisfeiler-Leman Features for Algorithm Selection in Constraint Optimisation

arXiv:2610.12119v1 Announce Type: cross Abstract: Algorithm Selection is essential for efficient Constraint Programming. Over the years, many algorithm selectors based on machine learning methods have

researcharxiv-cs-ai

Verdict Without the Rule: Diagnosing and Auditing Regulatory Rule Sensitivity in LLM Compliance Systems

arXiv:2610.12313v1 Announce Type: new Abstract: Large language model compliance systems are deployed on the assumption that a verdict depends on the regulatory rule it is given. We test this directly

safetyarxiv-cs-ai

VGGTWorld-VLA: Intent-Conditioned 3D World Evolution for Autonomous Driving

arXiv:2610.11161v1 Announce Type: new Abstract: VGGT provides a strong foundation for geometry-centric world models by recovering unified 3D scene geometry from visual observations. Although recent ex

agentsarxiv-cs-cv

Visible Reasoning Is Not a Universal Optimizer: Persona- and Thinking-Dependent Effects in Analytics Code Generation

arXiv:2610.10639v1 Announce Type: cross Abstract: Visible Chain-of-Thought (CoT) is often treated as a broadly useful reasoning instruction, yet analytics code generation combines natural-language amb

Walking on Roofs: Exploring the Potential of Walking Robots for Construction Work on Roofs

arXiv:2610.12272v1 Announce Type: new Abstract: This paper investigates the feasibility of deploying quadruped walking robots for the automation of work in roof environments. While quadrupeds have dem

safetyarxiv-cs-ro

Web automation with Ollama on a 4 GB GPU: Qwen 3.5 4B plans, a heuristic clicks, and saved tasks replay with no model at all

I've been building ANCHOR, a web automation agent that runs entirely on Ollama. You describe a task in plain language ('Register Maria Silva, IT department, contractor, and save'), point it at a site,

model-releasesr-ollama

What 30,000 Hours of Ego-centric Video Does Not Teach

arXiv:2610.12464v1 Announce Type: new Abstract: World models offer a promising alternative to physics-based simulators, yet remain far from practical deployment. We ask how far scaling ego-centric hum

When Can You Prune Your Network? A Study of Intermediate Neurons in Multilingual Speech Parsing

arXiv:2610.11520v1 Announce Type: new Abstract: End-to-end speech parsing, a task recently proposed, consists in predicting both the transcription and the syntactic tree for a spoken utterance. Existi

researcharxiv-cs-cl

When Citations Mislead? A Claim-Level Benchmark for Legal Hallucination Detection

arXiv:2610.10971v1 Announce Type: cross Abstract: Large language models are increasingly used in legal research and drafting, but they can still produce claims that sound convincing without being supp

When Interfaces Speak: Data-Aware Generative UI Harness for Active Interaction

arXiv:2610.11123v1 Announce Type: new Abstract: Most human-agent interaction today remains text-based. Natural language can impose cognitive overload, ambiguity, information chaos, and slow input for

Tutorials

Whose Ground Truth? Embracing Ambiguity in Human-Centered AI

arXiv:2610.10805v1 Announce Type: new Abstract: As AI systems increasingly interact with people and make decisions about them, understanding human interpretations becomes an important part of developi

tutorialsarxiv-cs-ai

Workerville: Towards an Organizational Behavior Account of Agent Safety

arXiv:2610.11561v1 Announce Type: new Abstract: LLM-based agents now interact with their environments continuously, shaped by such organizational channels as user instructions, peer messages, and long

WorldAlign: Decoupled 4D Reward for World-Consistent Video Generation

arXiv:2610.12382v1 Announce Type: new Abstract: Faithful visual world simulation requires generated videos to maintain 4D world consistency, encompassing both static and dynamic consistency. Static co

safetyarxiv-cs-cv

WOVEN: Weaving Visual World Modeling into Multimodal LLMs

model-releasesarxiv-cs-cl

arXiv:2610.12417v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) struggle with spatial, embodied, physical, and temporal reasoning. We hypothesize that these failures reflect

YOCO: You Only Calibrate Once! Fast Mocap Calibration for Dexterous Teleoperation

arXiv:2610.11657v1 Announce Type: new Abstract: Dexterous teleoperation requires reliable human-hand state estimations. However, common low-cost motion-capture gloves and markerless trackers often exh

researcharxiv-cs-ro

1/ My heart is heavy. I made a number of mistakes in my life, and not asking earlier for an immediate slowdown is one of them. If OpenAI sta…

model-releasesyoshua-bengio--x

1/ My heart is heavy. I made a number of mistakes in my life, and not asking earlier for an immediate slowdown is one of them. If OpenAI starts making similar breakthroughs in biology, we risk somethi

A Cognitive-Aware QML-CRL Framework for Detecting Affinity and Romance-Investment Fraud

arXiv:2610.09141v1 Announce Type: new Abstract: We present a hybrid quantum-classical framework that detects affinity and romance-investment fraud by modelling the cognitive biases in a manipulative c

agentsarxiv-cs-lg

A Framework for the Systematic Review of ML Assets in AI Registries

arXiv:2610.09551v1 Announce Type: new Abstract: Background: Modern software systems increasingly rely on Machine Learning (ML) assets (i.e., pre-trained models, datasets, benchmarks) for building, eva

