Search: “evaluation”

AUCp: Pseudo-AUC for Inference Model Selection with Unlabeled Validation Data in Abnormality Detection

arXiv:2606.08742v1 Announce Type: new Abstract: Abnormality detection is a crucial yet challenging task in medical image analysis. Distinguishing abnormalities from normal data by learning to reconstr

researcharxiv-cs-cv

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Model Releases

Auditing Proprietary Alignment in Large Language Models: A Comparative Framework Without a Ground-Truth Standard

DGX agent

arXiv:2606.08381v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly released and deployed through opaque development and deployment pipelines, enabling model providers to i

model-releasesarxiv-cs-ai

9 Jun 2026

Automating the Expert Eye: A System-Agnostic Deep Learning Framework for Rare Event Discovery in Imbalanced Force Spectroscopy

arXiv:2606.09541v1 Announce Type: cross Abstract: Single-Molecule Force Spectroscopy (SMFS) provides unprecedented insights into biomolecular mechanics, yet the high-throughput generation of force-ext

Baichuan-M4: A Clinical-Grade Medical Agent System for Continuous Care

arXiv:2606.08982v1 Announce Type: new Abstract: Baichuan-M4 is Baichuan Intelligence's clinical-grade medical large model, designed for continuous care rather than single-turn medical question answeri

Balancing Real and Synthetic Data for CNN-based Masonry Crack Detection

arXiv:2606.08033v1 Announce Type: new Abstract: Cracks are a critical indicator of building health, and early stage identification is fundamental to prevent harmful damages. Advances in deep learning

researcharxiv-cs-cv

Beware of GeeksBearing Gifts: Building True EU Frontier AI Sovereignty

arXiv:2606.07536v1 Announce Type: cross Abstract: Frontier artificial intelligence is reshaping all aspects of society, from economic output or military capability to democratic institutions. The EU i

Beyond Scalar Rewards by Internalizing Reasoning into Score Distributions

arXiv:2606.09076v1 Announce Type: new Abstract: Reward models are central to text-to-image post-training, but visual preference is subjective and better represented as a distribution over rubric score

BlendServe: Optimizing Offline Inference for Auto-regressive Large Models with Resource-aware Batching

arXiv:2411.16102v2 Announce Type: replace Abstract: Offline batch inference, which leverages the flexibility of request batching to achieve higher throughput and lower costs, is becoming more popular

Bridging Traditional Explainability Methods and Multimodal Multilingual Models: An XAI-Based Analysis

arXiv:2606.07533v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) effectively integrate text and audio to interpret context in complex interactive dialogues. However, the inte

Calibration of Structured Ignorance Certificates for Diagnosing Unknown Unknowns in Reasoning Models

arXiv:2606.08571v1 Announce Type: cross Abstract: Large language models frequently fail in a characteristic way: rather than acknowledging ignorance, they produce fluent but incorrect answers to quest

Can Data Work be Reparative?

arXiv:2606.09408v1 Announce Type: cross Abstract: We present an ethnographic study of an alternative approach to data work, developed by a civic-tech initiative that builds datasets for training and b

Tools

Can Voice Agents Handle Bilingual Customers? Benchmarking Frontier ASR on Code-Switched Speech

This paper benchmarks frontier automatic speech recognition (ASR) systems on their ability to handle code-switched speech, where bilingual speakers mix languages within a single conversation. The rese

toolshugging-face

Can You Trust What You See? Human and AI Detection of Synthetic Legal Evidence

arXiv:2606.07613v1 Announce Type: cross Abstract: Visual evidence has long been treated as a reliable form of legal proof, but advances in artificial intelligence (AI) are undermining that assumption.

Local Ai

CANS: Accelerating Multiuser Collaborative Edge Inference via Cooperative Autodidactic NeuroSurgeon

arXiv:2606.09175v1 Announce Type: cross Abstract: Recently, mobile edge computing (MEC)-enabled collaborative deep neural network (DNN) inference has emerged as a promising approach for delivering int

local-aiarxiv-cs-ai

CARE: A Conformal Safety Layer for Medical Summarization

arXiv:2606.08969v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for medical summarization, but their outputs can omit medically important information and introduce

Causal Agent Replay: Counterfactual Attribution for LLM-Agent Failures

arXiv:2606.08275v1 Announce Type: cross Abstract: When an LLM agent fails -- issues a refund it should not have, calls the wrong tool, leaks data -- existing tooling answers what happened (observabili

