Search: “evaluation”

Self-Evolving Code-with-Image Reasoning

model-releasesarxiv-cs-cv

arXiv:2608.11292v1 Announce Type: new Abstract: Multimodal models increasingly reach for tools when solving visual tasks (crop, zoom, rotate, brighten), a paradigm known as thinking-with-images. The c

Self-Evolving Embodied Agents via Skill-Harness Evolution

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arXiv:2608.11350v1 Announce Type: new Abstract: Embodied agents are increasingly built as systems around foundation models, where performance depends not only on model weights but also on the skills,

model-releasesarxiv-cs-cl

13 Aug 2026

Social Chain of Thought: A Multi-Agent Architecture Grounded in Medical Differential Diagnosis Methodology

arXiv:2608.11420v1 Announce Type: new Abstract: Medical diagnostic reasoning is a high-impact use case for LLMs that carries significant implications for the health and wellbeing of users. When OpenAI

Structural Silence: When AI Infrastructure Fails Speakers of Underrepresented Languages

arXiv:2608.12278v1 Announce Type: cross Abstract: Artificial intelligence tools for education and language support are increasingly framed as scalable responses to access gaps in under-resourced commu

applicationsarxiv-cs-ai

TailBooster: A Dual-Layer Generative Framework for Extreme Value Augmentation with Operational Validity Enforcement

arXiv:2608.11951v1 Announce Type: cross Abstract: Extreme events in air transport, such as severe arrival delays and abnormal air times, cause cascading network disruptions with substantial operationa

safetyarxiv-cs-ai

Local Ai

The Off-Support Barrier: Why Semantic Safety Constraints Are Not Learning-Problem Invariants, and What Follows for Prior Design, Containment, and Verification

arXiv:2608.11243v1 Announce Type: new Abstract: We argue that a single structural fact organizes a wide range of phenomena in contemporary AI safety: a semantic safety constraint (e.g., the agent does

local-aiarxiv-cs-ai

Top-down Traffic Scenario Generation via Joint Initial-Goal Diffusion and Trajectory Infilling

arXiv:2608.11407v1 Announce Type: new Abstract: Robust traffic simulators are crucial for developing and testing autonomous vehicles to reduce the costly, labor-intensive real-world data collection pr

agentsarxiv-cs-ro

Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pre-training

arXiv:2604.07037v2 Announce Type: replace-cross Abstract: Accelerator-based neutrino physics is entering an energy-frontier regime in which interactions reach the TeV scale and produce exceptionally d

researcharxiv-cs-cv

Towards Human Motion World Models via Executable Behaviour Representations

arXiv:2604.18064v2 Announce Type: replace Abstract: Human motion world models should capture motion's intentionality by being executable: adaptable to different actions and capable of assessing motion

safetyarxiv-cs-ai

Tutorials

Towards Sustainable Learning in Online Education: A Reinforcement Learning Approach

arXiv:2608.11245v1 Announce Type: new Abstract: Online education offers unprecedented scalability and accessibility to global learners from diverse backgrounds, but it often suffers from low engagemen

tutorialsarxiv-cs-ai

Towards the Harness of Embodied Agents

arXiv:2608.11246v1 Announce Type: new Abstract: The success of coding agents has established the harness as a paradigm: what an agent achieves depends not on the model alone, but on the infrastructure

Towards Understanding On-Policy Distillation through the Lens of Test-Time Scaling

arXiv:2608.11829v1 Announce Type: cross Abstract: On-policy distillation (OPD) has emerged as a promising post-training technique for enhancing LLM reasoning. It is commonly believed to enable the stu

safetyarxiv-cs-cl

TradingMoE: Routing the Right Experts in Evolving Markets

arXiv:2608.11785v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for financial analysis and trading, but direct trading remains challenging because the predicti

researcharxiv-cs-lg

Transit Destination Inference from Tap-In-Only Bus Smart-Card Data: A Hierarchical Bayesian Approach

arXiv:2608.11223v1 Announce Type: cross Abstract: Entry-only automatic fare collection systems record boardings but not alightings, preventing direct construction of origin-destination (OD) matrices.

