Search: “evaluation”

Debug2Fix: Can Interactive Debugging Help Coding Agents Fix More Bugs?

arXiv:2602.18571v2 Announce Type: replace-cross Abstract: While significant progress has been made in automating various aspects of software development through coding agents, there is still significa

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Decomposed Trust: Privacy, Adversarial Robustness, Ethics, and Fairness in Low-Rank LLMs

DGX agent

arXiv:2511.22099v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have driven major advances across domains, yet their massive size hinders deployment in resource-constrained sett

safetyarxiv-cs-ai

22 Apr 2026

DeltaSeg: Tiered Attention and Deep Delta Learning for Multi-Class Structural Defect Segmentation

arXiv:2604.18745v1 Announce Type: new Abstract: Automated segmentation of structural defects from visual inspection imagery remains challenging due to the diversity of damage types, extreme class imba

researcharxiv-cs-cv

Denoising, Fast and Slow: Difficulty-Aware Adaptive Sampling for Image Generation

arXiv:2604.19141v1 Announce Type: new Abstract: Diffusion- and flow-based models usually allocate compute uniformly across space, updating all patches with the same timestep and number of function eva

safetyarxiv-cs-cv

Detecting Hallucinations in SpeechLLMs at Inference Time Using Attention Maps

arXiv:2604.19565v1 Announce Type: cross Abstract: Hallucinations in Speech Large Language Models (SpeechLLMs) pose significant risks, yet existing detection methods typically rely on gold-standard out

Detection of T-shirt Presentation Attacks in Face Recognition Systems

model-releasesarxiv-cs-cv

arXiv:2604.19365v1 Announce Type: new Abstract: Face recognition systems are often used for biometric authentication. Nevertheless, it is known that without any protective measures, face recognition s

Discrete Tilt Matching

arXiv:2604.18739v1 Announce Type: new Abstract: Masked diffusion large language models (dLLMs) are a promising alternative to autoregressive generation. While reinforcement learning (RL) methods have

researcharxiv-cs-lg

Divide-and-Conquer Approach to Holistic Cognition in High-Similarity Contexts with Limited Data

arXiv:2604.19339v1 Announce Type: new Abstract: Ultra-fine-grained visual categorization (Ultra-FGVC) aims to classify highly similar subcategories within fine-grained objects using limited training s

local-aiarxiv-cs-cv

Do Emotions Influence Moral Judgment in Large Language Models?

arXiv:2604.19125v1 Announce Type: new Abstract: Large language models have been extensively studied for emotion recognition and moral reasoning as distinct capabilities, yet the extent to which emotio

safetyarxiv-cs-cl

Does Self-Consistency Improve the Recall of Encyclopedic Knowledge?

model-releasesarxiv-cs-cl

arXiv:2604.19395v1 Announce Type: new Abstract: While self-consistency is known to improve performance on symbolic reasoning, its effect on the recall of encyclopedic knowledge is unclear due to a lac

Dual Triangle Attention: Effective Bidirectional Attention Without Positional Embeddings

arXiv:2604.18603v1 Announce Type: cross Abstract: Bidirectional transformers are the foundation of many sequence modeling tasks across natural, biological, and chemical language domains, but they are

EgoMotion: Hierarchical Reasoning and Diffusion for Egocentric Vision-Language Motion Generation

arXiv:2604.19105v1 Announce Type: new Abstract: Faithfully modeling human behavior in dynamic environments is a foundational challenge for embodied intelligence. While conditional motion synthesis has

researcharxiv-cs-cv

Enabling Vibration-Based Gesture Recognition on Everyday Furniture via Energy-Efficient FPGA Implementation of 1D Convolutional Networks

arXiv:2510.23156v2 Announce Type: replace-cross Abstract: The growing demand for smart home interfaces has increased interest in non-intrusive sensing methods like vibration-based gesture recognition.

applicationsarxiv-cs-ai

Tutorials

End-to-End Large Portfolio Optimization for Variance Minimization with Neural Networks through Covariance Cleaning

arXiv:2507.01918v3 Announce Type: replace-cross Abstract: We develop a rotation-invariant neural network that provides the global minimum-variance portfolio by jointly learning how to lag-transform hi

tutorialsarxiv-cs-ai

Enhancing Construction Worker Safety in Extreme Heat: A Machine Learning Approach Utilizing Wearable Technology for Predictive Health Analytics

arXiv:2604.19559v1 Announce Type: new Abstract: Construction workers are highly vulnerable to heat stress, yet tools that translate real-time physiological data into actionable safety intelligence rem

safetyarxiv-cs-ai

Enhancing Unsupervised Keyword Extraction in Academic Papers through Integrating Highlights with Abstract

