Search: “evaluation”

HiFA4: Training-Free 4-bit FlashAttention on Ascend HIF4 NPUs for LLM Inference

arXiv:2607.04302v1 Announce Type: cross Abstract: We present HiFA4, a post-training operator-level design that executes both QK^T and PV in FlashAttention as 4-bit HIF4 Cube GEMMs for LLM inference on

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How Far is Too Far? Defining the Distance Threshold for Verification Siamese Networks

DGX agent

arXiv:2607.05329v1 Announce Type: new Abstract: Siamese verification networks are widely used to compare items such as faces, cars, or signatures. In these scenarios, the network is trained to learn a

tutorialsarxiv-cs-lg

7 Jul 2026

How many labels do you need? A decision framework for cross-habitat marine species recognition

arXiv:2607.02559v1 Announce Type: new Abstract: Automated image recognition is increasingly used to scale ecological monitoring beyond manual annotation, yet ecologists lack evidence-based guidance on

How Much of the Routing Gap Is Real? Decomposing the Router-to-Oracle Gap into Reproducible Specialist Advantage and Single-Draw Label Noise

arXiv:2607.03436v1 Announce Type: new Abstract: Routing among large language models (LLMs) promises better quality at lower cost, motivated by the reported gap between learned routers and a per-instan

How Utilitarian Are OpenAI's Models Really? Replicating and Reinterpreting Pfeffer, Krugel, and Uhl (2025)

arXiv:2603.22730v2 Announce Type: replace Abstract: Pfeffer, Krugel, and Uhl (2025) report that OpenAI's reasoning model o1-mini produces more utilitarian responses to the trolley problem and footbrid

safetyarxiv-cs-cl

Human-Centric Reflective Architecture for Human-AI Collaborative Decision-Making

arXiv:2607.03025v1 Announce Type: new Abstract: The use of Large Language Models (LLMs) across diverse areas of human activity-ranging from everyday tasks to safety-critical applications-aims to enhan

safetyarxiv-cs-ai

Agents

HunyuanOCR-1.5: Making Lightweight OCR VLMs Faster and Better

arXiv:2607.04884v1 Announce Type: new Abstract: We present HunyuanOCR-1.5, a lightweight end-to-end OCR-specialized vision-language model. HunyuanOCR unifies document parsing, text spotting, informati

agentsarxiv-cs-cv

Hybrid Deep Learning for Traceability and Classification of Industrial Slate Tiles

arXiv:2607.04811v1 Announce Type: new Abstract: Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and qualit

applicationsarxiv-cs-cv

IBIS: A Hybrid Inception-BiLSTM and SVM Ensemble for Robust Doppler-based Human Activity Recognition

arXiv:2510.24936v3 Announce Type: replace Abstract: Wi-Fi sensing is a leading technology for Human Activity Recognition (HAR), offering a non-intrusive and cost-effective solution for healthcare and

applicationsarxiv-cs-cv

ICR-RL: Deep Reinforcement Learning via In-Context Regression

arXiv:2509.11259v2 Announce Type: replace-cross Abstract: Recent advancements in machine learning have largely been driven by foundation models (FMs) trained on large, diverse datasets, enabling them

Improving LLMs via Validator-to-Generator Alignment

arXiv:2607.02668v1 Announce Type: new Abstract: Large language models are inconsistent: varying prompts or including unrelated information can lead to unexpected changes in model outputs. The generato

safetyarxiv-cs-cl

ImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment

arXiv:2607.05009v1 Announce Type: cross Abstract: Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular assessment, yet many clinical ECG records, particularly

applicationsarxiv-cs-ai

Inclusive KL Gradient Flows: Otto-Wasserstein, Fisher-Rao-Gaussian, and Local-Estimator Dynamics

arXiv:2411.00214v2 Announce Type: replace-cross Abstract: Otto's Wasserstein gradient flow of the inclusive (forward) Kullback--Leibler (KL) divergence offers a principled framework for analyzing stat

researcharxiv-cs-lg

IndustryNav: Exploring Spatial Reasoning of Embodied Agents in Dynamic Industrial Navigation

arXiv:2511.17384v2 Announce Type: replace-cross Abstract: While Visual Large Language Models (VLLMs) show great promise as embodied agents, they continue to face substantial challenges in spatial reas

InFlux++: Real and Synthetic Data for Estimating Dynamic Camera Intrinsics

arXiv:2607.05389v1 Announce Type: new Abstract: Camera intrinsics are vital for recovering 3D structure from 2D video. However, most 3D algorithms assume fixed intrinsics throughout a video, an assump