Two-Stage Deformable-Convolutional Inverse Design of Nanophotonic Absorbers from Optical Spectra

arXiv:2608.11860v1 Announce Type: cross Abstract: Data-driven inverse design enables efficient generation of nanophotonic structures with prescribed optical responses, but spectrum-to-geometry mapping

Un-EVIMO: Unsupervised Event-Based Independent Motion Segmentation

arXiv:2312.00114v3 Announce Type: replace Abstract: Event cameras are a novel type of biologically inspired vision sensor known for their high temporal resolution, high dynamic range, and low power co

researcharxiv-cs-cv

Uncertainty as a Planning Signal: Multi-Turn Decision Making for Goal-Oriented Conversation

arXiv:2604.03924v2 Announce Type: replace-cross Abstract: Goal-oriented conversational systems require making sequential decisions under uncertainty about the user's intent, where the algorithm must b

Uncertainty-Aware and Explainable Ensemble Deep Learning Framework for Multi-Class Skin Lesion Classification

arXiv:2608.11280v1 Announce Type: cross Abstract: Skin cancer diagnosis from dermoscopic images remains challenging due to high intra-class variability, inter-class similarity, class imbalance, and th

Local Ai

UniGround: Universal 3D Visual Grounding via Training-Free Scene Parsing

arXiv:2603.08131v2 Announce Type: replace-cross Abstract: 3D Visual Grounding (3DVG) localizes objects from natural-language descriptions in 3D scenes and is fundamental to embodied AI applications. A

local-aiarxiv-cs-cv

User-Assisted Collaborative Distributed Inference for Efficient QoS-Aware Autoscaling

arXiv:2608.11840v1 Announce Type: cross Abstract: Growing demand for artificial intelligence (AI) inference services requires scalable infrastructure, yet centralized serving costs rise with demand. W

Using BigQuery Graphs with measures for trusted agentic workloads

When enterprises transition from using simple chat assistants to autonomous, agentic workloads, they quickly run into a hard truth: Agents are prone to inaccurate insights when working with directly r

agentsgoogle-cloud-ai

Variable Selection in the Context of AI Fairness

arXiv:2608.11251v1 Announce Type: cross Abstract: Fairness in AI systems has become more important with recent regulatory demands, such as the EU AI Act. Traditional approaches often do not take into

safetyarxiv-cs-ai

Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates

arXiv:2608.11435v1 Announce Type: new Abstract: Forward and inverse modeling of parametric dynamical systems requires surrogate models that are not only accurate for state prediction, but also informa

Video2Track: From Real-World Interaction Videos to Steerable Adversarial Closed-Track Testing for Automated Driving Systems

arXiv:2608.11592v1 Announce Type: new Abstract: Closed-track testing plays a fundamental role in the verification and validation of automated driving systems (ADS), particularly for safety-critical sc

safetyarxiv-cs-ro

A Joint-Distribution Route to Fair Representations with Continuous Sensitive Attributes

arXiv:2608.10470v1 Announce Type: new Abstract: Fair representation learning with a continuous sensitive attribute S requires a representation Z that is statistically independent of S. Existing criter

safetyarxiv-cs-lg

A Systematic Sample Size Analysis of ML-Based Path Loss Prediction for LPWAN

arXiv:2608.11083v1 Announce Type: cross Abstract: Low Power Wide Area Networks like LoRa are increasingly deployed for smart city applications, requiring accurate path loss prediction for effective ne

applicationsarxiv-cs-lg

Accelerated Learning of High Dimensional Functions with a Tensor-Featured Training Network

arXiv:2608.10351v1 Announce Type: new Abstract: In this work we present a method to accelerate the optimization of learning high dimensional functions using deep neural network (DNN). This optimizatio

researcharxiv-cs-lg

Automatic Field-of-View Adjustment for a View-Expansive Microscope via LSTM-Based Gaze and Pipette Motion Interpretation

arXiv:2608.10401v1 Announce Type: cross Abstract: Intracytoplasmic sperm injection (ICSI) operators frequently adjust the field-of-view (FOV) during procedures, which interrupts workflow and increases

researcharxiv-cs-lg

Bandwidth-Efficient Multi-Agent Communication through Information Bottleneck and Vector Quantization

arXiv:2602.02035v2 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning systems deployed in real-world robotics applications face severe communication constraints that significant

Behavioral Inference at Scale: The Fundamental Asymmetry Between Motivations and Belief Systems

arXiv:2509.05624v3 Announce Type: replace-cross Abstract: How much information about an agent's underlying values can be recovered from its observable behavior? This question matters for any approach

Bridging Severe Cross-Modal Misalignment: End-to-End Visible-Infrared Object Detection via Explicit Feature-Domain Affine Registration

model-releasesarxiv-cs-cv

arXiv:2608.10680v1 Announce Type: new Abstract: Visible-infrared object detection relies on complementary RGB and thermal cues, but its performance is often degraded by cross-modal spatial misalignmen

Carefully Considering Culture: Analyzing LLM Alignment in Single- and Multi-Cultural Settings using Cultural Consensus Theory

arXiv:2608.09937v1 Announce Type: new Abstract: Recent work in NLP has probed large language models for their understanding of cultural norms across countries. However, this work typically considers d

safetyarxiv-cs-cl

ChemWorld: Programmable Chemical Worlds for Controlled and Replayable Agent Experimentation

arXiv:2608.10792v1 Announce Type: new Abstract: Autonomous chemistry increasingly depends on environments in which agents can repeatedly act, observe, and adapt.Physical laboratories provide essential

