Search: “evaluation”

A Latency-Aware Framework for Visuomotor Policy Learning on Industrial Robots

arXiv:2602.14255v2 Announce Type: replace Abstract: Industrial robots are increasingly deployed in construction and manufacturing tasks, where the deployment of end-to-end visuomotor policies is chall

safetyarxiv-cs-ro

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A Physics-informed Neural Network Approach for Robust Buckling Load Prediction and Reliability-Based Design of Thin Truncated Conical Shells

DGX agent

arXiv:2608.21818v1 Announce Type: new Abstract: Thin-walled truncated conical shells are widely used in aerospace, marine, offshore, and lightweight infrastructure systems due to their high strength-t

safetyarxiv-cs-lg

25 Aug 2026

AcroMELD: Recovering Interactive PDF Forms with Structure-Aware Graph Set Transformers

model-releasesarxiv-cs-cv

arXiv:2608.22338v1 Announce Type: new Abstract: Interactive PDF form fields are often absent from documents that visually resemble forms, leaving users unable to enter data without printing or externa

Adversarial Agents on Topology Optimization: Understanding the Fragility and Robustness of Deep Learning-based and Physics-Based Design Models under Adversarial Perturbation

arXiv:2608.22606v1 Announce Type: new Abstract: Topology optimization, using both physic-based approaches and deep learning surrogates, serves as a cornerstone for generative design agents in cyber-ma

agentsarxiv-cs-lg

Adversarial Robustness of Phishing Email Detection: A Comparative Study of TF-IDF + Logistic Regression and Fine-Tuned DistilBERT

arXiv:2607.18429v2 Announce Type: replace-cross Abstract: Phishing emails remain one of the most persistent cybersecurity threats, and machine-learning classifiers are widely used to detect them. Most

Agentic AI for Safety-critical Multi-drone Systems: Challenges and Opportunities

arXiv:2608.21444v1 Announce Type: new Abstract: Multi-drone systems are increasingly positioned for safety-critical missions such as search and rescue (SAR) and critical infrastructure monitoring. Yet

safetyarxiv-cs-ai

Agentic-Kube: A Graph-Enhanced Multi-Agent Reinforcement Learning Framework for Multi-Objective Kubernetes Scheduling

arXiv:2603.12031v3 Announce Type: replace-cross Abstract: Cloud-native container orchestration requires resource schedulers capable of balancing infrastructure expenditure, fault resilience, and node

safetyarxiv-cs-lg

Local Ai

AgentWeave: Routing Before Reasoning for Efficient Function Calling in Tool-Rich Language Models

arXiv:2608.23078v1 Announce Type: new Abstract: Large language models increasingly operate over large collections of tools, functions, APIs, and specialized agents. As the candidate action space grows

local-aiarxiv-cs-ai

All four leading LLMs talk more than they listen to personality-verified synthetic help-seekers

arXiv:2608.22425v1 Announce Type: cross Abstract: Large language models are increasingly consulted at moments of distress, yet single-turn benchmarks neither test sustained exchanges nor distinguish b

AraDetox: A Multi-Dialect Arabic Detoxification Dataset

arXiv:2608.22894v1 Announce Type: cross Abstract: Arabic harmful-language detection has received considerable attention, yet Arabic text detoxification remains underexplored. We introduce AraDetox, a

ATHENA: Knowledge-guided agentic neural architecture search for AutoFormer-based electronic health record modeling

arXiv:2608.21712v1 Announce Type: new Abstract: Transformer-based models are widely used for clinical prediction from electronic health records (EHRs), yet their architectures still require substantia

agentsarxiv-cs-ai

Balancing Safety and Optimality in Robot Path Planning: Algorithm and Metric

arXiv:2505.23197v4 Announce Type: replace-cross Abstract: Path planning for autonomous robots faces a fundamental trade-off between path length and obstacle clearance. While existing algorithms typica

safetyarxiv-cs-ai

Benchmarking Retrieval-Augmented Generation Strategies for Large Language Model-Based Travel Mode Choice Prediction

arXiv:2508.17527v2 Announce Type: replace Abstract: Accurately predicting travel mode choice is essential for effective transportation planning, yet traditional statistical and machine learning models

Benchmarking the Robustness of Foundation Models for Mammography under Domain Shift

arXiv:2607.10358v2 Announce Type: replace-cross Abstract: Foundation models are increasingly used as image feature extractors for mammography, but their robustness under external domain shift remains

Beyond Factual Knowledge: Benchmarking and Learning Step-Level Procedural Rule Reasoning in Large Language Models

arXiv:2608.22753v1 Announce Type: new Abstract: Large language models (LLMs) excel at text understanding and generation, yet still struggle to reliably understand and apply externally provided procedu

