Search: “evaluation”

When Seeing Is Not Believing -- A Benchmark for Search-Grounded Video Misinformation Detection

arXiv:2606.04098v1 Announce Type: new Abstract: Video misinformation increasingly operates at the semantic and evidential level: authentic footage may be selectively edited, temporally reordered, spli

4 Jun 2026

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XSSR: Cross-Domain Self-Supervised Representative Selection for Efficient Annotation in Medical Image Segmentation

DGX agent

arXiv:2606.04301v1 Announce Type: new Abstract: Acquiring labeled medical image data is resource-intensive and a challenge further exacerbated in cross-domain scenarios where source and target dataset

model-releasesarxiv-cs-cv

4 Jun 2026

You Only Train Once: Differentiable Subset Selection for Omics Data

arXiv:2512.17678v2 Announce Type: replace-cross Abstract: Selecting compact and informative gene subsets from single-cell transcriptomic data is essential for biomarker discovery, improving interpreta

4 Jun 2026

A Benchmark for Semi-supervised Multi-modal Crowd Counting

arXiv:2606.03646v1 Announce Type: new Abstract: This paper constructs the first benchmark on semi-supervised multi-modal crowd counting. To lay the foundation for this unexplored task, we first formul

A Hybrid Approach For Malware Classification Using Secondary Features Fusion

arXiv:2606.03432v1 Announce Type: cross Abstract: The number of malware (either variant or novel) is rapidly increasing, making malware detection and mitigation a complex problem. One approach to impr

A New Framework for Cybersecurity Refusals in AI Agents

arXiv:2606.02644v1 Announce Type: cross Abstract: Agentic scaffolds have dramatically improved LLM performance on complex, long-horizon tasks, yielding both broad benefits and amplified risks in domai

A Scoping Review of the Ethical Perspectives on Anthropomorphising Large Language Model-Based Conversational Agents

arXiv:2601.09869v2 Announce Type: replace Abstract: Anthropomorphisation -- the phenomenon whereby non-human entities are ascribed human-like qualities -- has become increasingly salient with the rise

Local Ai

A unified multi-task framework enables interpretable chest radiograph analysis

arXiv:2606.03417v1 Announce Type: new Abstract: While multimodal deep learning has advanced medical imaging analysis, existing black-box systems extcolor{black}{may remain confined to isolated tasks,

local-aiarxiv-cs-cv

Act Like a Pathologist: Tissue-Aware Whole Slide Image Reasoning

arXiv:2603.00667v3 Announce Type: replace Abstract: Computational pathology has advanced rapidly in recent years, driven by domain-specific image encoders and growing interest in using vision-language

Local Ai

Agent libOS: A Library-OS-Inspired Runtime for Long-Running, Capability-Controlled LLM Agents

arXiv:2606.03895v1 Announce Type: cross Abstract: Large language model (LLM) agents are evolving from request-response assistants into long-running software actors: they maintain state across model ca

local-aiarxiv-cs-ai

AI Model Extraction Attacks: Bypassing Single-Client Assumptions in Defenses

arXiv:2606.03381v1 Announce Type: cross Abstract: Ensuring the protection of Artificial Intelligence (AI) models deployed in military Command and Control (C2) systems and critical infrastructure is es

Aligning Data-Driven Predictors with Allocation: A Decision-Focused Approach to Survival Analysis

arXiv:2606.02671v1 Announce Type: cross Abstract: Machine learning predictors have become essential tools for guiding automated decision making. However, a major misalignment persists: predictive mode

safetyarxiv-cs-ai

An Attention-Based Denoising Model for Diffusion Weighted Imaging

arXiv:2606.03903v1 Announce Type: new Abstract: Diffusion-weighted imaging (DWI) is used for whole-body cancer screening, but it typically requires a long acquisition time. When the scan time is reduc

Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension

arXiv:2405.03386v2 Announce Type: replace Abstract: Training with noisy class labels impairs neural networks' generalization performance. In this context, mixup is a popular regularization technique t

researcharxiv-cs-lg

Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddings

arXiv:2407.11821v2 Announce Type: replace Abstract: Statistical information is ubiquitous but drawing valid conclusions from it is prohibitively hard. We explain how knowledge graph embeddings can be

Ask When It Pays: Cost-Aware Open-Ended Interaction for Instance Goal Navigation

arXiv:2606.03175v1 Announce Type: new Abstract: Instance Goal Navigation (IGN) requires an embodied agent to find a specific object instance among distractors from an underspecified natural-language d

Applications

Assessing Pause Thresholds for empirical Translation Process Research

arXiv:2604.01410v2 Announce Type: replace Abstract: Text production (and translations) proceeds in the form of stretches of typing, interrupted by keystroke pauses. It is often assumed that fast typin

applicationsarxiv-cs-cl

Assistax: A Multi-Agent Hardware-Accelerated Reinforcement Learning Benchmark for Assistive Robotics

arXiv:2507.21638v2 Announce Type: replace Abstract: The development of reinforcement learning (RL) algorithms has been largely driven by ambitious challenge tasks and benchmarks. Games have dominated