A Lightweight Vision-Language Fusion Framework for Predicting App Ratings from User Interfaces and Metadata

arXiv:2602.20531v2 Announce Type: replace Abstract: App ratings are among the most significant indicators of the quality, usability, and overall user satisfaction of mobile applications. However, exis

researcharxiv-cs-cv

A Parameter-efficient Convolutional Approach for Camouflaged Weed Detection in Multispectral Aerial Imagery

arXiv:2603.06655v2 Announce Type: replace Abstract: We introduce FCBNet, an efficient model designed for camouflaged weed detection. The architecture is based on a fully frozen ConvNeXt backbone, the

A Positive Case for Faithfulness: LLM Self-Explanations Help Predict Model Behavior

arXiv:2602.02639v2 Announce Type: replace-cross Abstract: LLM self-explanations are often presented as a promising tool for AI oversight, yet their faithfulness to the model's true reasoning process i

A Probabilistic Perspective on Wasserstein-Based Evidential Uncertainty for Out-of-Distribution Segmentation

arXiv:2610.10116v1 Announce Type: new Abstract: Semantic segmentation networks operate on a fixed set of classes and therefore fail when out-of-distribution (OOD) objects appear during deployment, a c

Applications

A Review Of Robotic World Models For Dynamic Environments Based On Factor And Scene Graphs

arXiv:2610.08800v1 Announce Type: cross Abstract: Models based on graphs have emerged in robotics as a powerful foundation for internal world representations, where factor and scene graphs are among t

applicationsarxiv-cs-cv

A Unified Information-Theoretic Approach to Constrained Multi-Fidelity Multi-Objective Bayesian Optimization

arXiv:2610.10174v1 Announce Type: new Abstract: Bayesian optimization often involves multiple objectives, constraints, and fidelity levels. We address the challenge of jointly selecting where and at w

A Unified Kinematic Representation Enables Reusable Biological Joint Moment Estimation

arXiv:2610.09150v1 Announce Type: new Abstract: Objective: Data-driven models that estimate physiological states, particularly biological joint moments, are widely used in exoskeleton control. However

researcharxiv-cs-ro

Abdominal Ultrasound Simulation from Semantic Labels using Paired Label-to-Physics-Based Image Translation

arXiv:2610.08849v1 Announce Type: cross Abstract: Purpose: Current abdominal ultrasound (US) simulation methods often require CT-based anatomical references for ray-casting, limiting deformation and p

researcharxiv-cs-cv

Activation-Aware Weight Tensorization: A Calibration-Time Preconditioner for Tensor-Network LLM Compression

arXiv:2610.10085v1 Announce Type: new Abstract: Post-training tensor-network compression replaces Transformer linear layers with Tensor Train (TT) or Tree Tensor Network (TTN) operators, but standard

Adversarial RL for Port-Scan Evasion: Attacker Feature Visibility in Edge-Deployed IDS

arXiv:2610.08864v1 Announce Type: cross Abstract: Machine learning-based intrusion detection systems (IDS) are increasingly used in resource-constrained Internet of Things (IoT) environments, yet thei

AirGroundVLN: A Large-Scale Benchmark for Goal-Oriented Air-Ground Collaborative Vision-and-Language Navigation

model-releasesarxiv-cs-ro

arXiv:2610.10421v1 Announce Type: new Abstract: Goal-oriented Vision-and-Language Navigation (VLN) requires agents to locate and reach targets described in natural language without prescribed routes.

Align Before You Combine: Reference Space Calibration for Supervision Without Ground Truth

arXiv:2610.09525v1 Announce Type: new Abstract: We introduce a calibration-first framework that produces supervision scores without access to ground-truth labels or a shared annotation space. Our fram

An Informational Curse of Horizon in Goal-Conditioned Policy Learning

arXiv:2610.09247v1 Announce Type: new Abstract: The difficulty of learning goal-reaching policies is often attributed to a 'curse of horizon' that manifests as bias accumulation in temporal-difference

An Invariant Tangent-Angle Descriptor and a Band U-Net for 2D Fragment Adjacency Prediction

arXiv:2610.09459v1 Announce Type: new Abstract: This paper addresses the prediction of adjacency between pairs of 2D fragments based on their contours. We improved the two-stage architecture proposed

Local Ai

Anaximander: Interactively Running Geospatial Deep Learning Models on Any Compute Backend

arXiv:2610.09085v1 Announce Type: new Abstract: Applying deep learning models to satellite imagery from within geographic information systems (GIS) remains high-friction for remote sensing practitione

local-aiarxiv-cs-cv

APE: Selective Fine-tuning with Acceptance Criteria for Language Model Adaptation

model-releasesarxiv-cs-cl

arXiv:2505.19912v3 Announce Type: replace Abstract: We present Adjacent Possible Exploration (APE), a selective fine-tuning method for adapting large language models that systematically explores param

Are Parameter-Efficient Fine-tuning Methods Really Different?

arXiv:2610.09122v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) offers many parameterizations, yet their methodological and functional differences remain unclear. We compare six

Ask the Expert: LLM-Guided Reinforcement Learning for Autonomous Cyber Defense

arXiv:2610.09337v1 Announce Type: cross Abstract: Policy-based reinforcement learning (RL) approaches have produced promising results for autonomous cyber defense; however, they are sample-inefficient