Causal Longitudinal Prior-Fitted Networks for Counterfactual Outcome Prediction

arXiv:2606.05797v2 Announce Type: replace Abstract: Longitudinal treatment decisions from multivariate time-series data require predicting potential outcomes under future treatment sequences in the pr

CausShield: Sample Reconstruction-Resilient Vertical FL via Causal Representation Learning

arXiv:2606.08027v1 Announce Type: cross Abstract: Vertical federated learning (VFL) is a distributed learning paradigm that leverages vertically partitioned features across isolated parties without sh

Chain of Flow: ECG-Conditioned 4D Cardiac Cine Generation from Patient-Specific Anatomical Anchor

model-releasesarxiv-cs-cv

arXiv:2602.22919v2 Announce Type: replace Abstract: Cardiac cine magnetic resonance imaging (MRI) is central to functional cardiac assessment, yet a full current cine sequence may not always be direct

CheXanatomy: Anatomy-Aware Vision-Language Modeling for Chest Radiographs

arXiv:2606.08420v1 Announce Type: new Abstract: Vision-language models (VLMs) pretrained on large-scale image-text pairs demonstrate strong image-level understanding, but are primarily optimized for g

Chiaroscuro Attention: Spending Compute in the Dark

arXiv:2606.08327v1 Announce Type: cross Abstract: Standard transformers apply self-attention uniformly at every layer and token, regardless of whether the input requires dynamic cross-token interactio

CineDance: Towards Next-Generation Multi-Shot Long-Form Cinematic Audio-Video Generation

arXiv:2606.09639v1 Announce Type: new Abstract: The fidelity and structural diversity of training datasets fundamentally determine the capabilities of video generation models. While commercial systems

CodeTaste: Can LLMs Generate Human-Level Code Refactorings?

arXiv:2603.04177v2 Announce Type: replace-cross Abstract: LLM coding agents can generate working code, but their solutions often accumulate complexity, duplication, and architectural debt. Human devel

Component Ablation for Efficient Hybrid Language Model Architectures: Performance, Resilience, and Compression Implications

arXiv:2603.22473v2 Announce Type: replace-cross Abstract: Hybrid language models combine softmax attention with linear-time sequence mechanisms such as state-space or linear-attention layers, but the

Condition-Gated Reasoning for Context-Dependent Biomedical Question Answering

arXiv:2602.17911v3 Announce Type: replace-cross Abstract: Current biomedical question answering (QA) systems often assume that medical knowledge applies uniformly, yet real-world clinical reasoning is

Conditional Random Ordered Transport Spaces

arXiv:2606.08113v1 Announce Type: new Abstract: A small Wasserstein distance does not certify that a transformation is admissible. In evidence-constrained, semantic, causal, physical, monotone, or ris

Constrained user-item allocation for e-commerce marketing campaigns

arXiv:2606.09623v1 Announce Type: new Abstract: When running marketing campaigns, retailers must decide which products to promote and which users to target. These decisions are inherently coupled: eff

safetyarxiv-cs-lg

ContextShift: A Controlled Benchmark for Context Dependence in Object Detection

model-releasesarxiv-cs-cv

arXiv:2606.09495v1 Announce Type: new Abstract: Modern object detectors achieve strong performance on standard benchmarks, yet their robustness to contextual variation remains insufficiently understoo

Local Ai

Continuous Language Diffusion as a Decoder-Interface Problem

arXiv:2606.08810v1 Announce Type: cross Abstract: Gaussian-corrupted sentence embeddings have no direct linguistic interpretation, yet continuous diffusion language models can generate fluent text fro

local-aiarxiv-cs-lg

Convolutional Sparse Coding via the Locally Competitive Algorithm on Loihi 2

arXiv:2606.08584v1 Announce Type: new Abstract: Sparse coding provides a principled framework for signal representation by expressing an input as a linear combination of only a small number of basis f

Cooperative Long Rope Skipping via Multi-Agent Reinforcement Learning

arXiv:2606.08064v1 Announce Type: new Abstract: Humans exhibit remarkable motor agility, enabling a wide range of dynamic skills such as running and jumping, which highlights the great potential of hu

safetyarxiv-cs-ro

CoSeP: Complementary Separability Pruning via Class-Separability Clustering

arXiv:2505.13225v2 Announce Type: replace Abstract: Neural network pruning aims to compress models for efficient deployment, yet two fundamental challenges remain. First, many methods rely on per-comp

researcharxiv-cs-cv

CoVEBench: Can Video Editing Models Handle Complex Instructions?

