Search: “benchmark”

Vmem-arphi: Low-Compute Out-of-Distribution Detection in Spiking Neural Networks from Membrane-Potential Statistics

model-releasesarxiv-cs-cv

arXiv:2610.00350v1 Announce Type: new Abstract: Spiking Neural Networks (SNNs) offer an energy-efficient approach to processing event-camera data, yet out-of-distribution (OOD) detection remains chall

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WBAG: A Whole-Body and Attached-Geometry Safety Framework for Vision-Language-Action Manipulation

DGX agent

arXiv:2610.01083v1 Announce Type: new Abstract: Vision-language-action (VLA) policies have demonstrated impressive capabilities in generalizable robotic manipulation, but their deployment in the real

model-releasesarxiv-cs-ro

2 Oct 2026

What Builds the Scene? Luminance Dominates Geometry Formation in 3D Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2610.00749v1 Announce Type: new Abstract: Standard 3D Gaussian Splatting (3DGS) learns geometry and appearance jointly from RGB supervision, making it difficult to isolate how luminance and chro

What Does a Skill Actually Do? Estimands and Evaluation Validity for Tool and Skill Use in LLM Agents: A Critical Review

arXiv:2609.33153v2 Announce Type: replace-cross Abstract: Reported improvements from tools and reusable skills in large language model agents refer to different comparisons. This critical narrative re

researcharxiv-cs-ai

What Should an Agent Remember? Disentangling Retention from Retrieval in Bounded-Memory Evaluation

arXiv:2610.00366v1 Announce Type: new Abstract: A persistent agent must decide both what to retain as information arrives and what to surface once a query appears, yet memory evaluations can confound

When Does a Second Model Help? Cross-Model Review in LLM Verification

arXiv:2610.01471v1 Announce Type: cross Abstract: Large language models now generate code, documentation, and analyses, and are increasingly used to review such output. We ask when a second review by

When Text-to-Image Helps Editing: The Effects of Conditioning During Denoising

arXiv:2610.01681v1 Announce Type: new Abstract: Unified models are trained for both instruction-based image editing and text-to-image (T2I) generation, but standard editing pipelines keep source-image

researcharxiv-cs-cv

Where's Waldo? Query-language Preference under Cross-lingual Knowledge Disparities

arXiv:2610.00606v1 Announce Type: cross Abstract: Large Language Models increasingly serve as interfaces for knowledge-intensive information seeking tasks across languages by synthesizing multilingual

World Observer: Joint Actor-Observer Generation for Persistent World Modeling

model-releasesarxiv-cs-cv

arXiv:2610.02162v1 Announce Type: new Abstract: How can a world model continuously observe regions beyond the actor's current view? Video world models simulate how an environment evolves from an agent

Wrivinder: Towards Spatial Intelligence for Geo-locating Ground Images onto Satellite Imagery

arXiv:2602.14929v2 Announce Type: replace Abstract: Aligning ground-level imagery with geo-registered satellite maps is crucial for mapping, navigation, and situational awareness, yet remains challeng

safetyarxiv-cs-cv

Zero-shot generalization of transformer neural operators to larger domains

arXiv:2606.14597v2 Announce Type: replace Abstract: Transformer-based neural operators have shown remarkable performance for approximating solution operators of partial differential equations on compl

safetyarxiv-cs-lg

A Data-Free Physics-Informed Neural Operator for Level-Set Interface Advection

arXiv:2609.38195v1 Announce Type: new Abstract: Operators for interfacial problems are trained on reference solutions produced by the solver they are intended to replace. This work develops a data-fre

researcharxiv-cs-lg

A Dynamical Theory of LoRA in Continual Learning

arXiv:2609.39367v1 Announce Type: cross Abstract: Despite the widespread use of Low-Rank Adaptation (LoRA), little is known about its dynamics in continual learning and the mechanisms by which low-ran

A Time-Aware Bag-of-Receptive-Fields for Interpretable Irregular Time Series Classification

arXiv:2609.39268v1 Announce Type: cross Abstract: Irregular time series, characterized by non-uniform sampling intervals, missing observations, and variable lengths, are ubiquitous in healthcare, mobi

A Two-Echelon Covering Tour Vehicle Routing Problem with Drones for Post-Disaster Relief

model-releasesarxiv-cs-ro

arXiv:2609.38227v1 Announce Type: new Abstract: We introduce the two-echelon covering tour vehicle routing problem (2E-CTVRP) for the distribution of relief supplies after a disaster. In the first ech

About the Influence of Workflow Topology on Task Intensity Prediction through Graph Learning

arXiv:2609.39481v1 Announce Type: cross Abstract: Efficient resource provisioning for large-scale workflows on cloud infrastructures is a critical performance engineering challenge. These workflows ar

