Search: “evaluation”

Spatially Grounded Concept-Based Image Classification

arXiv:2510.04180v2 Announce Type: replace Abstract: Deep neural networks can achieve high accuracy while relying on evidence that is hard to inspect or misaligned with the intended task. Concept Bottl

Stealthy World Model Manipulation via Data Poisoning

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DGX agent

arXiv:2606.18697v2 Announce Type: replace Abstract: Model-based learning agents use learned world models to predict future states, plan actions, and adapt to new environments. However, the process of

researcharxiv-cs-lg

23 Jun 2026

Structured Spectral Graph Representation Learning for Multi-label Abnormality Analysis from 3D CT Scans

arXiv:2510.10779v5 Announce Type: replace Abstract: With the growing volume of CT examinations, there is an increasing demand for automated tools such as organ segmentation, abnormality detection, and

Sub-Billion, Super-Frontier: Small Language Models Rival Zero-Shot Frontier LLMs on General and Literary Relation Extraction

model-releasesarxiv-cs-lg

arXiv:2606.22606v1 Announce Type: cross Abstract: Large language models (LLMs) achieve strong relation extraction (RE), but their computational demands and reliance on proprietary APIs limit deploymen

Subject-Level Unknown-Identity Identification from Leap Motion Controller 2 Hand Landmarks

arXiv:2606.22986v1 Announce Type: new Abstract: This work studies subject recognition from Leap Motion Controller 2 (LMC2) hand landmark data under a subject-level unknown-identity identification prot

Towards Accurate and Robust Surveillance Roadside IVD via Trackletized Audio-Visual Reasoning

arXiv:2606.22299v1 Announce Type: new Abstract: Idling Vehicle Detection (IVD) seeks to determine, at the final frame of a video clip, whether any vehicle is idling, meaning the vehicle is stationary

Using predictive multiplicity to measure individual performance within the AI Act

arXiv:2602.11944v2 Announce Type: replace Abstract: When building AI systems for decision support, one often encounters the phenomenon of predictive multiplicity: a single best model does not exist; i

safetyarxiv-cs-lg

WildBox: A Dataset and Benchmark for Aerial Monocular 3D Detection of African Savanna Wildlife

arXiv:2606.21309v1 Announce Type: new Abstract: We introduce WildBox, a dataset and benchmark for monocular 3D detection of wildlife from drone video, comprising 237,505 3D bounding box annotations ac

The Starter Tier for Google AI Studio explained

model-releasesgoogle-cloud-ai

You've got a working prototype in Google AI Studio. A React frontend, a Node.js backend, maybe a database. Now you want a live URL to share with your team, your users, or a friend who wants to try it.

22 Jun 2026

3-Key-Input: Exploring the Theoretical Minimum Keys for Text Entry

arXiv:2606.11642v1 Announce Type: cross Abstract: How far can we reduce the number of physical keys if we endow an ambiguous keyboard with modern language models? Fewer keys increase hardware design f

researcharxiv-cs-cl

Adversarial Attacks on Learned Policies for Surgical Robotic Tasks

arXiv:2606.11535v1 Announce Type: new Abstract: Learning-based policies are being considered to augment the dexterity of human surgeons in robot-assisted surgery. Can the end-to-end mapping from visua

safetyarxiv-cs-ro

APEX: Automated Prompt Engineering eXpert with Dynamic Data Selection

arXiv:2606.11459v1 Announce Type: cross Abstract: Large Language Models are highly sensitive to prompt formulation, necessitating automatic prompt optimization to unlock their full potential. While ev

Are LLMs Bad at Moral Reasoning?

arXiv:2606.11635v1 Announce Type: cross Abstract: For highly capable AI systems to operate safely in dynamic, open-ended environments, they must be able to identify, understand, and respond to moral r

Automated Mediator for Human Negotiation: Pre-Mediation via a Structured LLM Pipeline

arXiv:2606.11379v1 Announce Type: new Abstract: Pre-mediation, the preparatory phase preceding direct human negotiation, plays a critical role in achieving mutually beneficial agreements, yet is often

agentsarxiv-cs-ai

Benchmarking Large Language Models for Safety Data Extraction

model-releasesarxiv-cs-cl

arXiv:2606.11204v1 Announce Type: new Abstract: Accurate extraction of structured information from Safety Data Sheets (SDS) remains challenging in industrial safety due to heterogeneous document forma

