Search: “framework”

Uncertainty Quantification for Cardiac Shape Reconstruction with Deep Signed Distance Functions via MCMC methods

arXiv:2605.07987v1 Announce Type: cross Abstract: Atlas-based approaches allow high-quality, patient-specific shape reconstructions of cardiac anatomy from sparse and/or noisy data such as point cloud

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Uncovering Hidden Systematics in Neural Network Models for High Energy Physics

DGX agent

arXiv:2605.07470v1 Announce Type: new Abstract: Neural networks (NNs) are inherently multidimensional classifiers that learn complex, non-linear relationships among input observables. While their flex

tutorialsarxiv-cs-lg

11 May 2026

Uneven Evolution of Cognition Across Generations of Generative AI Models

arXiv:2605.06815v1 Announce Type: new Abstract: The pursuit of artificial general intelligence necessitates robust methods for evaluating the cognitive capabilities of models beyond narrow task perfor

UniD-Shift: Towards Unified Semantic Segmentation via Interpretable Share-Private Multimodal Decomposition

arXiv:2605.07356v1 Announce Type: new Abstract: Semantic segmentation of large-scale 3D point clouds is crucial for applications such as autonomous driving and urban digital twins. However, the sparse

safetyarxiv-cs-cv

UniV2D: Bridging Visual Restoration and Semantic Perception for Underwater Salient Object Detection

arXiv:2605.07146v1 Announce Type: new Abstract: Underwater salient object detection (USOD) plays a vital role in marine vision tasks but remains fundamentally challenging due to severe visual degradat

tutorialsarxiv-cs-cv

Unsolvability Ceiling in Multi-LLM Routing: An Empirical Study of Evaluation Artifacts

arXiv:2605.07395v1 Announce Type: cross Abstract: Efficient routing across multiple LLMs enables cost-quality tradeoffs by directing queries to the cheapest capable model. Prior work attributes routin

Upper Generalization Bounds for Neural Oscillators

arXiv:2603.09742v2 Announce Type: replace Abstract: Neural oscillators that originate from second-order ordinary differential equations (ODEs) have shown competitive performance in learning mappings b

researcharxiv-cs-lg

VDEGaussian: Video Diffusion Enhanced 4D Gaussian Splatting for Dynamic Urban Scenes Modeling

arXiv:2508.02129v2 Announce Type: replace Abstract: Dynamic urban scene modeling is a rapidly evolving area with broad applications. While current approaches leveraging neural radiance fields or Gauss

safetyarxiv-cs-cv

VecCISC: Improving Confidence-Informed Self-Consistency with Reasoning Trace Clustering and Candidate Answer Selection

arXiv:2605.08070v1 Announce Type: new Abstract: A standard technique for scaling inference-time reasoning is Self-Consistency, whereby multiple candidate answers are sampled from an LLM and the most c

researcharxiv-cs-ai

Velocity-Space 3D Asset Editing

arXiv:2605.07385v1 Announce Type: cross Abstract: Editing a 3D asset locally, modifying a target region while preserving the rest, is a fundamental requirement of native 3D editing. Existing methods e

VesselRW: Weakly Supervised Subcutaneous Vessel Segmentation via Learned Random Walk Propagation

arXiv:2508.06819v3 Announce Type: replace Abstract: The task of parsing subcutaneous vessels in clinical images is often hindered by the high cost and limited availability of ground truth data, as wel

tutorialsarxiv-cs-cv

Video Understanding Reward Modeling: A Robust Benchmark and Performant Reward Models

arXiv:2605.07872v1 Announce Type: cross Abstract: Multimodal reward models have advanced substantially in text and image domains, yet progress in video understanding reward modeling remains severely l

VideoRouter: Query-Adaptive Dual Routing for Efficient Long-Video Understanding

arXiv:2605.05848v2 Announce Type: replace-cross Abstract: Video large multimodal models increasingly face a scalability bottleneck: long videos produce excessively long visual-token sequences, which s

safetyarxiv-cs-ai

VISD: Enhancing Video Reasoning via Structured Self-Distillation

arXiv:2605.06094v2 Announce Type: replace-cross Abstract: Training VideoLLMs for complex reasoning remains challenging due to sparse sequence level rewards and the lack of fine grained credit assignme

safetyarxiv-cs-ai

VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts

model-releasesarxiv-cs-ro

arXiv:2605.06175v2 Announce Type: replace Abstract: Vision-language-action (VLA) models inherit rich visual-semantic priors from pre-trained vision-language backbones, but adapting them to robotic con

We just published the demo video from our latest @DBOS_Inc user group! Big thanks to Adrian Lyjak from @llama_index for walking through the …

