Search: “evaluation”

arXiv:2509.14000v4 Announce Type: replace Abstract: Global Navigation Satellite Systems (GNSS) face growing disruption from intentional jamming, undermining critical infrastructure where precise posit

applicationsarxiv-cs-lg

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Knowledge-Data Dually Driven Paradigm for Accurate Landslide Susceptibility Prediction under Data-Scarce Conditions Using Geomorphic Priors and Tabular Foundation Model

DGX agent

arXiv:2604.25196v1 Announce Type: new Abstract: Landslide susceptibility prediction is critical for geohazard risk assessment and mitigation. Conventional data-driven paradigm achieves high predictive

researcharxiv-cs-lg

29 Apr 2026

Large Language Models Are Effective Human Annotation Assistants, But Not Good Independent Annotators

arXiv:2503.06778v3 Announce Type: replace Abstract: Event annotation is important for identifying market changes, monitoring breaking news, and understanding sociological trends. Although expert annot

Learning from Medical Entity Trees: An Entity-Centric Medical Data Engineering Framework for MLLMs

arXiv:2604.25296v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional

safetyarxiv-cs-cl

Learning with Embedded Linear Equality Constraints via Variational Bayesian Inference

arXiv:2604.24911v1 Announce Type: new Abstract: Machine Learning is becoming more prevalent in science and engineering, but many approaches do not provide meaningful uncertainty estimates and predicti

Local Ai

Leveraging Previous-Traversal Point Cloud Map Priors for Camera-Based 3D Object Detection and Tracking

arXiv:2604.25405v1 Announce Type: new Abstract: Camera-based 3D object detection and tracking are central to autonomous driving, yet precise 3D object localization remains fundamentally constrained by

local-aiarxiv-cs-cv

Magnification-Invariant Image Classification via Domain Generalization and Stable Sparse Embedding Signatures

arXiv:2604.25817v1 Announce Type: new Abstract: Magnification shift is a major obstacle to robust histopathology classification, because models trained on one imaging scale often generalize poorly to

Marco-MoE: Open Multilingual Mixture-of-Expert Language Models with Efficient Upcycling

arXiv:2604.25578v1 Announce Type: new Abstract: We present Marco-MoE, a suite of fully open multilingual sparse Mixture-of-Experts (MoE) models. Marco-MoE features a highly sparse design in which only

minAction.net: Energy-First Neural Architecture Design -- From Biological Principles to Systematic Validation

model-releasesarxiv-cs-lg

arXiv:2604.24805v1 Announce Type: new Abstract: Modern machine learning optimizes for accuracy without explicitly accounting for internal computational cost, even though physical and biological system

Mitigating Coordinate Prediction Bias from Positional Encoding Failures

arXiv:2510.22102v2 Announce Type: replace-cross Abstract: While Multimodal Large Language Models (MLLMs) excel at general vision-language tasks, precise coordinate prediction remains a significant cha

Most pharma agent pilots never make it to production. We’re partnering with @Axtria to close this gap. Built on LangSmith, Axtria’s pharma-n…

Most pharma agent pilots never make it to production. We’re partnering with @Axtria to close this gap. Built on LangSmith, Axtria’s pharma-native AgentOps framework will give life sciences enterprises

agentsharrison-chase--x

Named Entity Recognition of Historical Texts via Large Language Model

arXiv:2508.18090v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated remarkable versatility across a wide range of natural language processing tasks and domains. On

Navigating Global AI Regulation: A Multi-Jurisdictional Retrieval-Augmented Generation System

arXiv:2604.25448v1 Announce Type: new Abstract: Navigating AI regulation across jurisdictions is increasingly difficult for policymakers, legal professionals, and researchers. To address this, we pres

safetyarxiv-cs-cl

Online combinatorial optimization with stochastic decision sets and adversarial losses

arXiv:2604.25269v1 Announce Type: new Abstract: Most work on sequential learning assumes a fixed set of actions that are available all the time. However, in practice, actions can consist of picking su

Optimal UGV-UAV Cooperative Partitioning and Inspection of Shortest Paths

arXiv:2604.25284v1 Announce Type: new Abstract: We study cooperative shortest path planning for an unmanned ground vehicle (UGV) assisted by an unmanned aerial vehicle (UAV) in environments with unkno

researcharxiv-cs-ro

Phase-Associative Memory: Sequence Modeling in Complex Hilbert Space

arXiv:2604.05030v2 Announce Type: replace Abstract: Experiments probing natural language processing by both humans and LLMs suggest that the meaning of a semantic expression is indeterminate prior to

