Search: “evaluation”

Conditional Hypothesis Generation for LLM-Based Text Analysis with Researcher-Specified Covariates

arXiv:2606.03029v1 Announce Type: cross Abstract: A core goal of computational social science is to discover interpretable differences in how language varies across outcomes of interest, such as polit

applicationsarxiv-cs-ai

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CoralBay: A Self-Supervised CT Foundation Model

DGX agent

arXiv:2606.03888v1 Announce Type: new Abstract: Self-supervised learning has enabled large-scale pre-training on 2D natural images, producing general-purpose visual representations that transfer effec

model-releasesarxiv-cs-cv

3 Jun 2026

Cost-Aware Query Routing in RAG: Empirical Analysis of Retrieval Depth Tradeoffs

arXiv:2606.02581v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) faces a fundamental three-way tension: deeper retrieval improves factual grounding but inflates token costs and e

CourseTimeQA: A Lecture-Video Benchmark and a Latency-Constrained Cross-Modal Fusion Method for Timestamped QA

arXiv:2512.00360v2 Announce Type: replace Abstract: We study timestamped question answering over educational lecture videos under a single-GPU latency/memory budget. Given a natural-language query, th

Hardware

CRAM-ER: Error-Resilient Spintronic Computational Random Access Memory for Scalable In-Memory Computation

arXiv:2606.02781v1 Announce Type: cross Abstract: Deep neural networks (DNNs) have achieved state-of-the-art performance across diverse domains. However, typical Von Neumann compute paradigms face sev

hardwarearxiv-cs-ai

CropCraft: A Procedural World Generator for Robotic Simulation of Agricultural Tasks

arXiv:2511.02417v2 Announce Type: replace Abstract: The adoption of agroecological practices in modern agriculture requires robotic systems capable of operating in highly diverse and complex field env

researcharxiv-cs-cv

Cross-Modal Contrastive Learning of ECG and Angiography Representations for Severe Stenosis Classification

arXiv:2606.02605v1 Announce Type: cross Abstract: Coronary artery stenosis is a common cardiovascular disease, with severe, untreated cases posing significant risks of heart attack. Although coronary

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments

arXiv:2506.21129v2 Announce Type: replace-cross Abstract: Autonomous unmanned aerial vehicles (UAVs) increasingly rely on reinforcement learning (RL) for navigation. However, global navigation satelli

D-Judge: Disrupting Multi-Turn Jailbreaks using Semantics-Preserving Output Rewriting

arXiv:2606.02640v1 Announce Type: cross Abstract: Multi-turn jailbreak attacks pose a growing threat to large language model (LLM) safety because they exploit feedback from auxiliary judge models to i

Decoupled Smart Contract Audits: Lightweight LLM Framework via Distillation and Aggregation

arXiv:2606.03128v1 Announce Type: cross Abstract: Smart contracts face critical security challenges that require thorough auditing in decentralized web services. While Large Language Models (LLMs) hav

Demo2Tutorial: From Human Experience to Multimodal Software Tutorials

model-releasesarxiv-cs-cv

arXiv:2606.03951v1 Announce Type: new Abstract: Human experience in digital environments offers a vast, underexplored resource of authentic, untrimmed interactions that contain rich procedural knowled

DiffUNet^2: Bidirectional Prediction, Probabilistic Generation and Collaborative Visual Discovery for Scientific Data

arXiv:2606.03926v1 Announce Type: cross Abstract: Modeling temporal evolution is important to analyzing and reasoning about scientific phenomena, yet most machine learning methods provide deterministi

researcharxiv-cs-lg

DMF: A Deterministic Memory Framework for Conversational AI Agents

arXiv:2606.03463v1 Announce Type: new Abstract: Conversational AI agents require memory systems that are both scalable and semantically coherent across long interaction horizons. Existing approaches r

Do Neural Retrievers Prefer Certain Documents? Evidence of Learned Relevance Priors

arXiv:2606.02814v1 Announce Type: cross Abstract: Neural retrievers are trained to estimate query-document relevance from annotated query-document pairs. Yet annotation protocols may not purely reflec

Do Real-World Datasets Contain Natural Experiments? An Empirical Study Using Causal Feature Selection

arXiv:2606.03251v1 Announce Type: new Abstract: In nature, events that affect some individuals or groups but not others constitute an implicit intervention and are known as natural experiments. For ex

applicationsarxiv-cs-ai

Don't Forget Your Embeddings: Robust Knowledge Erasure via Precise Editing of Embeddings

arXiv:2606.03695v1 Announce Type: new Abstract: As language models are increasingly deployed in real-world applications, the ability to erase specific knowledge from them becomes critical for safety a

dstack-capsule: Pod-Level Remote Attestation for Confidential Workloads on Kubernetes

arXiv:2606.03323v1 Announce Type: cross Abstract: The rise of LLM-as-a-Service and other confidential cloud workloads demands cryptographic proof that user data is processed in a trusted, untampered e

