Search: “evaluation”

FaCT: Faithful Concept Traces for Explaining Neural Network Decisions

arXiv:2510.25512v2 Announce Type: replace-cross Abstract: Deep networks have shown remarkable performance across a wide range of tasks, yet getting a global concept-level understanding of how they fun

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FAST-DIPS: Adjoint-Free Analytic Steps and Hard-Constrained Likelihood Correction for Diffusion-Prior Inverse Problems

DGX agent

arXiv:2603.01591v2 Announce Type: replace-cross Abstract: Training-free diffusion priors enable inverse-problem solvers without retraining, but for nonlinear forward operators data consistency often r

model-releasesarxiv-cs-ai

15 Apr 2026

Fragile Reconstruction: Adversarial Vulnerability of Reconstruction-Based Detectors for Diffusion-Generated Images

arXiv:2604.12781v1 Announce Type: new Abstract: Recently, detecting AI-generated images produced by diffusion-based models has attracted increasing attention due to their potential threat to safety. A

safetyarxiv-cs-cv

From Attenuation to Attention: Variational Information Flow Manipulation for Fine-Grained Visual Perception

arXiv:2604.12508v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in general visual understanding, they frequently falter in fine

researcharxiv-cs-cv

Fundus Image-based Glaucoma Screening via Retinal Knowledge-Oriented Dynamic Multi-Level Feature Integration

arXiv:2604.12351v1 Announce Type: new Abstract: Automated diagnosis based on color fundus photography is essential for large-scale glaucoma screening. However, existing deep learning models are typica

Generative Anonymization in Event Streams

arXiv:2604.12803v1 Announce Type: new Abstract: Neuromorphic vision sensors offer low latency and high dynamic range, but their deployment in public spaces raises severe data protection concerns. Rece

GoodPoint: Learning Constructive Scientific Paper Feedback from Author Responses

arXiv:2604.11924v1 Announce Type: new Abstract: While LLMs hold significant potential to transform scientific research, we advocate for their use to augment and empower researchers rather than to auto

Graph-Based Chain-of-Thought Pruning for Reducing Redundant Reflections in Reasoning LLMs

arXiv:2604.05643v2 Announce Type: replace Abstract: Extending CoT through RL has been widely used to enhance the reasoning capabilities of LLMs. However, due to the sparsity of reward signals, it can

safetyarxiv-cs-cl

GroupKAN: Efficient Kolmogorov-Arnold Networks via Grouped Spline Modeling

arXiv:2511.05477v2 Announce Type: replace Abstract: Medical image segmentation demands models that achieve high accuracy while maintaining computational efficiency and clinical interpretability. While

GTPBD-MM: A Global Terraced Parcel and Boundary Dataset with Multi-Modality

arXiv:2604.12315v1 Announce Type: new Abstract: Agricultural parcel extraction plays an important role in remote sensing-based agricultural monitoring, supporting parcel surveying, precision managemen

GUIDE: Guided Updates for In-context Decision Evolution in LLM-Driven Spacecraft Operations

arXiv:2603.27306v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have been proposed as supervisory agents for spacecraft operations, but existing approaches rely on static prompt

safetyarxiv-cs-ai

Habitat Classification from Ground-Level Imagery Using Deep Neural Networks

arXiv:2507.04017v3 Announce Type: replace Abstract: Habitat assessment at local scales -- critical for enhancing biodiversity and guiding conservation priorities -- often relies on expert field survey

local-aiarxiv-cs-cv

Agents

Habitat-GS: A High-Fidelity Navigation Simulator with Dynamic Gaussian Splatting

arXiv:2604.12626v1 Announce Type: cross Abstract: Training embodied AI agents depends critically on the visual fidelity of simulation environments and the ability to model dynamic humans. Current simu

agentsarxiv-cs-cv

Tutorials

Heuristic Classification of Thoughts Prompting (HCoT): Integrating Expert System Heuristics for Structured Reasoning into Large Language Models

arXiv:2604.12390v1 Announce Type: new Abstract: This paper addresses two limitations of large language models (LLMs) in solving complex problems: (1) their reasoning processes exhibit Bayesian-like st

tutorialsarxiv-cs-ai

HyperLiDAR: Adaptive Post-Deployment LiDAR Segmentation via Hyperdimensional Computing

arXiv:2604.12331v1 Announce Type: new Abstract: LiDAR semantic segmentation plays a pivotal role in 3D scene understanding for edge applications such as autonomous driving. However, significant challe

local-aiarxiv-cs-cv

Intelligent ROI-Based Vehicle Counting Framework for Automated Traffic Monitoring

arXiv:2604.12470v1 Announce Type: new Abstract: Accurate vehicle counting through video surveillance is crucial for efficient traffic management. However, achieving high counting accuracy while ensuri