PhyloSDF: Phylogenetically-Conditioned Neural Generation of 3D Skull Morphology via Residual Flow Matching

arXiv:2604.25371v1 Announce Type: cross Abstract: Generating novel, biologically plausible three-dimensional morphological structures is a fundamental challenge in computational evolutionary biology,

Policy Improvement Reinforcement Learning

arXiv:2604.00860v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a central post-training paradigm for improving the reasoning capabilities of large

safetyarxiv-cs-lg

PolyKV: A Shared Asymmetrically-Compressed KV Cache Pool for Multi-Agent LLM Inference

arXiv:2604.24971v1 Announce Type: cross Abstract: We present PolyKV, a system in which multiple concurrent inference agents share a single, asymmetrically compressed KV cache pool. Rather than allocat

Hardware

Practical exposure correction via compensation

arXiv:2212.14245v2 Announce Type: replace Abstract: In computer vision, correcting the exposure level is a fundamental task for enhancing the visual quality of observations with inappropriate lightnes

hardwarearxiv-cs-cv

Praxy Voice: Voice-Prompt Recovery + BUPS for Commercial-Class Indic TTS from a Frozen Non-Indic Base at Zero Commercial-Training-Data Cost

arXiv:2604.25441v1 Announce Type: cross Abstract: Commercial TTS systems produce near-native Indic audio, but the best open-source bases (Chatterbox, Indic Parler-TTS, IndicF5) trail them on measured

Principled Detection of Hallucinations in Large Language Models via Multiple Testing

arXiv:2508.18473v3 Announce Type: replace Abstract: While Large Language Models (LLMs) have emerged as powerful foundational models to solve a variety of tasks, they have also been shown to be prone t

Quantum-Inspired Robust and Scalable SAR Object Classification

arXiv:2604.25755v1 Announce Type: cross Abstract: SAR image classification naturally has to deal with huge noise and a high dynamic range particularly requiring robust classification models. Additiona

Recursive Multi-Agent Systems

arXiv:2604.25917v1 Announce Type: cross Abstract: Recursive or looped language models have recently emerged as a new scaling axis by iteratively refining the same model computation over latent states

agentsarxiv-cs-cl

Representation Paradigms in AI-based 3D Radiological Image Reconstruction: A Systematic Review

arXiv:2504.11349v3 Announce Type: replace Abstract: The demand for high-quality medical imaging in clinical practice and assisted diagnosis has made 3D image reconstruction in radiological imaging a k

ReSim: Reliable World Simulation for Autonomous Driving

arXiv:2506.09981v2 Announce Type: replace Abstract: How can we reliably simulate future driving scenarios under a wide range of ego driving behaviors? Recent driving world models, developed exclusivel

safetyarxiv-cs-cv

Rethinking Layer Redundancy in Large Language Models: Calibration Objectives and Search for Depth Pruning

arXiv:2604.24938v1 Announce Type: cross Abstract: Depth pruning improves the inference efficiency of large language models by removing Transformer blocks. Prior work has focused on importance criteria

Revisiting the Past: Data Unlearning with Model State History

arXiv:2506.20941v3 Announce Type: replace Abstract: Large language models are trained on massive corpora of web data, which may include private data, copyrighted material, factually inaccurate data, o

Robust Graph Matching through Semantic Relationship Generation for SLAM

arXiv:2604.25404v1 Announce Type: new Abstract: Graph-based representations such as Scene Graphs enable localization in structured indoor environments by matching a locally observed graph, constructed

researcharxiv-cs-ro

SARU: A Shadow-Aware and Removal Unified Framework for Remote Sensing Images with New Benchmarks

arXiv:2604.25432v1 Announce Type: new Abstract: Shadows are a prevalent problem in remote sensing imagery (RSI), degrading visual quality and severely limiting the performance of downstream tasks like

SciDER: Scientific Data-centric End-to-end Researcher

arXiv:2603.01421v2 Announce Type: replace-cross Abstract: Automated scientific discovery with large language models is transforming the research lifecycle from ideation to experimentation, yet existin

agentsarxiv-cs-cl

Self-DACE++: Robust Low-Light Enhancement via Efficient Adaptive Curve Estimation

arXiv:2604.25367v1 Announce Type: new Abstract: In this paper, we present Self-DACE++, an improved unsupervised and lightweight framework for Low-Light Image Enhancement (LLIE), building upon our prev