InfraNet: Quality-Aware RGB Guidance for Efficient Infrared Object Detection

arXiv:2607.03795v1 Announce Type: new Abstract: Robust object detection under adverse visual conditions remains a long-standing challenge for multi-modal perception systems. Existing fusion-based meth

Integrated Graph Search and Model Predictive Control for Smooth and Efficient Path Planning in Autonomous Vehicles

arXiv:2607.04259v1 Announce Type: new Abstract: Path planning is a fundamental component of autonomous vehicles, where achieving safe, comfortable, and dynamically feasible paths while ensuring comput

safetyarxiv-cs-ro

Integrating Neural Encoders in Bayesian Generalized Linear Mixed Models for Multimodal Data

arXiv:2607.04647v1 Announce Type: cross Abstract: Scalable Bayesian inference for generalized linear mixed models (GLMMs) provides uncertainty-aware analysis of correlated longitudinal data, but exist

Integrating Physics-Informed Neural Networks for Safe Reinforcement Learning in a 1-DoF Helicopter System

arXiv:2607.03125v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) offers powerful control for industrial cyber-physical systems (ICPSs), but its 'black-box' exploration risks violating

safetyarxiv-cs-lg

Interaction Techniques that Encourage Longer Prompts Can Improve Psychological Ownership when Writing with AI

arXiv:2507.03670v2 Announce Type: replace-cross Abstract: Writing longer prompts for an AI assistant to generate a story increases psychological ownership, a user's feeling that the writing belongs to

researcharxiv-cs-ai

Internal Pluralism and the Limits of Pairwise Comparisons

arXiv:2607.02672v1 Announce Type: new Abstract: Local pairwise comparisons are a standard tool for learning how people want decision rules to work, e.g., in participatory design or alignment. However,

local-aiarxiv-cs-ai

Interpretable machine learning predicts Parkinson's disease severity using motion-corrected QSM MRI and multiband multiecho fMRI features

arXiv:2607.02553v1 Announce Type: new Abstract: Introduction: Objective neuroimaging biomarkers may improve Parkinson's disease motor assessment by capturing brain variation not directly observable fr

IRG-MotionLLM: Interleaving Motion Generation, Assessment and Refinement for Text-to-Motion Generation

arXiv:2512.10730v2 Announce Type: replace Abstract: Recent advances in motion-aware large language models have shown remarkable promise for jointly learning motion understanding and generation knowled

Is the Geometry Doing the Work? An Operating-Point Audit of Hierarchy in Hyperbolic Vision-Language Models

arXiv:2607.05268v1 Announce Type: new Abstract: Whether a hyperbolic representation model uses its geometry cannot be read off its curvature parameter: what matters is the dimensionless operating poin

Iterative Visual Thinking and the Self-Correction Mirage in VLM Grounding

arXiv:2606.13156v2 Announce Type: replace-cross Abstract: Letting a vision-language model (VLM) think longer at test time has driven much recent progress. A natural way to bring this to spatial ground

safetyarxiv-cs-ai

Jointly Improving Dialect Identification and ASR in Indian Languages using Multimodal Feature Fusion

arXiv:2607.02862v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) and Dialect Identification (DID) are crucial for Indian languages, many of which are low-resource and exhibit signifi

researcharxiv-cs-cl

Agents

kAgent: An execution-guided crash resolution agent for the Linux kernel

arXiv:2504.20412v3 Announce Type: replace-cross Abstract: Fuzzing frameworks like syzkaller have uncovered thousands of Linux kernel crashes, many of which are critical and security-sensitive. However

agentsarxiv-cs-ai

Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI

arXiv:2606.16533v3 Announce Type: replace Abstract: We introduce extbf{Kairos}, a regret-aware native world-action model stack for Physical AI. Kairos is motivated by the view that a physical world mo

local-aiarxiv-cs-ai

KAM-WM: Kinematic Affordance Maps from Latent World Models for Robot Manipulation

arXiv:2607.04652v1 Announce Type: new Abstract: Learning manipulation from few demonstrations requires visual priors that capture not only where to interact, but also how the interaction should begin;

local-aiarxiv-cs-ro

KARMA: Knowledge graph-based Automated Reasoning Materialization and Alignment

arXiv:2607.03166v1 Announce Type: cross Abstract: Template-based contrastive synthesis is scalable, but its candidates often differ only in a few entity-slots while sequence-level optimization spreads

safetyarxiv-cs-ai

KinEMbed: Decoding Kinematics from Electromyography via Cross-Modal Contrastive Learning

arXiv:2607.04820v1 Announce Type: new Abstract: Decoding hand kinematics from surface electromyography (EMG) is a core challenge in wearable biosignal processing with clinical relevance for prosthetic

researcharxiv-cs-lg

Last-Meter Precision Navigation for UAVs: A Diffusion-Refined Aerial Visual Servoing Approach

arXiv:2607.04352v1 Announce Type: new Abstract: In this work, we study the last-meter precision navigation for UAVs, e.g., autonomously reaching a target within the final 10 meters using monocular vis

