Search: “evaluation”

TinyUDE: Solver-Free Universal Differential Equations on Microcontrollers via Lie-Taylor Jet Matching

arXiv:2609.26972v1 Announce Type: new Abstract: Training Universal Differential Equations (UDEs) traditionally relies on backpropagating through numerical ODE solvers, creating memory footprints far e

local-aiarxiv-cs-lg

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Today we establish that AI is as good as expert human tutors for immediate GRE learning gains (p=.015, n=2,383 students, study conducted Jul…

DGX agent

Today we establish that AI is as good as expert human tutors for immediate GRE learning gains (p=.015, n=2,383 students, study conducted July-Sep 2026). One hour with an expert GRE tutor: $75. One equ

model-releasesjeremy-howard--x

24 Sept 2026

Topological Signatures of Cyber-Attack Classes in Natural Visibility Graph Representations of Network Traffic

arXiv:2609.26990v1 Announce Type: cross Abstract: Natural Visibility Graph (NVG)-based representations provide a promising approach for capturing structural patterns in sequential network traffic. How

Tractable Reinforcement Learning for Full Class of Signal Temporal Logic Specifications Using Spatiotemporal Tube Reward

arXiv:2609.28396v1 Announce Type: new Abstract: This paper addresses the control problem for robotic systems, including non-holonomic and underactuated platforms operating under unknown dynamics and s

agentsarxiv-cs-ro

Training Intelligent Voice Assistant Wakeup with Controllable Synthetic Conversations

arXiv:2609.27037v1 Announce Type: new Abstract: Wake word detection is a critical component of virtual assistants, serving as the gateway to seamless user interactions. This paper introduces a novel w

TwinCheck: Evidence-Grounded Negative-Twin Verification for Stateful Tool Agents

arXiv:2609.26911v1 Announce Type: new Abstract: A single locally plausible tool call can derail an otherwise successful agent trajectory. Suspicion alone does not justify intervention, because the rep

Type-II Error Bounds for Test Supermartingales from Lower-Tail Hypotheses

arXiv:2609.27766v1 Announce Type: cross Abstract: In safe hypothesis testing with test supermartingals, Ville's inequality provides anytime-valid type-I error guarantees for every significance level a

UkisAI Swift Series / 27B, Flash Next and Bonsai 2 + GSQ-RCO / -63.4% thinking, x1.95 speed with xhigh accuracy

model-releasesr-localllama

Hey everyone, Jovan from UkisAI here! Today, we are introducing Swift, a family of efficient reasoning LLMs based on Qwen, trained by penalizing tokens related to pathological overthinking patterns an

Applications

VGM-VS: Rethinking Visual Geometry Model for High-Precision Visual Servoing

arXiv:2609.28312v1 Announce Type: cross Abstract: We present VGM-VS, a visual servoing method built on a pretrained feed-forward visual geometry model. Given the current view and a reference image cap

applicationsarxiv-cs-cv

Visual Tripwires: Anticipating Failure in Deep Vision Systems

model-releasesarxiv-cs-cv

arXiv:2609.28099v1 Announce Type: new Abstract: Deep vision systems remain vulnerable to corruption, occlusion, and distribution shift despite strong benchmark performance. Existing reliability method

Wave-Robust Passive AUV Localization Using FP-MUSIC

arXiv:2609.27712v1 Announce Type: new Abstract: Localizing an autonomous underwater vehicle without pre-deployed seabed transponders, or direct access to onboard vehicle sensors remains a core challen

agentsarxiv-cs-ro

What Changes When Fact-Verification Scores Improve? Evidence and Answer Accounting Across Trained Verifiers and LLMs

arXiv:2609.27064v1 Announce Type: new Abstract: A joint fact-verification score assesses answers and submitted evidence together. When the score improves, how much of the gain remains if the answers a

What Do Tabular Foundation Models Compute In Context? In-Situ Representation Refinement through Attention-Gated Updates

model-releasesarxiv-cs-lg

arXiv:2609.27679v1 Announce Type: new Abstract: What reusable computation should a tabular foundation model learn when every table defines a new supervised task? We develop in-situ representation refi

WhatWorkedBench: Benchmarking Experimental Understanding in AI Agents

arXiv:2609.27490v1 Announce Type: new Abstract: AI research agents need reliable knowledge of how their experiments change outcomes. We introduce WhatWorkedBench to measure experimental understanding,

agentsarxiv-cs-ai

When Accuracy Gaps Fail to Certify: Auditing Cross-Domain Recalibration of LLM Judges

arXiv:2609.27954v1 Announce Type: new Abstract: A scalar recalibration map fitted for an LLM judge on one task can fail when the task distribution changes, but the source-target accuracy gap is often

When Context Misleads: In-context Learning with Jurisdiction in Large Language Models

arXiv:2609.27603v1 Announce Type: cross Abstract: In-Context Learning (ICL) has become a cornerstone of modern LLM deployment. However, existing ICL post-training methods have a critical blind spot: t