We just published the demo video from our latest @DBOS_Inc user group! Big thanks to Adrian Lyjak from @llama_index for walking through the DBOS integration with LlamaAgents, an open-source Python fra

agentsjerry-liu--x

WebClipper: Efficient Evolution of Web Agents with Graph-based Trajectory Pruning

arXiv:2602.12852v2 Announce Type: replace Abstract: Deep Research systems based on web agents have shown strong potential in solving complex information-seeking tasks, yet their search efficiency rema

agentsarxiv-cs-ai

When Stored Evidence Stops Being Usable: Scale-Conditioned Evaluation of Agent Memory

arXiv:2605.07313v1 Announce Type: new Abstract: Memory-agent evaluations report fixed-snapshot accuracy or retrieval quality, but these scores do not show whether evidence remains usable as irrelevant

agentsarxiv-cs-ai

When Symbol Names Should Not Matter: A Logistic Theory of Fresh-Symbol Classification

arXiv:2605.07120v1 Announce Type: new Abstract: Template tasks have emerged as a clean testbed for asking whether transformers reason with abstract symbols rather than concrete token names. We study t

tutorialsarxiv-cs-lg

Who Prices Cognitive Labor in the Age of Agents? Compute-Anchored Wages

arXiv:2605.05558v2 Announce Type: replace Abstract: A natural intuition about the economics of AI agents is that, because agents can be replicated at very low marginal cost, agent labor may be supplie

safetyarxiv-cs-ai

Why Self-Inconsistency Arises in GNN Explanations and How to Exploit It

arXiv:2605.07527v1 Announce Type: cross Abstract: Recent work has observed that explanations produced by Self-Interpretable Graph Neural Networks (SI-GNNs) can be self-inconsistent: when the model is

WorldCup Sampling for Multi-bit LLM Watermarking

arXiv:2602.01752v2 Announce Type: replace Abstract: As large language models (LLMs) generate increasingly human-like text, watermarking has emerged as a promising solution for reliable attribution bey

researcharxiv-cs-cl

XDecomposer: Learning Prior-Free Set Decomposition for Multiphase X-ray Diffraction

arXiv:2605.05866v1 Announce Type: cross Abstract: Multiphase powder X-ray diffraction (PXRD) analysis remains a fundamental bottleneck in structure identification, as real-world synthesis often produc

applicationsarxiv-cs-lg

Hardware

XiYOLO: Energy-Aware Object Detection via Iterative Architecture Search and Scaling

arXiv:2605.06927v1 Announce Type: cross Abstract: Object detection on heterogeneous edge devices must satisfy strict energy, latency, and memory constraints while still providing reliable perception f

hardwarearxiv-cs-ai

A machine that can replace all US white collar work by 2035 will, in no way, be allowed to replace all US white collar work by 2035

applicationsethan-mollick--x

This post argues that despite technological capability, regulatory, economic, and social barriers will prevent AI systems from completely displacing all US white-collar workers by 2035, even if such m

lots of very interesting items here. They talk about pretty much everything from how to accelerate capabilities to concerns about agent safe…

model-releasesclem-delangue--x

lots of very interesting items here. They talk about pretty much everything from how to accelerate capabilities to concerns about agent safety. I'm devastated to inform doomers that 'full stack open s

RVPO: Risk-Sensitive Alignment via Variance Regularization

Current critic-less RLHF methods aggregate multi-objective rewards via an arithmetic mean, leaving them vulnerable to constraint neglect: high-magnitude success in one objective can numerically offset

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Ship code within minutes with the Gemini CLI DevOps Extension

model-releasesgoogle-cloud-ai

With AI coding tools like Antigravity and Claude Code, I can build a working web app in record time. But deploying it? That's where I'd historically lose the rest of the afternoon to Dockerfiles, IAM

Local Ai

v0.30.0-rc7

v0.30.0-rc7 is a release candidate version of Ollama, a platform for running large language models. This pre-release build was recently pushed to Docker repositories and represents testing iterations

local-aiollama-releases

A Comparative Study of PyCaret AutoML and CNN-BiLSTM for Binary Hate Speech Detection in Indonesian Twitter

model-releasesarxiv-cs-cl

arXiv:2605.04885v1 Announce Type: new Abstract: This paper compares a PyCaret AutoML branch and a CNN-BiLSTM branch for binary hate speech detection on Indonesian Twitter using the HS label from the c