Bi-EZP: LLM-Guided Bilevel Program Evolution for Ensemble Zero-Cost Proxy Discovery

arXiv:2608.21927v1 Announce Type: cross Abstract: Zero-cost proxies enable neural architecture search (NAS) to rank candidate networks from statistics computed at initialization, avoiding repeated tra

CallScreenBench: Benchmarking Small Language Models as Phone Secretaries

arXiv:2608.01033v2 Announce Type: replace-cross Abstract: Language models small enough to run on a handset, quantized to a few bits, are increasingly capable of acting on their user's behalf -- which

Can Large Language Models 'Hyper-Thread'?

arXiv:2608.22376v1 Announce Type: new Abstract: Large language models generate tokens sequentially, but can they execute multiple tasks concurrently while forming each token? Broader attention allocat

Applications

CardioMeta: Calibrated Multi-Task Prediction of Diabetes, Hypertension, and Cardiovascular Disease Across Population and EHR Data

arXiv:2607.15721v2 Announce Type: replace Abstract: Cardiometabolic diseases remain among the most persistent drivers of preventable morbidity because diabetes, hypertension, and cardiovascular diseas

applicationsarxiv-cs-lg

ChatGPT Work can now use its computer and browser to sign in to websites on web and mobile, without ChatGPT ever seeing your username or pas…

ChatGPT Work can now use its computer and browser to sign in to websites on web and mobile, without ChatGPT ever seeing your username or password. That means you can ask it to: • Set up utilities for

safetyopenai--x

Counter with Evidence! A Multi-Agent Memory Efficient Reasoning Framework for Hate Category Informed Counterspeech Generation

arXiv:2608.23152v1 Announce Type: new Abstract: Counterspeech effectively neutralizes the impact of online hate. Although prior work explores automated counterspeech generation, it largely emphasizes

agentsarxiv-cs-cl

DefaultShift: Auditing Semantic Default Shift in Accelerated Text-to-Image Models

arXiv:2608.21784v1 Announce Type: new Abstract: Few-step text-to-image models increasingly replace slower generators, yet acceleration can silently change distributions over unspecified attributes eve

researcharxiv-cs-cv

Dynamic Cogeneration of Bug Reproduction Test in Agentic Program Repair

arXiv:2601.19066v3 Announce Type: replace-cross Abstract: Bug Reproduction Tests (BRTs) have been used in many Automated Program Repair (APR) systems, primarily for validating fixes and aiding fix gen

agentsarxiv-cs-ai

EarthVerse: Benchmarking Scientific Agents Across Dynamic Earth Systems and Natural Hazards

arXiv:2608.23525v1 Announce Type: new Abstract: Earth-system analysis reconstructs changing physical processes from observations that differ in source, scale, timing, and modality. Natural hazards mak

Local Ai

Falsification-Based Verification of LLM-Generated Optimization Models: Sound Test Batteries and Their Detection Limits

arXiv:2607.16646v2 Announce Type: replace-cross Abstract: Large language models now translate natural-language descriptions of decision problems into solver-ready optimization models, and they fail si

local-aiarxiv-cs-ai

Flesch-Kincaid Readability Depends Only on the Topic Distribution in Long Texts under Topic Models

arXiv:2608.23327v1 Announce Type: new Abstract: Flesch Reading Ease (FRE) and the Flesch-Kincaid Grade Level (FKGL) are widely used readability scores for English computed from the same two document s

From Generation to Simulation: How Far Are World Models from Being True Simulators?

arXiv:2608.23070v1 Announce Type: new Abstract: With the rapid progress of diffusion models and large-scale video generation, generative world models are increasingly expected to replace traditional s

Future Querying: Can LLMs Serve as Implicit Medical World Models?

arXiv:2608.23248v1 Announce Type: cross Abstract: Traditional clinical prediction models rely on task-specific pipelines and curated, structured data, which scale poorly and underutilize unstructured

Applications

Generated Reality: Human-centric World Simulation using Interactive Video Generation with Hand and Camera Control

arXiv:2602.18422v2 Announce Type: replace Abstract: Extended reality (XR) demands generative models that respond to users' tracked real-world motion, yet current video world models accept only coarse

applicationsarxiv-cs-cv

Grounded Normative Rule Generation with Structured Search

arXiv:2608.22229v1 Announce Type: new Abstract: Normative rules like institutional charters and workplace policies must be both human-readable and operationally verifiable against actual environment r

GSAR: Goal-State-Anchor Rewards for Mobile GUI Agents with Self-Evolving Data Synthesis

arXiv:2608.22847v1 Announce Type: new Abstract: Vision-Language Models (VLMs) based GUI agents stand to benefit significantly from online reinforcement learning (RL). However, their training is bottle

GuardianBench: A Same-Scene Instruction-Contrastive Benchmark for Latent Contextual Risk in Embodied AI

arXiv:2608.21928v1 Announce Type: new Abstract: In embodied AI, safety risk can be latent: a benign instruction and a safe scene become hazardous only when composed. Prior work has advanced embodied s