arXiv:2606.08415v1 Announce Type: cross Abstract: While recent text-guided video editing models excel at elementary tasks (e.g., style transfer, object insertion), real-world user requests are highly

CRANE: Knowledge Editing for Reasoning MLLMs

model-releasesarxiv-cs-cv

arXiv:2606.09033v1 Announce Type: new Abstract: The emergence of reasoning multimodal large language models (MLLMs), which generate explicit chain-of-thought (CoT) reasoning before producing answers,

Data Agents Under Attack: Vulnerabilities in LLM-Driven Analytical Systems

arXiv:2606.08661v1 Announce Type: cross Abstract: Data agents integrate LLM-driven reasoning with relational data access, executable analytical tools, and multi-step workflow orchestration, making the

Data-driven discovery of governing differential equations across physical systems

arXiv:2606.09638v1 Announce Type: new Abstract: Differential equations play a critical role in scientific discovery because they provide a mathematical framework to describe the behaviour of physical

De novo molecular generation with optical property preconditioning at the token level

arXiv:2606.08221v1 Announce Type: new Abstract: Designing OLED molecules with targeted optical properties remains challenging due to the scarcity of high-quality data and the limited reliability of co

Dealing with Annotator Disagreement in Hate Speech Classification

arXiv:2502.08266v3 Announce Type: replace-cross Abstract: Hate speech detection is a crucial task, especially on social media where harmful content can spread quickly. Collecting social media content

Declarative Outcome-Conformant Synthesis: Exact, Closed-Form Specification Satisfaction and a Conformance Benchmark

arXiv:2606.08736v1 Announce Type: new Abstract: We study a capability the dominant paradigm in synthetic tabular data does not provide: exact satisfaction of a declared analytical outcome with no sour

Decoupling Semantics and Logic: A Training-Free Coarse-to-Fine Pipeline for Video Retrieval-Augmented Generation

arXiv:2606.07924v1 Announce Type: cross Abstract: This paper presents our system description for the 2nd Workshop on Multimodal Augmented Generation via MultimodAl Retrieval (MAGMaR). Addressing the c

Decoupling the 'What' and 'Where' With Polar Coordinate Positional Embeddings

arXiv:2509.10534v3 Announce Type: replace-cross Abstract: The attention mechanism in a Transformer architecture matches key to query based on both content -- the what -- and position in a sequence --

Decoy-Calibrated Failure Audits for Language Models

arXiv:2606.09046v1 Announce Type: new Abstract: Useful audits reveal not only how often a model fails, but also where its failures concentrate. An auditor may test many candidate explanations: long in

Deep Tree Tensor Networks

arXiv:2502.09928v2 Announce Type: replace-cross Abstract: Originating in quantum physics, tensor networks (TNs) have been widely adopted as exponential machines and parametric decomposers for recognit

Agents

DeltaBox: Scaling Stateful AI Agents with Millisecond-Level Sandbox Checkpoint/Rollback

arXiv:2605.22781v2 Announce Type: replace-cross Abstract: LLM-powered AI agents require high-frequency state exploration (e.g., test-time tree search and reinforcement learning), relying on rapid chec

agentsarxiv-cs-ai

Deterministic Execution of ROS~2 Applications via Lingua Franca

arXiv:2606.09203v1 Announce Type: new Abstract: The Robot Operating System~2 (ROS 2) is a widely used middleware for robotic systems, characterized by a publish-subscribe (pub-sub) communication mecha

researcharxiv-cs-ro

Deterministic Integrity Gates for LLM-Assisted Clinical Manuscript Preparation: An Auditable Biomedical Informatics Architecture

arXiv:2606.09500v1 Announce Type: new Abstract: Objective. Large language models (LLMs) increasingly draft clinical research manuscripts, but their fluency can hide fabricated citations, numbers that

DexPIE: Stable Dexterous Policy Improvement from Real-World Experience

arXiv:2606.09615v1 Announce Type: cross Abstract: Dexterous manipulation presents substantial challenges for imitation learning due to its high-dimensional action space and complex contact-rich dynami

Differentially Private Range Subgraph Counting

arXiv:2606.08179v1 Announce Type: cross Abstract: Subgraph counting is a fundamental problem in graph analysis. Motivated by practical scenarios where graph analytics are performed on subgraphs induce