Blind Dexterous Grasping via Real2Sim2Real Tactile Policy Learning

arXiv:2606.11767v1 Announce Type: cross Abstract: Blind grasping with a dexterous hand is a crucial manipulation capability. Nevertheless, learning such tactile-only policies for real robots remains c

safetyarxiv-cs-ai

Bootstrapped Monitoring: Leveraging Transparent Reasoning to Oversee Stronger AI Agents

arXiv:2606.11998v1 Announce Type: new Abstract: Trusted monitoring is a cornerstone of AI control. However, as frontier models grow more capable, the increasing capabilities gap between trusted and un

agentsarxiv-cs-lg

Applications

Bridging the Modality Gap in Forensic Image Retrieval

arXiv:2606.12294v1 Announce Type: new Abstract: Automated image retrieval plays an increasingly critical role in modern forensic analysis, supporting investigative workflows that rely on efficient com

applicationsarxiv-cs-cv

Calibration Drift Under Reasoning: How Chain-of-Thought Budgets Induce Overconfidence in Large Language Models

arXiv:2606.11211v1 Announce Type: cross Abstract: The ability of large language models (LLMs) to express calibrated uncertainty is important for safe deployment. Chain-of-thought (CoT) reasoning is wi

Can AI Reason Like an Urban Planner? Benchmarking Large Language Models Against Professional Judgment

arXiv:2606.11678v1 Announce Type: new Abstract: Problem, Research Strategy, and Findings: The rise of large language models (LLMs) raises a key question for urban planning: which forms of professional

safetyarxiv-cs-cl

CU-Multi: A Dataset for Multi-Robot Collaborative Perception

arXiv:2509.19463v2 Announce Type: replace Abstract: A central challenge for multi-robot systems is fusing independently gathered perception data into a unified representation. Despite progress in Coll

researcharxiv-cs-ro

Energy-Efficient On-Device RAG on a Mobile NPU: System Design and Benchmark on Snapdragon X Elite

model-releasesarxiv-cs-cl

arXiv:2606.11257v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) pipelines are compute-intensive, combining embedding, retrieval, reranking, and large language model (LLM) generati

Explore From Sketch: Accelerating UAV Exploration in Large-scale Environments with Prior Maps

model-releasesarxiv-cs-ro

arXiv:2606.11708v1 Announce Type: new Abstract: Autonomous exploration with UAVs in large-scale, topologically complex environments often suffers from low efficiency due to suboptimal scheduling and d

Finding Sparse Subnetworks in One Training Cycle via Progressive Magnitude-Based Pruning

arXiv:2606.12278v1 Announce Type: new Abstract: Neural network pruning reduces model size by removing less important parameters while aiming to preserve predictive performance. Although the Lottery Ti

Flow Matching with In-Context Priors for Out-of-Distribution Brain Dynamics

arXiv:2606.11833v1 Announce Type: new Abstract: Flow matching and diffusion models enable conditional generation across domains ranging from images to proteins, with recent extensions to out-of-distri

researcharxiv-cs-lg

Local Ai

HAMNO: A Hierarchical Adaptive Multi-scale Neural Operator with Physics-Informed Learning for Dynamical Systems

arXiv:2606.11963v1 Announce Type: new Abstract: Neural operators provide a powerful framework for learning solution mappings of partial differential equations directly in function space. However, many

local-aiarxiv-cs-lg

ICA Lens: Interpreting Language Models Without Training Another Dictionary

arXiv:2606.11722v1 Announce Type: cross Abstract: Finding interpretable directions in language-model representations is critical for understanding and controlling model behavior. Sparse autoencoders (

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context

arXiv:2606.12291v1 Announce Type: new Abstract: Large language models (LLMs) now reach expert-level scores on medical licensing exams, encouraging the assumption that high scores imply safe medical ju

agentsarxiv-cs-cl

MentisOculi: Revealing the Limits of Reasoning with Mental Imagery

arXiv:2602.02465v2 Announce Type: replace Abstract: Frontier models are transitioning from multimodal large language models (MLLMs) that merely ingest visual information to unified multimodal models (

NightFeats @ MMU-RAGent NeurIPS 2025: A Context-Optimized Multi-Agent RAG System for the Text-to-Text Track

arXiv:2606.11199v1 Announce Type: cross Abstract: We present NightFeats, a structured multi-agent retrieval-augmented generation (RAG) system submitted to the MMU-RAGent competition at NeurIPS 2025, w

OmniLoc: A Geometry-Aware Foundation Model for Anchor-Free UE Localization Across Diverse Indoor Environments

model-releasesarxiv-cs-lg

arXiv:2606.11490v1 Announce Type: new Abstract: Indoor localization from wireless measurements remains challenging in large-scale deployments due to substantial variation in building geometry, the set

On the Study of Biometric Spoofing Detection using Deep Learning

arXiv:2606.11505v1 Announce Type: cross Abstract: Biometric systems are increasingly deployed in security applications; however, they remain vulnerable to spoofing attacks, in which attackers exploit