Auditable Climate Risk Intelligence from Fragmented ESG Data: Deterministic Orchestration and Imbalance-Aware Learning for Scope 1-3 Validation

arXiv:2606.02604v1 Announce Type: cross Abstract: ESG and climate risk data remain fragmented across heterogeneous Scope 1, Scope 2, and Scope 3 reporting environments, while conventional validation p

AUDITFLOW: Executable Symbolic Environments for Structured Financial Reporting Verification

arXiv:2606.03031v1 Announce Type: new Abstract: Structured financial audit verification is difficult for language-model agents because correctness depends on structured evidence rather than text alone

Agents

AUGUSTE: Online-Learning dApp for Predictive URLLC Scheduling

arXiv:2606.03664v1 Announce Type: cross Abstract: Ultra Reliable and Low Latency Communications (URLLC) was one of the main motivations behind 5G, with 3GPP advertising 1-10 ms latency targets for app

agentsarxiv-cs-ai

AutoTail-BSFGM: Class-Balance-Aware Fine-Tuning for Chinese Scholarly Text Classification

arXiv:2606.03576v1 Announce Type: new Abstract: Scholarly text classification supports literature organization, subject indexing, and research intelligence, but Chinese scholarly corpora often contain

researcharxiv-cs-cl

BEAST3D: Animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting

arXiv:2606.02937v1 Announce Type: cross Abstract: Multi-view video recordings are increasingly used to capture the 3D movements of animals in experimental settings, yet extracting rich 3D representati

BEV-ODOM2: Enhanced BEV-based Monocular Visual Odometry with PV-BEV Fusion and Dense Flow Supervision for Ground Robots

model-releasesarxiv-cs-ro

arXiv:2509.14636v2 Announce Type: replace Abstract: Scale-consistent ego-motion estimation is fundamental for autonomous ground robots. Bird's-Eye-View (BEV) representation naturally addresses the sca

Beyond Compression: Quantifying Spectral Accessibility in Vision Representations

arXiv:2606.03795v1 Announce Type: new Abstract: Vision-language models map visual features into a shared embedding space through learned projection layers, yet it remains unclear how these transformat

Beyond Semantics: Modeling Factual and Affective Perceptual Experiences from Vision-Language Data

arXiv:2606.03345v1 Announce Type: cross Abstract: We present P-Topics (Perception Topics) modeling, a novel problem for understanding how images are perceived affectively and across cultures. The goal

researcharxiv-cs-cl

Bootstrap Your Generator: Unpaired Visual Editing with Flow Matching

arXiv:2606.03911v1 Announce Type: new Abstract: Modern generative models possess a deep understanding of visual content, yet training them for image editing typically requires massive datasets of pair

Bridging Predictive Uncertainty and Safe Action: Sample-Conditioned Differentiable Planning for Autonomous Driving

arXiv:2606.03296v1 Announce Type: new Abstract: Complex, dynamic, and interactive driving environments pose significant challenges for autonomous driving, primarily due to the pervasive uncertainty of

safetyarxiv-cs-ro

Building Reliable Long-Form Generation via Hallucination Rejection Sampling

arXiv:2606.03628v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable progress in open-ended text generation, yet they remain prone to hallucinating incorrect or unsu

Calibration Data Trade-offs Across Capability Dimensions: Why Multi-Source Mixing Matters for High-Sparsity LLM Pruning

arXiv:2606.03328v1 Announce Type: cross Abstract: Post-training pruning compresses large language models to high sparsity using a small unlabelled calibration set, and recent work has concluded that t

Can Factual Opinions Be Edited (Manipulated) in Large Language Models?

model-releasesarxiv-cs-cl

arXiv:2606.03096v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly integrated into various domains, making knowledge editing techniques crucial yet potentially hazardous. Cu

Characterizing Detectability in 3DGS Poisoning: A Stage-wise Benchmark

arXiv:2606.03499v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has rapidly emerged as a leading representation for real-time novel view synthesis, but recent work shows it is vulnerable

ChatHealthAI: Aligning Electronic Health Record Representations with Large Language Models for Grounded Clinical Reasoning

arXiv:2606.02802v1 Announce Type: new Abstract: Large language models (LLMs) exhibit strong natural-language reasoning abilities for clinical decision support, but struggle to effectively model struct

CoEval: Ranking Language Models for Custom Tasks Without Labeled Data or Trustworthy Benchmarks

arXiv:2606.03650v1 Announce Type: cross Abstract: Choosing or ranking language models for a specific application is hardest when no task-specific labeled data exists, and standard public benchmarks ca

Combining Statistical Features and Deep Encodings for Rehearsal-Based Class-Incremental Time Series Classification

model-releasesarxiv-cs-lg

arXiv:2606.03292v1 Announce Type: cross Abstract: Many systems used in real-world environments require adding new categories and incorporating new information without forgetting what was previously le

Applications

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

CoralBay: A Self-Supervised CT Foundation Model

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

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

model-releasesarxiv-cs-cl

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

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

safetyarxiv-cs-ai

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

safetyarxiv-cs-ai

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

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