Is Sliding Window All You Need? An Open Framework for Long-Sequence Recommendation

arXiv:2604.12372v1 Announce Type: new Abstract: Long interaction histories are central to modern recommender systems, yet training with long sequences is often dismissed as impractical under realistic

researcharxiv-cs-lg

iTeach: In the Wild Interactive Teaching for Failure-Driven Adaptation of Robot Perception

model-releasesarxiv-cs-ro

arXiv:2410.09072v4 Announce Type: replace Abstract: Robotic perception models often fail when deployed in real-world environments due to out-of-distribution conditions such as clutter, occlusion, and

Knowledge Is Not Static: Order-Aware Hypergraph RAG for Language Models

arXiv:2604.12185v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enhances large language models by grounding outputs in retrieved knowledge. However, existing RAG methods including

applicationsarxiv-cs-cl

LaV-CoT: Language-Aware Visual CoT with Multi-Aspect Reward Optimization for Real-World Multilingual VQA

arXiv:2509.10026v4 Announce Type: replace Abstract: As large vision language models (VLMs) advance, their capabilities in multilingual visual question answering (mVQA) have significantly improved. Cha

LLM-Based Automated Diagnosis Of Integration Test Failures At Google

arXiv:2604.12108v1 Announce Type: cross Abstract: Integration testing is critical for the quality and reliability of complex software systems. However, diagnosing their failures presents significant c

applicationsarxiv-cs-ai

LLM-Guided Prompt Evolution for Password Guessing

arXiv:2604.12601v1 Announce Type: cross Abstract: Passwords still remain a dominant authentication method, yet their security is routinely subverted by predictable user choices and large-scale credent

Tutorials

LLM-Guided Task- and Affordance-Level Exploration in Reinforcement Learning

arXiv:2509.16615v2 Announce Type: replace Abstract: Reinforcement learning (RL) is a promising approach for robotic manipulation, but it can suffer from low sample efficiency and requires extensive ex

tutorialsarxiv-cs-ro

LLMs Struggle with Abstract Meaning Comprehension More Than Expected

arXiv:2604.12018v1 Announce Type: cross Abstract: Understanding abstract meanings is crucial for advanced language comprehension. Despite extensive research, abstract words remain challenging due to t

researcharxiv-cs-ai

Local-Splitter: A Measurement Study of Seven Tactics for Reducing Cloud LLM Token Usage on Coding-Agent Workloads

arXiv:2604.12301v1 Announce Type: cross Abstract: We present a systematic measurement study of seven tactics for reducing cloud LLM token usage when a small local model can act as a triage layer in fr

local-aiarxiv-cs-ai

Long-Horizon Plan Execution in Large Tool Spaces through Entropy-Guided Branching

arXiv:2604.12126v1 Announce Type: new Abstract: Large Language Models (LLMs) have significantly advanced tool-augmented agents, enabling autonomous reasoning via API interactions. However, executing m

Agents

Malice in Agentland: Down the Rabbit Hole of Backdoors in the AI Supply Chain

arXiv:2510.05159v4 Announce Type: replace-cross Abstract: While finetuning AI agents on interaction data -- such as web browsing or tool use -- improves their capabilities, it also introduces critical

agentsarxiv-cs-ai

Agents

Mathematics Teachers Interactions with a Multi-Agent System for Personalized Problem Generation

arXiv:2604.12066v1 Announce Type: new Abstract: Large language models can increasingly adapt educational tasks to learners characteristics. In the present study, we examine a multi-agent teacher-in-th

agentsarxiv-cs-ai

Meet Dynamic Individual Preferences: Resolving Conflicting Human Value with Paired Fine-Tuning

arXiv:2604.12479v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have significantly improved the alignment of models with general human preferences. However, a major cha

safetyarxiv-cs-cl

MISID: A Multimodal Multi-turn Dataset for Complex Intent Recognition in Strategic Deception Games

arXiv:2604.12700v1 Announce Type: new Abstract: Understanding human intent in complex multi-turn interactions remains a fundamental challenge in human-computer interaction and behavioral analysis. Whi

Mitigating Shortcut Learning via Feature Disentanglement in Medical Imaging: A Benchmark Study

arXiv:2602.18502v2 Announce Type: replace Abstract: Although deep learning models in medical imaging often achieve excellent classification performance, they can rely on shortcut learning, exploiting