HelaBERT: Enhancing Sinhala Language Understanding with Dual Pooling Classification Head

arXiv:2608.22922v1 Announce Type: new Abstract: We present HelaBERT, a family of two BERT-based masked language models pre-trained from scratch on approximately 1 billion tokens of Sinhala text source

How Agents Represent Humans: Human-Directed Stereotypes in an Open Agent Social Network

arXiv:2608.22192v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed in persistent social environments, where generated claims can be posted, replied to, remembered, and reused.

safetyarxiv-cs-cl

How Does Research Evolve? Tracing Cross-Domain Trajectories in NLP, ML, and CV Through Claim-Grounded Typed Citations

arXiv:2606.22342v2 Announce Type: replace Abstract: How does research evolve, and can we trace it at the level of individual claims? Scientific progress is not simply a uniform accumulation of facts.

InstructMove: A Text-Indispensable Benchmark for Instruction-Following Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.22990v1 Announce Type: new Abstract: Vision-language-action (VLA) models have made general-purpose robot manipulation increasingly plausible by conditioning robot actions on natural-languag

Is Next-Chunk Reasoning RL Really Better than SFT? Revisiting Training Strategies under no-CoT Data

arXiv:2608.23256v1 Announce Type: new Abstract: Recent work proposes next-chunk reasoning RL for leveraging no-CoT data---corpora such as worked solutions and textbook derivations that contain reasoni

Learning from the Test: Self-Referential Differential Testing for Deep RL Agents

arXiv:2608.22284v1 Announce Type: cross Abstract: Deep Reinforcement Learning (DRL) has achieved significant success in complex decision-making problems. As DRL systems are increasingly deployed in re

safetyarxiv-cs-ai

MemGuard: Persisting Verifier Signals for LLM-Agent Memory Governance

arXiv:2608.21867v1 Announce Type: new Abstract: LLM agents are moving from single-prompt use to long task streams in which reusable memory becomes a core capability for terminal, software-engineering,

Minimum Bisection Problem: Machine Learning-Based Penalty Parameter Tuning for Optimization on Quantum Annealers

model-releasesarxiv-cs-lg

arXiv:2509.19005v2 Announce Type: replace-cross Abstract: The Minimum Bisection Problem is a fundamental, computationally hard graph partitioning problem with applications in parallel computing, netwo

Applications

MoCo-AIS: A Contrastive Learning Framework for Similarity Computation of Vessel Trajectories

arXiv:2606.17978v2 Announce Type: replace Abstract: Trajectory similarity is a fundamental task in analyzing mobility patterns, essential for applications such as route pattern extraction, mobility pr

applicationsarxiv-cs-ai

Modalities Should Talk to Each Other: Dual-Stream Multimodal Learning for Long-Horizon Influenza Forecasting

arXiv:2608.23373v1 Announce Type: new Abstract: Forecasting long-range influenza-like illness (ILI) matters for public health readiness. Publicly available surveillance datasets typically pair numeric

Models in the Same Family are NOT Trust-Equivalent

arXiv:2508.13533v2 Announce Type: replace Abstract: Within a model family, a smaller variant is often deployed as a drop-in replacement for a larger one when their performance is similar. However, per

More Experts, Worse Dynamics: Inverse Scaling and Spectral Bias in Mixture-of-Experts State-Space Models

arXiv:2608.21840v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures are commonly motivated as a way to increase expressivity by decomposing complex systems into simpler local dynami

safetyarxiv-cs-lg

MOSH-WM: Mask-Grounded Soft-Hamiltonian Dynamics for Object-Centric World Models

arXiv:2608.22750v1 Announce Type: new Abstract: Object-centric world models forecast future videos by evolving a set of entity slots, but the variables receiving dynamics supervision are often unconst

safetyarxiv-cs-lg

Motion-Based Tokenization for Cross-Dataset Egocentric Gaze Modeling

model-releasesarxiv-cs-cv

arXiv:2608.22926v1 Announce Type: new Abstract: Gaze is increasingly used as an input signal for vision and multimodal models, yet no consensus exists on how to represent it across datasets. Raw trace

No One Model Catches Every Harm: Benchmarking Content Moderation Across Safety Scenarios

arXiv:2608.21775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in real-world applications, yet they remain vulnerable to generating harmful content. From advers

safetyarxiv-cs-cl

OmniCAD: A Large-Scale Benchmark for 3D Spatial Reasoning in Robotics Assemblies

model-releasesarxiv-cs-cv

arXiv:2608.22637v1 Announce Type: new Abstract: Recent vision-language models (VLMs) show strong capabilities in robotic perception and spatial reasoning, yet their ability to reason about complex mec