Search: “evaluation”

GDPval is one of the most important benchmarks of AI ability because it is based on human expertise. It compares expert human performance to…

model-releasesethan-mollick--x

GDPval is one of the most important benchmarks of AI ability because it is based on human expertise. It compares expert human performance to AI performance using expert human judges who spend an avera

18 Apr 2026

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Research

3D Conditional Image Synthesis of Left Atrial LGE MRI from Composite Semantic Masks

DGX agent

arXiv:2601.04588v2 Announce Type: replace Abstract: Segmentation of the left atrial (LA) wall and endocardium from late gadolinium-enhanced (LGE) MRI is essential for quantifying atrial fibrosis in pa

researcharxiv-cs-cv

17 Apr 2026

A deep learning framework for glomeruli segmentation with boundary attention

arXiv:2604.14263v1 Announce Type: cross Abstract: Accurate detection and segmentation of glomeruli in kidney tissue are essential for diagnostic applications. Traditional deep learning methods primari

A Hierarchical Spatiotemporal Action Tokenizer for In-Context Imitation Learning in Robotics

arXiv:2604.15215v1 Announce Type: new Abstract: We present a novel hierarchical spatiotemporal action tokenizer for in-context imitation learning. We first propose a hierarchical approach, which consi

researcharxiv-cs-ro

A multi-platform LiDAR dataset for standardized forest inventory measurement at long term ecological monitoring sites

model-releasesarxiv-cs-ro

arXiv:2604.14635v1 Announce Type: new Abstract: We present a curated multi-platform LiDAR reference dataset from an instrumented ICOS forest plot, explicitly designed to support calibration, benchmark

A Multimodal Data Collection Framework for Dialogue-Driven Assistive Robotics to Clarify Ambiguities: A Wizard-of-Oz Pilot Study

arXiv:2601.16870v2 Announce Type: replace Abstract: Integrated control of wheelchairs and wheelchair-mounted robotic arms (WMRAs) has strong potential to increase independence for users with severe mo

researcharxiv-cs-ro

Abstract Sim2Real through Approximate Information States

arXiv:2604.15289v1 Announce Type: new Abstract: In recent years, reinforcement learning (RL) has shown remarkable success in robotics when a fast and accurate simulator is available for a given task.

safetyarxiv-cs-ro

Hardware

Accelerate Clean, Modular, Nuclear Reactor Design with AI Physics

NVIDIA released PhysicsNeMo, an open-source AI framework designed to speed up nuclear reactor design through physics-based simulations. The framework uses machine learning-based multiphysics emulators

hardwarenvidia-developer

AD4AD: Benchmarking Visual Anomaly Detection Models for Safer Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2604.15291v1 Announce Type: new Abstract: The reliability of a machine vision system for autonomous driving depends heavily on its training data distribution. When a vehicle encounters significa

Adaptive Layer Selection for Layer-Wise Token Pruning in LLM Inference

arXiv:2601.07667v2 Announce Type: replace Abstract: Due to the prevalence of large language models (LLMs), key-value (KV) cache reduction for LLM inference has received remarkable attention. Among num

AlphaCNOT: Learning CNOT Minimization with Model-Based Planning

arXiv:2604.13812v1 Announce Type: new Abstract: Quantum circuit optimization is a central task in Quantum Computing, as current Noisy Intermediate Scale Quantum devices suffer from error propagation t

An Intelligent Robotic and Bio-Digestor Framework for Smart Waste Management

arXiv:2604.14882v1 Announce Type: cross Abstract: Rapid urbanization and continuous population growth have made municipal solid waste management increasingly challenging. These challenges highlight th

agentsarxiv-cs-lg

An unsupervised decision-support framework for multivariate biomarker analysis in athlete monitoring

arXiv:2604.14534v1 Announce Type: new Abstract: Purpose. Athlete monitoring is constrained by small cohorts, heterogeneous biomarker scales, limited feasibility of repeated sampling, and the lack of r

Bayesian-LoRA: Probabilistic Low-Rank Adaptation of Large Language Models

arXiv:2601.21003v2 Announce Type: replace Abstract: Large Language Models usually put more emphasis on accuracy and therefore, will guess even when not certain about the prediction, which is especiall

Applications

Bayesian Optimization with Gaussian Processes to Accelerate Stationary Point Searches

arXiv:2603.10992v3 Announce Type: replace-cross Abstract: Building local surrogates to accelerate stationary point searches on potential energy surfaces spans decades of effort. Done correctly, surrog

applicationsarxiv-cs-lg

Benchmarking Classical Coverage Path Planning Heuristics on Irregular Hexagonal Grids for Maritime Coverage Scenarios

model-releasesarxiv-cs-ro

arXiv:2604.15202v1 Announce Type: new Abstract: Coverage path planning on irregular hexagonal grids is relevant to maritime surveillance, search and rescue and environmental monitoring, yet classical