EaDex: A Cross-Embodiment Dexterous Manipulation Framework from Low-Cost Demonstrations

arXiv:2606.03268v1 Announce Type: new Abstract: Dexterous manipulation learning has long been hindered by the high costs of data and training, as pure reinforcement learning typically requires large-s

agentsarxiv-cs-ro

Easy-to-Use Shielding for Reinforcement Learning

arXiv:2606.03804v1 Announce Type: new Abstract: Safe exploration is a key challenge in Reinforcement Learning (RL) that aims to prevent agents from making harmful decisions while exploring their envir

safetyarxiv-cs-lg

Echelon: Auditable Aggregate-Only Language-Model Adaptation Across Privacy Boundaries

arXiv:2606.02958v1 Announce Type: cross Abstract: Cross-organization language-model adaptation increasingly faces hard governance constraints: in many deployments, device-level model state-parameters,

Efficient Hyperparameter Optimization for LLM Reinforcement Learning

arXiv:2606.03073v1 Announce Type: cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is highly sensitive to hyperparameter configurations, making hyperparameter optimization

Efficient Transformer-Based Localized Patch Sampling for Choroid Plexus Segmentation in Multiple Sclerosis

arXiv:2606.03566v1 Announce Type: cross Abstract: Background: The lateral ventricle choroid plexus (LVCP) is gaining recognition as a key imaging biomarker for multiple sclerosis (MS) related to physi

Eliciting Complex Spatial Reasoning in MLLMs through Wide-Baseline Matching

model-releasesarxiv-cs-cv

arXiv:2606.03577v1 Announce Type: new Abstract: Wide-baseline matching (WBM) requires integrating geometric understanding, viewpoint changes, fine-grained perception, and occlusion reasoning, making i

eMEM: A Hybrid Spatio-Temporal Memory System For Embodied Agents

model-releasesarxiv-cs-ro

arXiv:2606.03374v1 Announce Type: new Abstract: We present eMEM (Embodied Memory), a hybrid graph-based memory system for embodied agents operating in physical environments. Current agent memory archi

Enhancing Operational Safety via Agentic Dialogue Hazard Identification Analysis

arXiv:2606.03812v1 Announce Type: new Abstract: Operational safety in high-stakes domains such as industrial process control, autonomous, and safety-critical systems, demand reliable hazard identifica

Experience-Driven Dynamic Exits for LLMs with Reinforcement Learning

arXiv:2606.03113v1 Announce Type: new Abstract: Large Language Models suffer from slow autoregressive inference. While self-speculative decoding accelerates this process, its efficiency is hampered by

Exploring Adversarial Robustness and Safety Alignment in Multilingual Multi-Modal Large Language Models

arXiv:2606.03793v1 Announce Type: new Abstract: Multimodal Large Language Models integrate visual perception into language reasoning, introducing a continuous attack surface susceptible to adversarial

safetyarxiv-cs-cl

Exploring Easy Boosts for Lidar Semantic Scene Completion

arXiv:2606.03992v1 Announce Type: new Abstract: This paper investigates 'free lunch' strategies to boost the performance of lidar semantic scene completion (SSC) without requiring complex architectura

researcharxiv-cs-cv

Extreme Motion Generation via Hybrid Null-Space Control for Straight-Line Path Following

arXiv:2606.03390v1 Announce Type: new Abstract: This work studies ``extreme motion generation'', which aims to maximize the Cartesian path length along a pre-defined trajectory within the manipulator'

safetyarxiv-cs-ro

Face versus Body Tracking for Human-Robot Interaction: An Egocentric Dataset

arXiv:2606.03694v1 Announce Type: cross Abstract: To enable meaningful human-robot interaction (HRI), a robot must continuously assess engagement by consistently tracking users over time. State-of-the

agentsarxiv-cs-cv

Tutorials

FCUS-rPPG: A Fast-Converging Unsupervised Framework for Remote Photoplethysmography via Gradient Oscillation Suppression

arXiv:2606.03050v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact extraction of blood volume pulse (BVP) signals using consumer-grade cameras. Recent unsupervised

tutorialsarxiv-cs-cv

Local Ai

FederatedSkill: Federated Learning for Agentic Skill Evolution

arXiv:2606.03143v1 Announce Type: cross Abstract: Modern LLM agents increasingly rely on skill libraries to handle complex tasks, making skill evolution a primary driver of self-improvement. However,

local-aiarxiv-cs-cl

Few-Shot Prediction for Pulsar Noise with Long Short-Term Memory Network

arXiv:2606.03574v1 Announce Type: cross Abstract: This work proposes a novel solution to predict pulsar timing residuals with limited data, addressing the critical challenge of data scarcity across sp