Learning Flexible Generalization in Video Quality Assessment by Bringing Device and Viewing Condition Distributions

arXiv:2607.04643v1 Announce Type: new Abstract: Video quality assessment (VQA) plays a critical role in optimizing video delivery systems. While numerous objective metrics have been proposed to approx

applicationsarxiv-cs-cv

Learning Only What Valid Adapters Can Express: Subspace-Constrained Adaptation Against Fine-Tuning Poisoning

arXiv:2607.05300v1 Announce Type: new Abstract: Parameter-efficient fine-tuning still leaves a broad space of behavior-changing updates reachable, so a poisoned objective can be represented and optimi

Tutorials

Learning Probabilistic Embeddings for Unsupervised Action Segmentation

arXiv:2607.05263v1 Announce Type: new Abstract: This paper concerns the problem of unsupervised temporal action segmentation for long, untrimmed videos. Recent successful approaches follow a joint rep

tutorialsarxiv-cs-cv

Learning to Generate Multiple Objects from Dense and Occluded Layouts

arXiv:2607.03488v1 Announce Type: new Abstract: Text-to-image diffusion models fail to generate correct object counts in dense scenes, where overlapping instances collapse into indistinguishable struc

Learning When to Attend: Conditional Memory Access for Long-Context LLMs

model-releasesarxiv-cs-cl

arXiv:2603.17484v2 Announce Type: replace Abstract: Language models struggle to generalize beyond pretraining context lengths, limiting long-horizon reasoning and retrieval. Continued pretraining on l

Less Tokens, Better Forecasts: Sparse Residual Routing for Efficient Weather Prediction

arXiv:2607.02829v1 Announce Type: new Abstract: Existing ViT-based weather forecasting models apply uniform computation across all spatial tokens, even though nearby atmospheric grid points often cont

LeukocyteCount: Automatic Identification and Counting for leukocytes using Deep Learning

arXiv:2607.04486v1 Announce Type: cross Abstract: Diagnosing and monitoring diseases frequently involves the analysis of human biological samples, with blood analysis being pivotal. Specifically, leuk

Leveraging Natural Language Processing to Unravel the Mystery of Life: A Review of NLP Approaches in Genomics, Transcriptomics, and Proteomics

arXiv:2506.02212v2 Announce Type: replace-cross Abstract: Natural Language Processing (NLP) has transformed various fields beyond linguistics by applying techniques originally developed for human lang

researcharxiv-cs-ai

Leveraging Pathology Co-occurrence for Test-Time Adaptation in Chest X-Ray Diagnosis

arXiv:2607.03715v1 Announce Type: new Abstract: Medical imaging models often degrade when deployed at new clinical sites due to differences in imaging equipment, protocols, and patient populations. Te

Lightweight Polyp Segmentation via a Gain-Aware Prediction-Space Recursive Controller

arXiv:2607.03062v1 Announce Type: new Abstract: While lightweight polyp segmentation is highly desirable for low-cost deployment, reported performance gains often stem from upgraded backbone encoders,

LiNO: Lifting based multiresolution neural operator

arXiv:2607.02715v1 Announce Type: new Abstract: Recently, neural operators have shown promising outcomes for learning solution operators of differential equations directly from data. This framework le

Lipschitz-Based Robustness Certification Under Floating-Point Execution

arXiv:2603.13334v4 Announce Type: replace-cross Abstract: Lipschitz-based robustness certification bounds a network's sensitivity through concrete numerical computation rather than symbolic reasoning,

LLM-Based Test Oracles: Source-of-Authority Taxonomy -- A Systematic Literature Review

arXiv:2607.05031v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to produce test oracles, the part of a test that decides whether observed behavior is correct. Yet

LLM for the development of FCM

arXiv:2607.04983v1 Announce Type: cross Abstract: This article is about the development of a fuzzy cognitive map using a local large language model. In the light of recent advances it is evident that

local-aiarxiv-cs-ai

Local Constrained Bayesian Optimization

arXiv:2603.07965v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) for high-dimensional constrained problems remains a significant challenge due to the curse of dimensionality. We pr

researcharxiv-cs-lg

Localized LoRA-MoE: Block-wise Low-Rank Experts With Adaptive Routing

arXiv:2607.05114v1 Announce Type: cross Abstract: Large Language Models (LLMs) and high-dimensional perception networks increasingly rely on parameter-efficient fine-tuning (PEFT) to adapt to diverse