A foundation model of vision, audition, and language for in-silico neuroscience

arXiv:2605.04326v1 Announce Type: cross Abstract: Cognitive neuroscience is fragmented into specialized models, each tailored to specific experimental paradigms, hence preventing a unified model of co

researcharxiv-cs-lg

A Hybrid Method for Low-Resource Named Entity Recognition

arXiv:2605.04489v1 Announce Type: cross Abstract: Named Entity Recognition (NER) is a critical component of Natural Language Processing with diverse applications in information extraction and conversa

applicationsarxiv-cs-cl

A Mean Curvature Approach to Boundary Detection: Geometric Insights for Unsupervised Learning

arXiv:2605.04274v1 Announce Type: new Abstract: Accurate boundary detection in high-dimensional data remains a central challenge in unsupervised learning, particularly in the presence of non-linear st

applicationsarxiv-cs-lg

A Provably Convergent and Practical Algorithm for Gromov--Wasserstein Optimal Transport

arXiv:2605.04175v1 Announce Type: new Abstract: Gromov--Wasserstein optimal transport (GWOT) aligns metric measure spaces by matching their within-domain relational structures, but large-scale GWOT re

researcharxiv-cs-lg

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning

arXiv:2509.10784v3 Announce Type: replace-cross Abstract: Medical vision foundation models remain limited in downstream tasks, particularly volumetric medical image segmentation. While fine-tuning on

Adaptive Ensemble Aggregation for Actor-Critics

model-releasesarxiv-cs-lg

arXiv:2507.23501v2 Announce Type: replace Abstract: Ensembles are ubiquitous in off-policy actor-critic learning, yet their efficacy depends critically on how they are aggregated. Current methods typi

Advancing Aesthetic Image Generation via Composition Transfer

arXiv:2605.04609v1 Announce Type: new Abstract: Composition is a cornerstone of visual aesthetics, influencing the appeal of an image. While its principles operate independently of specific content, i

Aes3D: Aesthetic Assessment in 3D Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2605.05155v1 Announce Type: new Abstract: As 3D Gaussian Splatting (3DGS) gains attention in immersive media and digital content creation, assessing the aesthetics of 3D scenes becomes important

ANDRE: An Attention-based Neuro-symbolic Differentiable Rule Extractor

arXiv:2605.04193v1 Announce Type: cross Abstract: Inductive Logic Programming (ILP) aims to learn interpretable first-order rules from data, but existing symbolic and neuro-symbolic approaches struggl

tutorialsarxiv-cs-lg

Anny-Fit: All-Age Human Mesh Recovery

arXiv:2605.04728v1 Announce Type: new Abstract: Recovering 3D human pose and shape from a single image remains a cornerstone of human-centric vision, yet most methods assume adult subjects and optimiz

tutorialsarxiv-cs-cv

Local Ai

ARISE: A Repository-level Graph Representation and Toolset for Agentic Fault Localization and Program Repair

arXiv:2605.03117v1 Announce Type: cross Abstract: Repository-level fault localization (FL) and automated program repair (APR) require an agent to identify the relevant code units across files, follow

local-aiarxiv-cs-ai

ARMATA: Auto-Regressive Multi-Agent Task Assignment

arXiv:2605.04225v1 Announce Type: cross Abstract: Coordinating multi-agent systems over spatially distributed areas requires solving a complex hierarchical problem: first distributing areas among agen

agentsarxiv-cs-ro

ARTA: Adversarial-Robust Multivariate Time--Series Anomaly Detection via Sparsity-Constrained Perturbations

model-releasesarxiv-cs-lg

arXiv:2603.25956v2 Announce Type: replace Abstract: Time-series anomaly detection (TSAD) is a critical component in monitoring complex systems, yet modern deep learning-based detectors are often highl

Automated Large-scale CVRP Solver Design via LLM-assisted Flexible MCTS

arXiv:2605.03339v1 Announce Type: new Abstract: Solving large-scale CVRP (LSCVRP) with hundreds to thousands of nodes remains difficult for even state-of-the-art solvers. Divide-and-conquer can scale

Autonomous Laparoscope Control through Unified Mechanics-Based Representation of Multimodal Intraoperative Information

arXiv:2605.04408v1 Announce Type: new Abstract: Laparoscope-holding robots can provide surgeons with a stable laparoscopic field of view (FOV) and reduce the burden on human assistants. To maintain an

agentsarxiv-cs-ro

Local Ai

b9061

local-aillama-cpp-releases

Release b9061 is a build version of llama.cpp, a C/C++ implementation designed to enable LLM inference with minimal setup and state-of-the-art performance across various hardware platforms . As a spec

BenCSSmark: Making the Social Sciences Count in LLM Research

model-releasesarxiv-cs-cl

arXiv:2605.04886v1 Announce Type: new Abstract: This position paper argues that the under-representation of social science tasks in contemporary LLM benchmarks limits advances in both LLM evaluation a

Beyond Exponential Decay: Rethinking Error Accumulation in Large Language Models

arXiv:2505.24187v2 Announce Type: replace Abstract: The prevailing assumption of an exponential decay in large language model (LLM) reliability with sequence length, predicated on independent per-toke

researcharxiv-cs-cl