arXiv:2604.19505v1 Announce Type: cross Abstract: Automatic keyword extraction from academic papers is a key area of interest in natural language processing and information retrieval. Although previou

researcharxiv-cs-cl

EssayCBM: Rubric-Aligned Concept Bottleneck Models for Transparent Essay Grading

arXiv:2512.20817v2 Announce Type: replace Abstract: Automated essay scoring (AES) has advanced significantly with neural language models, yet most systems remain opaque, offering little visibility int

researcharxiv-cs-cl

Agents

EvoMaster: A Foundational Evolving Agent Framework for Agentic Science at Scale

arXiv:2604.17406v2 Announce Type: replace Abstract: The convergence of large language models and agents is catalyzing a new era of scientific discovery: Agentic Science. While the scientific method is

agentsarxiv-cs-ai

Experiments or Outcomes? Probing Scientific Feasibility in Large Language Models

arXiv:2604.18786v1 Announce Type: cross Abstract: Scientific feasibility assessment asks whether a claim is consistent with established knowledge and whether experimental evidence could support or ref

Agents

Explicit Trait Inference for Multi-Agent Coordination

arXiv:2604.19278v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) show promise on complex tasks but remain prone to coordination failures such as goal drift, error cascades, and misa

agentsarxiv-cs-ai

Exploring Language-Agnosticity in Function Vectors: A Case Study in Machine Translation

arXiv:2604.19678v1 Announce Type: new Abstract: Function vectors (FVs) are vector representations of tasks extracted from model activations during in-context learning. While prior work has shown that

applicationsarxiv-cs-cl

Fine-Tuning Code Language Models to Detect Cross-Language Bugs

arXiv:2507.21954v2 Announce Type: replace-cross Abstract: Multilingual programming, which involves using multiple programming languages (PLs) in a single project, is increasingly common due to its ben

FluentAvatar: Flicker-Free Talking-Head Animation via Phoneme-Guided Autoregressive Modeling

model-releasesarxiv-cs-cv

arXiv:2509.12052v3 Announce Type: replace Abstract: Current talking-head generation has gradually shifted from GAN-based methods to diffusion-based paradigms, achieving remarkable progress in visual f

Four-Axis Decision Alignment for Long-Horizon Enterprise AI Agents

arXiv:2604.19457v1 Announce Type: new Abstract: Long-horizon enterprise agents make high-stakes decisions (loan underwriting, claims adjudication, clinical review, prior authorization) under lossy mem

Framelet-Based Blind Image Restoration with Minimax Concave Regularization

arXiv:2604.19314v1 Announce Type: new Abstract: Recovering corrupted images is one of the most challenging problems in image processing. Among various restoration tasks, blind image deblurring has bee

safetyarxiv-cs-cv

Agents

From Craft to Kernel: A Governance-First Execution Architecture and Semantic ISA for Agentic Computers

arXiv:2604.18652v1 Announce Type: cross Abstract: The transition of agentic AI from brittle prototypes to production systems is stalled by a pervasive crisis of craft. We suggest that the prevailing o

agentsarxiv-cs-ai

From Natural Language to Executable Narsese: A Neuro-Symbolic Benchmark and Pipeline for Reasoning with NARS

arXiv:2604.18873v1 Announce Type: new Abstract: Large language models (LLMs) are highly capable at language generation, but they remain unreliable when reasoning requires explicit symbolic structure,

From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing

arXiv:2604.18918v1 Announce Type: cross Abstract: Simulation-based testing of autonomous driving systems (ADS) must uncover realistic and diverse failures in dense, heterogeneous traffic. However, exi

From Proof to Program: Characterizing Tool-Induced Reasoning Hallucinations in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2511.10899v2 Announce Type: replace Abstract: Tool-augmented Language Models (TaLMs) can invoke external tools to solve problems beyond their parametric capacity. However, it remains unclear whe

GaiaFlow: Semantic-Guided Diffusion Tuning for Carbon-Frugal Search

arXiv:2602.15423v3 Announce Type: replace-cross Abstract: As the burgeoning power requirements of sophisticated neural architectures escalate, the information retrieval community has recognized ecolog

researcharxiv-cs-lg

GAIR: Location-Aware Self-Supervised Contrastive Pre-Training with Geo-Aligned Implicit Representations

arXiv:2503.16683v2 Announce Type: replace-cross Abstract: Vision Transformer (ViT) has been widely used in computer vision tasks with excellent results by providing representations for a whole image o