Mixed-Integer vs. Continuous Model Predictive Control for Binary Thrusters: A Comparative Study

arXiv:2603.19796v3 Announce Type: replace-cross Abstract: Binary on/off thrusters are commonly used for spacecraft attitude and position control during proximity operations. However, their discrete na

researcharxiv-cs-ro

MolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization

arXiv:2604.12237v1 Announce Type: cross Abstract: In drug discovery, molecular optimization aims to iteratively refine a lead compound to improve molecular properties while preserving structural simil

safetyarxiv-cs-ai

Multi-Head Residual-Gated DeepONet for Coherent Nonlinear Wave Dynamics

model-releasesarxiv-cs-lg

arXiv:2604.11972v1 Announce Type: new Abstract: Coherent nonlinear wave dynamics are often strongly shaped by a compact set of physically meaningful descriptors of the initial state. Traditional neura

Multilingual Multi-Label Emotion Classification at Scale with Synthetic Data

arXiv:2604.12633v1 Announce Type: new Abstract: Emotion classification in multilingual settings remains constrained by the scarcity of annotated data: existing corpora are predominantly English, singl

researcharxiv-cs-cl

Mutual Information Surprise: Rethinking Unexpectedness in Autonomous Systems

arXiv:2508.17403v3 Announce Type: replace Abstract: A community of researchers appears to think that a machine can be surprised and have introduced various surprise measures, principally the Shannon S

safetyarxiv-cs-lg

Narrative-Driven Paper-to-Slide Generation via ArcDeck

arXiv:2604.11969v1 Announce Type: new Abstract: We introduce ArcDeck, a multi-agent framework that formulates paper-to-slide generation as a structured narrative reconstruction task. Unlike existing m

Narrative over Numbers: The Identifiable Victim Effect and its Amplification Under Alignment and Reasoning in Large Language Models

arXiv:2604.12076v1 Announce Type: cross Abstract: The Identifiable Victim Effect (IVE) - the tendency to allocate greater resources to a specific, narratively described victim than to a statistically

NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Professional Image Quality Assessment (Track 1)

arXiv:2604.12512v1 Announce Type: cross Abstract: In this paper, we present an overview of the NTIRE 2026 challenge on the 3rd Restore Any Image Model in the Wild, specifically focusing on Track 1: Pr

Observing the unobserved confounding through its effects: toward randomized trial-like estimates from real-world survival data

arXiv:2604.12137v1 Announce Type: cross Abstract: Background: Randomized controlled trials (RCTs) are costly, time-consuming, and often infeasible, while treatment-effect estimation from observational

applicationsarxiv-cs-ai

OSC: Hardware Efficient W4A4 Quantization via Outlier Separation in Channel Dimension

arXiv:2604.12782v1 Announce Type: cross Abstract: While 4-bit quantization is essential for high-throughput deployment of Large Language Models, activation outliers often lead to significant accuracy

researcharxiv-cs-ai

PC-MIL: Decoupling Feature Resolution from Supervision Scale in Whole-Slide Learning

arXiv:2604.12100v1 Announce Type: new Abstract: Whole-slide image (WSI) classification in computational pathology is commonly formulated as slide-level Multiple Instance Learning (MIL) with a single g

local-aiarxiv-cs-cv

Physically Accurate Rigid-Body Dynamics in Particle-Based Simulation

model-releasesarxiv-cs-ro

arXiv:2603.14634v3 Announce Type: replace Abstract: Robotics demands simulation that can reason about the diversity of real-world physical interactions, from rigid to deformable objects and fluids. Cu

Pictorial and apictorial polygonal jigsaw puzzles from arbitrary number of crossing cuts

arXiv:2008.07644v3 Announce Type: replace-cross Abstract: Jigsaw puzzle solving, the problem of constructing a coherent whole from a set of non-overlapping unordered visual fragments, is fundamental t

researcharxiv-cs-ai

Poisoning the Inner Prediction Logic of Graph Neural Networks for Clean-Label Backdoor Attacks

arXiv:2603.05004v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have achieved remarkable results in various tasks. Recent studies reveal that graph backdoor attacks can poison t

applicationsarxiv-cs-ai

Policy-Invisible Violations in LLM-Based Agents

arXiv:2604.12177v1 Announce Type: new Abstract: LLM-based agents can execute actions that are syntactically valid, user-sanctioned, and semantically appropriate, yet still violate organizational polic

PolicyLLM: Towards Excellent Comprehension of Public Policy for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2604.12995v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly integrated into real-world decision-making, including in the domain of public policy. Yet, their ability t

PR-MaGIC: Prompt Refinement Via Mask Decoder Gradient Flow For In-Context Segmentation

arXiv:2604.12113v1 Announce Type: cross Abstract: Visual Foundation Models (VFMs) such as the Segment Anything Model (SAM) have significantly advanced broad use of image segmentation. However, SAM and

safetyarxiv-cs-ai