OpenMedReason: Scientific Reasoning Supervision for Medical Vision-Language Models

arXiv:2606.12169v1 Announce Type: cross Abstract: High-stakes clinical use of large vision-language models (LVLMs) requires reasoning that is grounded in visual evidence and clinical knowledge, not ju

Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steering

arXiv:2606.11386v1 Announce Type: cross Abstract: Full-duplex spoken language models (FD-SLMs) enable seamless speech interaction by allowing models to listen and speak simultaneously, yet the interna

Periodic-MAE: Periodic Video Masked Autoencoder for rPPG Estimation

arXiv:2506.21855v2 Announce Type: replace Abstract: In this paper, we propose Periodic-MAE, a self-supervised framework for learning generalizable spatio-temporal representations of periodic physiolog

Applications

Physics-Distilled Neural Network enabled by Large Language Models for Manufacturing Process-Property Predictive Modeling

arXiv:2606.11605v1 Announce Type: cross Abstract: Predicting process-property relationships in manufacturing is often challenged by high experimental costs and the limited interpretability of complex

applicationsarxiv-cs-ai

PRInTS: Reward Modeling for Long-Horizon Information Seeking

arXiv:2511.19314v2 Announce Type: replace Abstract: Information-seeking is a core capability for AI agents, requiring them to gather and reason over tool-generated information across long trajectories

agentsarxiv-cs-ai

Quantifying Subliminal Behavioral Transfer Ratios in Language Model Distillation

arXiv:2606.11270v1 Announce Type: cross Abstract: Distillation of a language model intended to transfer benign behavior to a student model may also transfer undesirable characteristics, if they are pr

SheafStain: Sheaf-Theoretic Schrodinger Bridge for Spatially and Biologically Coherent Virtual Staining

arXiv:2606.11846v1 Announce Type: new Abstract: Current virtual staining approaches offer the potential for time- and cost-efficient biomarker quantification in cancer diagnostics and prognostics. How

SkillJuror: Measuring How Agent Skill Organization Changes Runtime Behavior

arXiv:2606.11543v1 Announce Type: new Abstract: Agent Skills augment large language model (LLM) agents with procedural knowledge at inference time, but current benchmarks rarely distinguish what a Ski

agentsarxiv-cs-ai

Steering the Noise: Turning Random Perturbations into Effective Descent for Memory-Efficient LLM Fine-Tuning

model-releasesarxiv-cs-cl

arXiv:2601.04710v2 Announce Type: replace Abstract: Fine-tuning large language models (LLMs) achieves strong performance but is often limited by the memory overhead of backpropagation. Zeroth-order (Z

SVoT: State-aware Visualization-of-Thought for Spatial Reasoning via Reinforcement Learning

arXiv:2606.11770v1 Announce Type: new Abstract: Spatial reasoning remains a challenge for Multimodal Large Language Models (MLLMs), as it requires reliable multi-hop inference over both intermediate s

safetyarxiv-cs-ai

SwiftCTS: Fast Cross-Design Prediction and Pareto Optimization of Clock Tree Metrics via Few-Shot Calibration

model-releasesarxiv-cs-lg

arXiv:2606.11348v1 Announce Type: new Abstract: Clock Tree Synthesis (CTS) is a computationally expensive stage in the physical design flow, requiring iterative EDA tool invocations to navigate a vast

When Poison Fails After Retrieval: Revisiting Corpus Poisoning under Chunking and Reranking Pipelines

arXiv:2606.11265v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are vulnerable to corpus poisoning attacks that manipulate downstream model outputs through malicious kno

A History-Aware Visually Grounded Critic for Computer Use Agents

arXiv:2606.11078v1 Announce Type: new Abstract: Various test-time interventions for Computer Use Agents (CUAs), including critic models, have been developed to improve performance through pre-executio

A Systematic Approach for Selecting Trajectories for Data Augmentation

arXiv:2606.10938v1 Announce Type: new Abstract: Trajectory data augmentation is a promising approach to mitigate data scarcity in machine learning applications, but its utility has been limited by the

researcharxiv-cs-lg

Advancing Wood Identification in the Philippines: Utilizing the Xylorix Platform for Efficient AI Model Development and Deployment for Five Key Species

arXiv:2606.10876v1 Announce Type: new Abstract: Illegal logging and timber trade continue to pose significant challenges in the Philippines, where accurate wood species identification is essential for

Agentic Hybrid RAG for Evidence-Grounded Muon Collider Analysis

arXiv:2606.10381v1 Announce Type: cross Abstract: Muon collider research spans accelerator physics, detector instrumentation, and high-energy phenomenology, with relevant evidence scattered across a r