Generative Drifting for Conditional Medical Image Generation

arXiv:2604.19736v1 Announce Type: new Abstract: Conditional medical image generation plays an important role in many clinically relevant imaging tasks. However, existing methods still face a fundament

local-aiarxiv-cs-cv

Ground-Level Near Real-Time Modeling for PM2.5 Pollution Prediction

arXiv:2604.18973v1 Announce Type: cross Abstract: Air pollution is a worldwide public health threat that can cause or exacerbate many illnesses, including respiratory disease, cardiovascular disease,

Handling and Interpreting Missing Modalities in Patient Clinical Trajectories via Autoregressive Sequence Modeling

arXiv:2604.18753v1 Announce Type: cross Abstract: An active challenge in developing multimodal machine learning (ML) models for healthcare is handling missing modalities during training and deployment

applicationsarxiv-cs-ai

Headlines You Won't Forget: Can Pronoun Insertion Increase Memorability?

arXiv:2604.19189v1 Announce Type: new Abstract: For news headlines to influence beliefs and drive action, relevant information needs to be retained and retrievable from memory. In this probing study w

researcharxiv-cs-cl

HELM: Harness-Enhanced Long-horizon Memory for Vision-Language-Action Manipulation

arXiv:2604.18791v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models fail systematically on long-horizon manipulation tasks despite strong short-horizon performance. We show that this

HMR-Net: Hierarchical Modular Routing for Cross-Domain Object Detection in Aerial Images

arXiv:2604.18866v1 Announce Type: new Abstract: Despite advances in object detection, aerial imagery remains a challenging domain, as models often fail to generalize across variations in spatial resol

local-aiarxiv-cs-cv

Human-Machine Co-Boosted Bug Report Identification with Mutualistic Neural Active Learning

arXiv:2604.18862v1 Announce Type: cross Abstract: Bug reports, encompassing a wide range of bug types, are crucial for maintaining software quality. However, the increasing complexity and volume of bu

applicationsarxiv-cs-ai

I have seen some 'What are the best Scheduler/Samplers' questions. And I built a WF to help test them all at once.

local-air-stablediffusion

A user created a workflow to test multiple Stable Diffusion schedulers and samplers simultaneously, addressing common questions about which are optimal . The post likely demonstrates a comparative tes

Implicit Neural Field-Based Process Planning for Multi-Axis Manufacturing: Direct Control over Collision Avoidance and Toolpath Geometry

arXiv:2511.17578v2 Announce Type: replace Abstract: Existing curved-layer-based process planning methods for multi-axis manufacturing address collisions only indirectly and generate toolpaths in a pos

applicationsarxiv-cs-ro

Tutorials

IR-Flow: Bridging Discriminative and Generative Image Restoration via Rectified Flow

arXiv:2604.19680v1 Announce Type: new Abstract: In image restoration, single-step discriminative mappings often lack fine details via expectation learning, whereas generative paradigms suffer from ine

tutorialsarxiv-cs-cv

Iterable launches Nova agent to assist markets in scaling customer personalization

model-releasessiliconangle

Iterable Inc., a customer engagement platform, today announced that it launched an artificial intelligence agent designed to help marketers keep customer interactions relevant as campaigns scale. The

Knowledge-Guided Time-Varying Causal Inference for Arctic Sea Ice Dynamics

arXiv:2601.17647v2 Announce Type: replace-cross Abstract: Quantifying the causal relationship between sea ice thickness and sea surface height (SSH) is essential for understanding the mechanisms drivi

safetyarxiv-cs-ai

Large Language Models Exhibit Normative Conformity

arXiv:2604.19301v1 Announce Type: new Abstract: The conformity bias exhibited by large language models (LLMs) can pose a significant challenge to decision-making in LLM-based multi-agent systems (LLM-

safetyarxiv-cs-ai

Learning Evolution via Optimization Knowledge Adaptation

arXiv:2501.02200v2 Announce Type: replace-cross Abstract: The iterative search process of evolutionary algorithms (EAs) encapsulates optimization knowledge within historical populations and fitness ev

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors

arXiv:2604.19028v1 Announce Type: new Abstract: One of the most challenging problems in graph machine learning is generalizing across graphs with diverse properties. Graph neural networks (GNNs) face

applicationsarxiv-cs-lg

Learning to Credit the Right Steps: Objective-aware Process Optimization for Visual Generation

arXiv:2604.19234v1 Announce Type: new Abstract: Reinforcement learning, particularly Group Relative Policy Optimization (GRPO), has emerged as an effective framework for post-training visual generativ

safetyarxiv-cs-cv

LLMs Know They're Wrong and Agree Anyway: The Shared Sycophancy-Lying Circuit

arXiv:2604.19117v1 Announce Type: new Abstract: When a language model agrees with a user's false belief, is it failing to detect the error, or noticing and agreeing anyway? We show the latter. Across