XLOG: A CUDA-Native Engine for Neurosymbolic Integration

arXiv:2609.27203v1 Announce Type: new Abstract: xlog is a CUDA-native logic programming engine integrating neural perception with deterministic Datalog, probabilistic inference, and epistemic world vi

A bioinspired internal model-based online estimator for planar pursuit

arXiv:2609.25470v1 Announce Type: new Abstract: Bioinspired feedback controls for pursuit, tracking, and collective motion are often expressed in terms of the relative configuration between interactin

researcharxiv-cs-ro

A Computational Approach to Measuring Semantic Change in Sanskrit Literature

arXiv:2609.25012v1 Announce Type: new Abstract: Diachronic word embeddings have become the modern standard for tracking semantic change, yet they have been largely validated on modern, high-resource,

A Deployment Study of Identity-Gated Drone Gesture Control

model-releasesarxiv-cs-ro

arXiv:2609.25511v1 Announce Type: new Abstract: Vision-based gesture control accepts commands from any hand in the camera field of view, which is unsafe in shared indoor spaces. This paper presents IG

Applications

A Global Comparison of Schemas, Transparency, and Interoperability in Public-Sector AI Registers and Inventories

arXiv:2609.24883v1 Announce Type: new Abstract: Artificial intelligence (AI) registers and inventories aim to make governmental AI visible, but their institutional scope, schemas, and reporting practi

applicationsarxiv-cs-ai

Tutorials

A Hybrid AI Framework for Academic Advising: Integrating Ensemble-Based Grade Prediction and a Rule-Based Expert System

arXiv:2609.26243v1 Announce Type: cross Abstract: The rapidly increasing student population has posed serious challenges to the traditional academic advising process. This study designs and implements

tutorialsarxiv-cs-lg

A Lean and Spec-Driven AI-Assisted Software Development Lifecycle for Applied AI Education: The AI-SDLC Approach

arXiv:2609.24348v1 Announce Type: cross Abstract: AI coding agents increasingly support software development beyond code completion, including planning, implementation, testing, and repository-level t

local-aiarxiv-cs-ai

A Multi-Timestep LSTM Ensemble regressor for Enhanced Short-Term Runoff Prediction

arXiv:2609.26244v1 Announce Type: cross Abstract: Accurately forecasting river runoff is key to managing water resources, controlling floods, and planning agriculture. This study examines the Ajichay

agentsarxiv-cs-lg

A Reconfigurable Bidirectional Cable-Driven Hip Exoskeleton with Swappable Bench/Backpack Dual-configuration Actuation

arXiv:2609.25639v1 Announce Type: new Abstract: Hip exoskeletons provide an important hardware basis for lower-limb rehabilitation and locomotor assistance. Laboratory rehabilitation assessment and sy

researcharxiv-cs-ro

A retrospective analysis on the use of LLMs to study infant syntax learning

arXiv:2609.26539v1 Announce Type: new Abstract: Large language models (LLMs) have increasingly been used to investigate how children acquire syntax at an early stage of development. This is notably th

ABAI at COLIEE 2026 Task 1: Multi-Stage Retrieval with GraphRAG-Enhanced Meta-Learning, and a Post-Hoc Study of the Cross-Validation-to-Test Gap

arXiv:2609.26237v1 Announce Type: cross Abstract: We present the ABAI submission to COLIEE 2026 Task 1, case law retrieval, together with a controlled study of why it underperformed. The task suppress

ActGov: Governing LLM Agent Actions via Policy-Constrained Validation

arXiv:2609.24446v2 Announce Type: cross Abstract: Large language model (LLM) agents increasingly execute long-horizon workflows through external tools, allowing untrusted outputs to influence subseque

safetyarxiv-cs-ai

ADSEL: Adaptive Dual Self-Expression Learning for EEG Feature Selection via Incomplete Multi-Dimensional Emotion Labels

arXiv:2508.05229v2 Announce Type: replace-cross Abstract: EEG based multi-dimension emotion recognition has attracted substantial research interest in affective computing. However, the high dimensiona

Agensh: Scaling Organizational Intelligence to 1,024 Agents

arXiv:2609.26781v1 Announce Type: new Abstract: A multi-agent system can reduce latency on complex tasks by executing work concurrently. Several pioneering harness frameworks support multi-agent syste

An Accurate and Interpretable Hyper Graph Neural Network for GBM Survival Prediction

arXiv:2609.25088v1 Announce Type: cross Abstract: Survival prediction for glioblastoma multiforme (GBM) demands models that are both accurate and interpretable, yet existing approaches treat these obj

An Action Is Worth One Patch: Unified World-Action Modeling with PatchWAM

model-releasesarxiv-cs-ro

arXiv:2609.25961v1 Announce Type: new Abstract: Generative visual models offer a foundation for learning representations of physical dynamics, yet their extension to continuous control raises a fundam