Closing a 17-Year Gap: Algorithmic Detection and Empirical Prevalence of Rank Reversal in Multi-Criteria Decision Analysis

arXiv:2508.00129v2 Announce Type: replace Abstract: Rank Reversal, where the relative order of alternatives changes in ways that violate axioms of rational decision-making, is a well-documented threat

applicationsarxiv-cs-ai

Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design

arXiv:2608.10299v1 Announce Type: new Abstract: Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, s

agentsarxiv-cs-cl

CodeRabbit bags $143M to help companies get a grip on the explosion of AI-generated code

CodeRabbit Inc., the creator of a popular tool that automatically reviews artificial intelligence-generated code, is becoming more ambitious after closing on its latest 143 million Series C round of f

agentssiliconangle

ConRub-Med: Reinforcement Learning with Consensus Rubrics for Open-Ended Medical Question Answering

arXiv:2608.10996v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has been especially effective in mathematics and coding, where answers can be checked automatically. Many

safetyarxiv-cs-cl

Continuous Interaction Diffusion: A Diffusion-Native Runtime for Asynchronous Tool-Augmented Reasoning

arXiv:2608.10438v1 Announce Type: new Abstract: Large language models increasingly rely on external tools to access up-to-date information, perform computation, and interact with the outside world. Fo

ConVAWG: A Retrieval-Grounded Framework for Controlled Synthetic Dialogue Generation in Violence Against Women and Girls

arXiv:2608.11200v1 Announce Type: cross Abstract: Synthetic dialogue generation offers a way to study conversational dynamics in sensitive domains where real data are difficult to access, release, or

applicationsarxiv-cs-ai

Cross-View Feature Matching: Survey, Benchmarking, and Foundation-Model Perspectives

arXiv:2608.11093v1 Announce Type: cross Abstract: Cross-view feature matching aims to establish reliable correspondences across images with large viewpoint variations. Over the past decade, the field

researcharxiv-cs-cv

CurveFP: Rational-Radix Logarithmic Datatypes with Closed Products for Language Models

arXiv:2608.10010v1 Announce Type: new Abstract: Low-precision datatypes reduce language-model cost, but most formats optimize scalar fidelity while leaving the arithmetic induced by their products unc

Deciding When to Switch: E-Processes for Adaptive Minimax Training for Generative Adversarial Nets

arXiv:2608.10096v1 Announce Type: cross Abstract: Modern data science increasingly gives rise to hypothesis-testing problems that are not naturally formulated in terms of parameters within prespecifie

DOCSCHISEL: Adaptive Tool Documentation Optimization Framework for LLM Agents

arXiv:2608.10037v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly rely on external tools to accomplish complex real-world tasks, making tool documentation a critical groundin

DQS: A Low-Budget Query Strategy for Enhancing Unsupervised Data-driven Anomaly Detection Approaches

arXiv:2509.05663v4 Announce Type: replace Abstract: Truly unsupervised approaches for time series anomaly detection are rare in the literature. Those that exist suffer from a poorly set threshold, whi

applicationsarxiv-cs-lg

Dreamer-SAC: Off-Policy Learning in Latent World Models for Sample-Efficient Autonomous Driving

arXiv:2608.10386v1 Announce Type: new Abstract: Sample-efficient reinforcement learning for autonomous driving is often limited by the trade-off between data efficiency and model bias. While world mod

safetyarxiv-cs-lg

Dual Stress: Runtime Safety Monitoring for Safety-Constrained MPC Navigation

arXiv:2608.10791v1 Announce Type: new Abstract: Runtime hazard monitors for autonomous naviga- tion are conventionally built from geometric quantities: predicted clearance, time to collision, and requ

safetyarxiv-cs-ro

DualSpectralCF: Training-Free Sign-Aware Spectral Collaborative Filtering

arXiv:2608.10247v1 Announce Type: cross Abstract: Real-world recommendation platforms routinely collect explicit negative feedback such as 1-star reviews, hate-button clicks, distrust between users, a

applicationsarxiv-cs-lg

E^3mo-Bench: A Scalable Benchmark for Multimodal Evoked and Expressed Emotion Understanding via Bayesian Pairwise Alignment

model-releasesarxiv-cs-cv

arXiv:2608.10796v1 Announce Type: new Abstract: Understanding both expressed and evoked emotions is critical for multimodal large language models (MLLMs) to achieve comprehensive affect-aware interact