Sensitivity-Based Tube NMPC for Cooperative Aerial Structures Under Parametric Uncertainty

arXiv:2604.25766v1 Announce Type: new Abstract: This paper presents a sensitivity-based tube Nonlinear Model Predictive Control (NMPC) framework for cooperative aerial chains under bounded parametric

researcharxiv-cs-ro

Sketch2Arti: Sketch-based Articulation Modeling of CAD Objects

arXiv:2604.25781v1 Announce Type: new Abstract: Articulation modeling aims to infer movable parts and their motion parameters for a 3D object, enabling interactive animation, simulation, and shape edi

SnapMLA: Efficient Long-Context MLA Decoding via Hardware-Aware FP8 Quantized Pipelining

arXiv:2602.10718v3 Announce Type: replace-cross Abstract: While FP8 attention has shown substantial promise in innovations like FlashAttention-3, its integration into the decoding phase of the DeepSee

SODA-CitrON: Static Object Data Association by Clustering Multi-Modal Sensor Detections Online

arXiv:2602.22243v2 Announce Type: replace Abstract: The online fusion and tracking of static objects from heterogeneous sensor detections is a fundamental problem in robotics, autonomous systems, and

agentsarxiv-cs-ro

Spark Policy Toolkit: Semantic Contracts and Scalable Execution for Policy Learning in Spark

arXiv:2604.25061v1 Announce Type: cross Abstract: Custom policy-learning pipelines in Spark fail for two coupled systems reasons: rowwise Python execution makes inference impractical, and driver-side

safetyarxiv-cs-lg

Spectral bandits

arXiv:2604.25272v1 Announce Type: cross Abstract: Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this work, we study a bandit problem where the payoffs

safetyarxiv-cs-lg

Splatent: Splatting Diffusion Latents for Novel View Synthesis

arXiv:2512.09923v2 Announce Type: replace Abstract: Radiance field representations have recently been explored in the latent space of VAEs that are commonly used by diffusion models. This direction of

The founder’s AI foundation: The top announcements for startups from Next ‘26

model-releasesgoogle-cloud-ai

The momentum is undeniable: the world’s fastest-growing AI startups are building with Google Cloud. Instead of stitching together fragmented point solutions, founders are building their businesses her

'The more you look at chatbots, the more you realize that they were rushed to market with very little consideration for the consequences,' h…

Gary Marcus critiques the rapid deployment of chatbots to market without adequate consideration of potential harms and consequences. The statement reflects concerns about insufficient safety testing a

safetygary-marcus--x

The Surprising Universality of LLM Outputs: A Real-Time Verification Primitive

arXiv:2604.25634v1 Announce Type: cross Abstract: We report a striking statistical regularity in frontier LLM outputs that enables a CPU-only scoring primitive running at 2.6 microseconds per token, w

The Thinking Pixel: Recursive Sparse Reasoning in Multimodal Diffusion Latents

arXiv:2604.25299v1 Announce Type: new Abstract: Diffusion models have achieved success in high-fidelity data synthesis, yet their capacity for more complex, structured reasoning like text following ta

Toward Multimodal Conversational AI for Age-Related Macular Degeneration

arXiv:2604.25720v1 Announce Type: cross Abstract: Despite strong performance of deep learning models in retinal disease detection, most systems produce static predictions without clinical reasoning or

Towards interpretable AI with quantum annealing feature selection

arXiv:2604.25649v1 Announce Type: new Abstract: Deep learning models are used in critical applications, in which mistakes can have serious consequences. Therefore, it is crucial to understand how and

Towards Robust Deep Learning-based Rumex Obtusifolius Detection from Drone Images

arXiv:2604.25316v1 Announce Type: new Abstract: Domain adaptation (DA) addresses the challenge of transferring a machine learning model trained on a source domain to a target domain with a different d

Tutorials

Towards Seamless Lunar Mosaics: Deep Radiometric Normalization for Cross-Sensor Orbital Imagery Using Chandrayaan-2 TMC Data

arXiv:2604.25208v1 Announce Type: new Abstract: Radiometric inconsistencies remain a major challenge in generating seamless lunar mosaics from multi-mission orbital imagery due to variability in illum

tutorialsarxiv-cs-cv

Towards Unified Multi-task EEG Analysis with Low-Rank Adaptation

model-releasesarxiv-cs-lg

arXiv:2604.25131v1 Announce Type: new Abstract: Recent self-supervised pre-training methods for electroencephalogram (EEG) have shown promising results. However, the pre-trained models typically requi