Annie, Are You Okay? How Style- and Context-Based Personalization Shape AI-Assisted Decision-Making

arXiv:2609.24644v1 Announce Type: cross Abstract: As people turn to generative AI for financial advice, these systems can personalize how they communicate and what they say. Whether these forms of per

APEXA: Execution-Integrity Enforcement for Multi-Agent LLM Automation of Synchrotron Data Reduction

arXiv:2609.24165v1 Announce Type: new Abstract: Synchrotron data reduction, detector calibration followed by azimuthal integration of terabyte-scale diffraction series, is a multi-step, expert-bound b

Hardware

ArborSplat: Online Semantic Gaussian Splatting SLAM for Orchards

arXiv:2609.26315v1 Announce Type: new Abstract: Orchard robots need maps that preserve small but semantically important structures such as trunks, trellises, and fruit. 3D Gaussian Splatting (3DGS) SL

hardwarearxiv-cs-ro

AURA: Angular Update Rate Adaptation for training complex-valued neural networks

model-releasesarxiv-cs-lg

arXiv:2609.25914v1 Announce Type: new Abstract: Complex-valued neural networks (CVNNs) are increasingly adopted for complex-valued data; however, they are often trained with first-order optimizers inh

Beyond PUE: A Local Impact Audit Framework for Data Center Environmental Accountability

arXiv:2609.23421v1 Announce Type: cross Abstract: Standard data center sustainability metrics, including Power Usage Effectiveness (PUE), Water Usage Effectiveness (WUE), and Carbon Usage Effectivenes

safetyarxiv-cs-ai

Beyond Raw Engagement: A Counterfactual Observability Framework for Recommender Systems at Netflix

arXiv:2609.22747v1 Announce Type: cross Abstract: Understanding the performance of large-scale recommender systems remains an underexplored challenge, especially for content creators and model develop

safetyarxiv-cs-ai

Beyond Repeated Sampling: Learning Search Policies for LLM Reasoning

arXiv:2609.26704v1 Announce Type: new Abstract: Large language models increasingly tackle hard reasoning problems by spending more test-time compute, yet the dominant strategy remains naive repeated s

local-aiarxiv-cs-cl

Beyond Scalar Sensitivity: Activation-Aware Mixed-Precision LLM Quantization with Cross-Layer Refinement

arXiv:2609.25916v1 Announce Type: new Abstract: Mixed-precision weight quantization is commonly formulated as a Multiple-Choice Knapsack Problem (MCKP), yet existing solvers rely on scalar sensitivity

local-aiarxiv-cs-lg

Beyond Static Charts: Can Language and Vision Language Models Generate Interactive Data Visualization Interfaces?

arXiv:2609.26208v1 Announce Type: new Abstract: Data visualization is central to analytical reasoning, but real-world analysis increasingly requires language-driven interactive interfaces rather than

BOBA: Dynamic Bayesian Optimization through Bayesian Active Inference

arXiv:2609.26021v1 Announce Type: new Abstract: Dynamic black-box optimization presents significant challenges for Bayesian Optimization (BO), as the objective function evolves over time, causing opti

Brain-Token Learning: Microstate-Based Tokenization and Multi-Scale Interaction for Long-Horizon EEG Sequence Modeling

arXiv:2609.24324v1 Announce Type: new Abstract: Electroencephalography (EEG) provides a non-invasive window into dynamic brain activity, yet modeling long-horizon EEG sequences remains challenging due

Bridging the Data Gap: Digital Twin as a New Paradigm for AI-based Radio Sensing

arXiv:2609.26214v1 Announce Type: new Abstract: We present a methodology that places a 3D digital twin (DT) of the environment as the main enabler behind the development of radio sensing at scale. The

local-aiarxiv-cs-lg

Calibrated Confidence Expression for Radiology Report Generation

arXiv:2603.29492v2 Announce Type: replace Abstract: Safe deployment of Large Vision-Language Models (LVLMs) in radiology report generation requires not only accurate predictions but also clinically in

Capability-Aware Arbitration for Semantic Intent-Based Shared Control

arXiv:2609.25369v1 Announce Type: new Abstract: Shared control often allocates robot authority based on confidence in inferred human intent, assuming reliable autonomous execution. When this assumptio

safetyarxiv-cs-ro

Capable yet Parsimonious: Extracting and Characterizing Hidden Chain-of-Thought in Frontier Models

arXiv:2609.26637v1 Announce Type: new Abstract: The rapid capability gains of frontier language models are widely attributed to improved reasoning abilities, yet this cannot be verified as raw CoT tra

Cellular-Communication-Level Interpretability for Pathology Foundation Models via Graph Distillation on Microenvironment

arXiv:2609.26073v1 Announce Type: new Abstract: Pathology foundation models (PFMs) provide strong tile-level representations but remain difficult to interpret at the cellular and microenvironmental sc

researcharxiv-cs-cv