Benchmarking Linguistic Adaptation in Comparable-Sized LLMs: A Study of Llama-3.1-8B, Mistral-7B-v0.1, and Qwen3-8B on Romanized Nepali

model-releasesarxiv-cs-cl

arXiv:2604.14171v1 Announce Type: new Abstract: Romanized Nepali, the Nepali language written in the Latin alphabet, is the dominant medium for informal digital communication in Nepal, yet it remains

Tutorials

Beyond Visual Cues: Semantic-Driven Token Filtering and Expert Routing for Anytime Person ReID

arXiv:2604.15090v1 Announce Type: new Abstract: Any-Time Person Re-identification (AT-ReID) necessitates the robust retrieval of target individuals under arbitrary conditions, encompassing both modali

tutorialsarxiv-cs-cv

Bridging the Gap between Learning and Inference for Diffusion-Based Molecule Generation

model-releasesarxiv-cs-lg

arXiv:2411.05472v2 Announce Type: replace Abstract: The paradigm shift toward structure-driven molecule generation has been propelled by advances in deep generative models, such as variational auto-en

Calibrate-Then-Delegate: Safety Monitoring with Risk and Budget Guarantees via Model Cascades

arXiv:2604.14251v1 Announce Type: new Abstract: Monitoring LLM safety at scale requires balancing cost and accuracy: a cheap latent-space probe can screen every input, but hard cases should be escalat

Calibration-Gated LLM Pseudo-Observations for Online Contextual Bandits

arXiv:2604.14961v1 Announce Type: new Abstract: Contextual bandit algorithms suffer from high regret during cold-start, when the learner has insufficient data to distinguish good arms from bad. We pro

CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification

model-releasesarxiv-cs-cl

arXiv:2604.14602v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate toxic content, posing significant risks for safe deployment. Current mitigation strategies often degrad

Certified and accurate computation of function space norms of deep neural networks

arXiv:2603.06431v2 Announce Type: replace-cross Abstract: Neural network methods for PDEs require reliable error control in function space norms. However, trained neural networks can typically only be

researcharxiv-cs-lg

Tutorials

Chain-of-Glimpse: Search-Guided Progressive Object-Grounded Reasoning for Video Understanding

arXiv:2604.14692v1 Announce Type: new Abstract: Video understanding requires identifying and reasoning over semantically discriminative visual objects across frames, yet existing object-agnostic solut

tutorialsarxiv-cs-cv

Challenges in Translating Technical Lectures: Insights from the NPTEL

arXiv:2602.08698v2 Announce Type: replace Abstract: This study examines the practical applications and methodological implications of Machine Translation in Indian Languages, specifically Bangla, Mala

Chaotic CNN for Limited Data Image Classification

arXiv:2604.14645v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) often exhibit poor generalisation in limited training data scenarios due to overfitting and insufficient feature di

Chronological Knowledge Retrieval: A Retrieval-Augmented Generation Approach to Construction Project Documentation

arXiv:2604.14169v1 Announce Type: new Abstract: In large-scale construction projects, the continuous evolution of decisions generates extensive records, most often captured in meeting minutes. Since d

CI-CBM: Class-Incremental Concept Bottleneck Model for Interpretable Continual Learning

arXiv:2604.14519v1 Announce Type: cross Abstract: Catastrophic forgetting remains a fundamental challenge in continual learning, in which models often forget previous knowledge when fine-tuned on a ne

Cognitive Offloading in Agile Teams: How Artificial Intelligence Reshapes Risk Assessment and Planning Quality

arXiv:2604.13814v1 Announce Type: cross Abstract: Recent advances in artificial intelligence (AI) have shown promise in automating key aspects of Agile project management, yet their impact on team cog

Comparison of window shapes and lengths in short-time feature extraction for classification of heart sound signals

arXiv:2604.13567v1 Announce Type: cross Abstract: Heart sound signals, phonocardiography (PCG) signals, allow for the automatic diagnosis of potential cardiovascular pathology. Such classification tas

Constrained Decoding for Safe Robot Navigation Foundation Models

model-releasesarxiv-cs-lg

arXiv:2509.01728v4 Announce Type: replace-cross Abstract: Recent advances in the development of robotic foundation models have led to promising end-to-end and general-purpose capabilities in robotic s

CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas

arXiv:2604.15267v1 Announce Type: cross Abstract: It is increasingly important that LLM agents interact effectively and safely with other goal-pursuing agents, yet, recent works report the opposite tr

safetyarxiv-cs-cl

Cornfigurator: Automated Planning for Any-to-Any Multimodal Model Serving

arXiv:2512.14098v3 Announce Type: replace Abstract: Any-to-Any models are an emerging class of multimodal models that accept combinations of text and multimodal data as input and generate them as outp

researcharxiv-cs-lg

CROP: Token-Efficient Reasoning in Large Language Models via Regularized Prompt Optimization

arXiv:2604.14214v1 Announce Type: new Abstract: Large Language Models utilizing reasoning techniques improve task performance but incur significant latency and token costs due to verbose generation. E

agentsarxiv-cs-cl

Applications

CT-VIR: Continuous-Time Visual-Inertial-Ranging Fusion for Indoor Localization with Sparse Anchors

arXiv:2604.14545v1 Announce Type: new Abstract: Visual-inertial odometry (VIO) is widely used for mobile robot localization, but its long-term accuracy degrades without global constraints. Incorporati

applicationsarxiv-cs-ro

Data Driven Agent Design with Evals & Hill Climbing Algorithms this is a mental model dump i’ve been thinking through + iterating on as we’r…

Data Driven Agent Design with Evals & Hill Climbing Algorithms this is a mental model dump i’ve been thinking through + iterating on as we’re building self-improvement infra around agents: - mining Tr

agentsharrison-chase--x

DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation

arXiv:2602.22839v2 Announce Type: replace Abstract: Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing pre

agentsarxiv-cs-ai

DeepPrune: Parallel Scaling without Inter-trace Redundancy

arXiv:2510.08483v2 Announce Type: replace Abstract: Parallel scaling has emerged as a powerful paradigm to enhance reasoning capabilities in large language models (LLMs) by generating multiple Chain-o

DeTracker: Motion-decoupled Vehicle Detection and Tracking in Unstabilized Satellite Videos

model-releasesarxiv-cs-cv

arXiv:2601.09240v2 Announce Type: replace Abstract: Satellite videos provide continuous observations of surface dynamics but pose significant challenges for multi-object tracking (MOT), especially und

Direct Preference Optimization for Primitive-Enabled Hierarchical RL: A Bilevel Approach

arXiv:2411.00361v4 Announce Type: replace Abstract: Hierarchical reinforcement learning (HRL) enables agents to solve complex, long-horizon tasks by decomposing them into manageable sub-tasks. However

Local Ai

DocVAL: Validated Chain-of-Thought Distillation for Grounded Document VQA

arXiv:2511.22521v2 Announce Type: replace Abstract: Document visual question answering requires models not only to answer questions correctly, but also to precisely localize answers within complex doc

local-aiarxiv-cs-cv

DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling

arXiv:2509.03472v2 Announce Type: replace Abstract: Differentially-Private SGD (DP-SGD) and its adaptive variant DP-Adam are powerful techniques to protect user privacy when using sensitive data to tr

researcharxiv-cs-lg

DPSQL+: A Differentially Private SQL Library with a Minimum Frequency Rule

model-releasesarxiv-cs-lg

arXiv:2602.22699v2 Announce Type: replace-cross Abstract: SQL is the de facto interface for exploratory data analysis; however, releasing exact query results can expose sensitive information through m

Dual Pose-Graph Semantic Localization for Vision-Based Autonomous Drone Racing

arXiv:2604.15168v1 Announce Type: new Abstract: Autonomous drone racing demands robust real-time localization under extreme conditions: high-speed flight, aggressive maneuvers, and payload-constrained

agentsarxiv-cs-ro

Applications

DVFace: Spatio-Temporal Dual-Prior Diffusion for Video Face Restoration

arXiv:2604.14560v1 Announce Type: new Abstract: Video face restoration aims to enhance degraded face videos into high-quality results with realistic facial details, stable identity, and temporal coher

applicationsarxiv-cs-cv

EchoAgent: Towards Reliable Echocardiography Interpretation with 'Eyes','Hands' and 'Minds'

arXiv:2604.05541v2 Announce Type: replace Abstract: Reliable interpretation of echocardiography (Echo) is crucial for assessing cardiac function, which demands clinicians to synchronously orchestrate

agentsarxiv-cs-cv

ECM Contracts: Contract-Aware, Versioned, and Governable Capability Interfaces for Embodied Agents

model-releasesarxiv-cs-ai

arXiv:2604.13097v1 Announce Type: cross Abstract: Embodied agents increasingly rely on modular capabilities that can be installed, upgraded, composed, and governed at runtime. Prior work has introduce

Edge-preserving noise for diffusion models

arXiv:2410.01540v4 Announce Type: replace Abstract: Classical diffusion models typically rely on isotropic Gaussian noise, treating all regions uniformly and overlooking structural information importa