Applications

Accelerated Algorithm for Sparse Regularized Partial Optimal Transport

arXiv:2609.40075v1 Announce Type: new Abstract: Partial Optimal Transport (POT) extends the classical optimal transport problem by relaxing the strict mass conservation constraint, enabling its use in

applicationsarxiv-cs-lg

Activation-Conditioned Self-Distillation

arXiv:2609.38342v1 Announce Type: new Abstract: On-policy self-distillation uses a model as its own teacher to provide dense supervision for reasoning, often through reference-solution conditioning. P

Active Learning with Imperfect Labels: Optimal Labeler Assignment and Sample Selection

arXiv:2512.12870v2 Announce Type: replace-cross Abstract: Active Learning (AL) is commonly used in applications where labeling data is expensive or time-consuming. In practice, however, labels are oft

Tutorials

AdaGEPA: Adaptive Feedback Allocation for Reflective Prompt Optimization

arXiv:2609.39927v1 Announce Type: new Abstract: Prompt optimization improves the performance of language-model systems on downstream tasks by refining their prompts. Classical methods evaluate prompts

tutorialsarxiv-cs-cl

Agentic Relative Camera Pose Estimation via Learned Ranking and Verification

arXiv:2609.38755v1 Announce Type: new Abstract: A wide range of approaches have been developed for camera pose estimation, including correspondence-based methods, end-to-end pose regression, and recen

safetyarxiv-cs-cv

Local Ai

Agentic Tool-Augmented Reasoning for Explainable Image Forgery Detection

arXiv:2609.39066v1 Announce Type: new Abstract: Conventional image forgery detection methods produce binary scores or pixel-level masks without interpretable evidence, while recent multimodal large la

local-aiarxiv-cs-cv

AIMS: An Agentic AI Framework for Sim-to-Real Multi-Modal ISAC

arXiv:2609.39964v1 Announce Type: new Abstract: Multi-modal integrated sensing and communication (ISAC) enables environmental perception and reliable connectivity for intelligent wireless networks. Da

Aligning Thoughts with Answers: Probability Rewards to Tame Thinking Drift

arXiv:2609.39183v1 Announce Type: new Abstract: This paper studies extbf{thinking--answer consistency} in vision-language models. We focus on Visual Intention Grounding, where a model infers a target

researcharxiv-cs-cv

An Empirical Study of On-Device Translation for Real-Time Live-Stream Chat on Mobile Devices

arXiv:2601.02641v2 Announce Type: replace Abstract: Despite its efficiency, there has been little research on the practical aspects required for real-world deployment of on-device AI models, such as t

An Input-Frugal Deep Learning Framework for Weather-Driven National Crop-Yield Forecasting: A Case Study of Brazilian Soybean

arXiv:2609.38447v1 Announce Type: new Abstract: Reliable, timely crop-yield forecasts are essential for market stability and risk management, yet many approaches rely on costly or hard-to-scale inputs

Applications

ANI: Adaptive Numerical Injection for Unifying Semantic and Arithmetic Representations in Numerical Reasoning

arXiv:2609.39294v1 Announce Type: new Abstract: Precise numerical reasoning with Large Language Models (LLMs) is essential for expanding their applicability to complex real-world tasks. However, text-

applicationsarxiv-cs-ai

Approval Laundering: Systematizing Approval--Execution Binding Failures in AI Coding-Agent Harnesses

arXiv:2609.38983v1 Announce Type: cross Abstract: Modern AI coding-agent harnesses (Claude Code, Codex CLI, Cursor) rest their security boundary on a largely unexamined assumption: that the action A a

ArchitectureIQ: On the Measure of Training Intuition

arXiv:2609.39714v1 Announce Type: new Abstract: Top researchers have good intuition, but do language models have as good intuition about model training as top AI researchers? To measure model intuitio

ASENA: Self-evolving Agents for Embodied Navigation

arXiv:2609.39207v1 Announce Type: new Abstract: We present ASENA, an embodied agent system that connects general-purpose coding agents to robot sensing, computation, supervised execution, and persiste

safetyarxiv-cs-ro

Local Ai

Belief-Aware Multi-Agent Path Finding under Map Uncertainty

arXiv:2609.40269v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) aims to find collision-free paths for multiple agents in a shared environment. Classical MAPF assumes that all static ob

local-aiarxiv-cs-ai

BELIEFRAG: Making Adaptive RAG State-Aware under Evolving Evidence

arXiv:2609.39139v1 Announce Type: new Abstract: Adaptive RAG uses signals such as confidence, relevance, support, and retrieval quality to decide when to search or correct evidence. In multi-step retr

researcharxiv-cs-ai

Better Supervision Is Nearby: Neighborhood On-Policy Self-Distillation

model-releasesarxiv-cs-cl

arXiv:2609.39687v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains mathematical reasoning models using a privileged teacher that sees a reference solution and supervises student