agentsarxiv-cs-lg

Fixed-Time Dynamic Landing of Quadrotors using Adaptive Unscented Kalman Filtering and Nonlinear Model Predictive Control

arXiv:2606.02658v1 Announce Type: new Abstract: This paper introduces an estimation and control framework for dynamic landing of multi-rotor uncrewed aerial vehicles on moving platforms. The proposed

researcharxiv-cs-ro

Fixing FOLIO and MALLS: Verified Annotations and an LLM-assisted Framework to Focus Human Relabeling

arXiv:2606.02837v1 Announce Type: cross Abstract: Accurate translation from Natural Language to First-Order Logic (NL-to-FOL) underpins neurosymbolic AI systems and Natural Language Inference (NLI), m

Local Ai

FLARE: Fine-Grained Diagnostic Feedback for LLM Code Refinement

arXiv:2606.03852v1 Announce Type: cross Abstract: Large language models often generate code with bugs. Existing methods rely on feedback signals such as test failures and self-critiques to iteratively

local-aiarxiv-cs-ai

FlowGuard: Flow Matching for Identity-Independent Detection of Data-Free Model Stealing Attacks on Energy System Intrusion Detection Systems

arXiv:2606.03430v1 Announce Type: cross Abstract: Artificial Intelligence (AI)-based Intrusion Detection Systems (IDS) deployed in energy infrastructure are vulnerable to model theft attacks, which al

FORGE: Multi-Agent Graduated Exploitation and Detection Engineering

arXiv:2606.03453v1 Announce Type: cross Abstract: Vulnerability disclosure volumes now far exceed organizational assessment capacity, yet three adjacent research communities (proof-of-concept generati

agentsarxiv-cs-ai

Generating the Modal Worker: A Cross-Model Audit of Race and Gender in LLM-Generated Personas Across 41 Occupations

arXiv:2510.21011v3 Announce Type: replace-cross Abstract: As generative AI tools are increasingly used to portray people in professional roles, understanding their racial and gender representational b

GeoDrive-Bench: Benchmarking Region-Specific Multimodal Reasoning in Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2606.02774v1 Announce Type: new Abstract: Vision-language models (VLMs) for autonomous driving have shown promising performance, but their ability to handle region-specific traffic rules remains

Glass Box at Orbit: A Constitutional AI Verification Framework for Trustworthy Autonomous CubeSat Intelligence

arXiv:2606.02967v1 Announce Type: cross Abstract: The space industry is quietly building toward something nobody has fully reckoned with: orbital data centers running thousands of autonomous AI worklo

GLINT: Sparsely Gated Vision-Language Alignment for Fine-Grained Radiology Representations

arXiv:2606.03180v1 Announce Type: cross Abstract: Vision-language models (VLMs) for radiology have emerged as a scalable paradigm by leveraging image-report pairs naturally produced in clinical workfl

safetyarxiv-cs-cl

Grasp-Then-Plan with Failure Attribution: A Closed Two-Stage Framework for Precise and Generalizable Robotic Manipulation

arXiv:2606.03385v1 Announce Type: cross Abstract: In robotic manipulation, the tight coupling between grasping and motion planning often obscures the true source of failure, leading to inefficient tri

Hallucination Is Linearly Decodable from Mid-Layer Hidden States in Quantized LLMs

arXiv:2606.02628v1 Announce Type: cross Abstract: We investigate whether open-source LLMs encode a linearly separable truthfulness signal in their hidden states, and at which network depth this signal

Hallucinations as Orthogonal Noise: Inference-Time Manifold Alignment via Dynamic Contextual Orthogonalization

arXiv:2606.03022v1 Announce Type: cross Abstract: Hallucination in Large Language Models (LLMs), characterized by the generation of content inconsistent with contextual facts or logical constraints --

Hierarchical Federated Learning with Dynamic Clustering and Adaptive Regularization for Robust Infrastructure Inspection

arXiv:2606.03084v1 Announce Type: new Abstract: The deployment of data-driven computer vision models for structural health monitoring (SHM) is heavily constrained by the data silo dilemma due to strin

applicationsarxiv-cs-cv

High-Dimensional Latents Should Be Diagnosed Through Phase Structure

arXiv:2606.02600v1 Announce Type: cross Abstract: We study autoencoder and variational-autoencoder latent spaces through the lens of spin-glass theory. The paper has two components. First, we formaliz

applicationsarxiv-cs-lg

Hint-Guided Diversified Policy Optimization for LLM Reasoning

arXiv:2606.03021v1 Announce Type: new Abstract: Recent developments in Large Language Models (LLMs) have showcased impressive reasoning capabilities, with Reinforcement Learning with Verifiable Reward

safetyarxiv-cs-cl