Beyond Policy Alignment: Closing the Planning-Learning Loop for Robot Control with Learned World Models

model-releasesarxiv-cs-ro

arXiv:2609.39751v1 Announce Type: new Abstract: Planning with learned world models combines online trajectory optimization with learned value and policy functions for high-dimensional control. Because

Beyond the Remembered World: Predictive 4D Belief for Persistent Navigation in Evolving Worlds

arXiv:2609.39166v1 Announce Type: new Abstract: Persistent spatial memory enables embodied agents to navigate familiar environments across repeated visits. However, targets may move while unobserved,

Agents

Beyond the Shadows of Plato's Cave: Evaluating False Memory in Autonomous Agents via Counterfactual Reasoning

arXiv:2609.39473v1 Announce Type: new Abstract: Autonomous agents increasingly rely on memory to generalize beyond their training environments. However, agents are bounded by what they have seen and b

agentsarxiv-cs-ai

Local Ai

Build Local AI Apps with C++ and NVIDIA TensorRT RTX Samples

The Nvidia Deploy repository provides open‑source C++ samples that pair ONNX Runtime with the TensorRT RTX execution provider to accelerate local inference on Windows and Linux. It separates model exp

local-ainvidia-developer

Can an AI Agent Rediscover a Blaschke-Curve Invariant?

arXiv:2609.38369v1 Announce Type: new Abstract: We study generalized Blaschke curves as a controlled environment for AI-assisted mathematical rediscovery. For one fixed degree-four Blaschke product, a

Can Computation from Earlier Problems Help LLMs Solve New Ones?

arXiv:2609.39394v1 Announce Type: new Abstract: Large language models often solve independent problems in the same conversation. Can computation from earlier problems help them solve new ones? To answ

Cascadia: A Control-Plane-Free Alternative to Hyperconverged AI Infrastructure

arXiv:2609.38697v1 Announce Type: cross Abstract: We present Cascadia, a system for serving large language models on fleets of commodity Intel AIPCs using their CPU, integrated-GPU, and NPU resources.

CAST: Causal Advantage-Structured Training with Spatially Grounded Compositional Rewards for Diffusion Models

arXiv:2609.39441v1 Announce Type: cross Abstract: Online reinforcement learning has been extended to flow matching for diffusion model (DM) image generation. However, this paradigm faces three limitat

Applications

CDMD: A Cross-Dataset Mixed-Type Diffusion Model for Tabular Data

arXiv:2609.39124v1 Announce Type: new Abstract: Generative models for tabular data are typically trained separately for each dataset, limiting knowledge transfer and requiring the storage of many spec

applicationsarxiv-cs-lg

CellMSA: Context Modeling for Single-Cell Representation Learning

arXiv:2609.38908v1 Announce Type: cross Abstract: Single-cell transcriptomics enables profiling of cellular states at unprecedented resolution, but its high dimensionality, sparsity, and technical bat

safetyarxiv-cs-ai

Certification-Based Differentially Private Learning

arXiv:2609.39629v1 Announce Type: new Abstract: Differential privacy (DP) in machine learning is typically achieved by adding noise to model parameters (private learning) or to model outputs (private

CoEvoWhen: Policy-Tool Coevolution for Ultra-Long Video Temporal Grounding

arXiv:2609.40048v1 Announce Type: new Abstract: Ultra-long video temporal grounding requires balancing long-range evidence search with fine-grained event understanding under a limited visual budget, y

safetyarxiv-cs-cv

Composition, Not Conversation: VLMs Lose the Scene, Not the Thread

arXiv:2609.38368v1 Announce Type: new Abstract: Vision-language models (VLMs) increasingly reason over visual evidence that is cropped, segmented, retrieved, or revealed over time. Yet most VQA benchm

researcharxiv-cs-cv

Continual Learning of Dynamical Systems in Recurrent Neural Networks through Recyclable Unit Gating

arXiv:2609.38356v1 Announce Type: new Abstract: Dynamical Systems Reconstruction (DSR) aims to infer models from observed time series that reproduce a system's qualitative long-term behavior. Continua

Contrastive Representation Shaping for LLM Unlearning

arXiv:2601.22028v2 Announce Type: replace Abstract: Most LLM unlearning methods aim to approximate retrain-from-scratch behaviors with minimal distribution shift, often via alignment-style objectives

safetyarxiv-cs-lg