Search: “models”

GenSplatCodec: Feed-Forward Gaussian Splatting Compression via One-Step Diffusion

arXiv:2607.24403v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting (3DGS) enables scalable scene reconstruction without per-scene optimization, yet produces dense Gaussians that are co

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Grokking on the Weight-Decay Clock: A Rate Hierarchy from Softly Broken Symmetries

DGX agent

arXiv:2607.23967v1 Announce Type: new Abstract: Delayed generalization, or grokking, remains poorly understood despite extensive empirical study. We identify an exactly solvable late-time relaxation m

local-aiarxiv-cs-ai

28 Jul 2026

HandSCS: Structural Coordinate Space for Animatable Hand Gaussian Splatting

arXiv:2503.14736v3 Announce Type: replace Abstract: Photorealistic and animatable hand avatars are essential for applications such as AR/VR, gaming, and telepresence. Recent 3D Gaussian Splatting (3DG

HiMemVLN: Enhancing Reliability of Open-Source Zero-Shot Vision-and-Language Navigation with Hierarchical Memory System

arXiv:2603.14807v3 Announce Type: replace Abstract: LLM-based agents have demonstrated impressive zero-shot performance in vision-language navigation (VLN) tasks. However, most zero-shot methods prima

agentsarxiv-cs-cv

How Well Can AI Generate Backlogs from App Mockups?

arXiv:2607.22902v1 Announce Type: new Abstract: Creating sprint backlogs requires considerable effort, as items such as epics, user stories, and tasks can be missed or inconsistently specified. We pro

HyCE-RAG: Hypergraph Chain-of-Evidence Retrieval-Augmented Generation for Explainable Multi-hop Question Answering

arXiv:2607.22597v1 Announce Type: new Abstract: Multi-hop question answering requires systems to retrieve evidence from multiple documents and connect scattered facts into a coherent reasoning process

Interview with Kalle Lyytinen on 'Implications of Theories of Language for Information Systems'

arXiv:2607.23142v1 Announce Type: new Abstract: Over fourty years after the initial publication of 'Implications of Theories of Language for Information Systems' in MIS Quaterly, Lyytinen reflects abo

researcharxiv-cs-cl

Joint Flow Matching for Generator-Consistent Classification

arXiv:2607.23946v1 Announce Type: new Abstract: We introduce Joint Flow Matching (JFM), a training framework for continuous normalising flows over multiple variables. Standard flow matching transports

researcharxiv-cs-lg

KAP: Bridging the Knowledge Selection-Runtime Consumption Gap in LLM Systems

arXiv:2607.24260v1 Announce Type: new Abstract: Modern LLM systems increasingly rely on knowledge-selection processes that produce high-value structured priors, such as ranked evidence, graph topology

safetyarxiv-cs-lg

Label-free Industrial Fault Detection via Adversarial Inverse Reinforcement Learning: A System for Run-to-Failure Prognostics

arXiv:2607.22987v1 Announce Type: cross Abstract: Machinery fault detection (MFD) remains heavily reliant on supervised learning, which struggles with the scarcity of fault labels in real-world settin

Tutorials

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones

arXiv:2607.22803v1 Announce Type: cross Abstract: Recovering the 6-DoF pose of the knee bones from a plain radiograph, given the patient's segmented pre-operative CT, turns a routine low-dose image in

tutorialsarxiv-cs-cv

Learning to Optimize at Scale: A Benders Decomposition-TransfORmers Framework for Stochastic Combinatorial Optimization

arXiv:2607.22550v1 Announce Type: cross Abstract: We propose a learning-augmented Benders decomposition framework to solve large-scale two-stage stochastic mixed-integer programs. We focus on the two-

researcharxiv-cs-lg

Learning When to Reason for Text-to-SQL via SFT and DPO

arXiv:2607.22622v1 Announce Type: cross Abstract: Recent Text-to-SQL methods rely heavily on reasoning-centric paradigms such as Chain-of-Thought (CoT), achieving substantial gains on complex benchmar

LithoFormer: A Robust Framework for Stratigraphic Inference via Transformers

arXiv:2607.22804v1 Announce Type: cross Abstract: Accurate geological characterization of subsurface reservoirs from well log data is essential to support projects such as carbon capture and storage (

LLM-based Source Code Compression via Thresholded Symbol Ranking

arXiv:2607.24192v1 Announce Type: cross Abstract: We study the problem of lossless compression of source code, motivated by the storage demands of large-scale software archives, such as Software Herit

researcharxiv-cs-cl

LongStraw: Long-Context RL Beyond 2M Tokens under a Fixed GPU Budget

arXiv:2607.14952v3 Announce Type: replace Abstract: Long-context RL post-training is constrained by the lifetime of state and gradients, not attention cost alone. In GRPO, one multi-million-token prom

safetyarxiv-cs-lg

Loss-Aware Feature-Map Pruning in Convolutional Neural Networks Using Multi-Armed Bandits

arXiv:2607.22564v1 Announce Type: new Abstract: Convolutional neural networks often contain redundant feature maps that increase storage and inference cost. This paper presents a loss-aware feature-ma

Manga Coloring Tool 2

local-air-stablediffusion

Hey everyone! 👋 I'm excited to announce the official release of Manga Coloring Tool 2.0, a completely free, local, open-source web application designed to colorize manga pages and chapters effortlessl

Tools

Many AI tools rent intelligence. Kimi K3 on Fireworks is different. Fine-tune it on your own data, serve from US-hosted endpoints, and own t…

Many AI tools rent intelligence. Kimi K3 on Fireworks is different. Fine-tune it on your own data, serve from US-hosted endpoints, and own the weights. Zero data retention. ICYMI yesterday, start buil

toolsfireworks-ai--x

MINT-V2X: A Mobility-Integrated Network Trajectory Dataset for Predictive Resource Management

arXiv:2607.22654v1 Announce Type: new Abstract: Vehicle-to-Everything (V2X) communication systems are based on datasets that not only contain vehicle trajectory data but also wireless network paramete

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization

arXiv:2512.03522v3 Announce Type: replace-cross Abstract: Robots are often required to localize in environments with unknown object classes and semantic ambiguity. However, when performing global loca

applicationsarxiv-cs-cv

Multi-Modal Object Re-Identification with Prompt-S6 and Semantic-Aware Knowledge Guidance

arXiv:2607.23451v1 Announce Type: new Abstract: Multi-modal object Re-Identification (ReID) aims to retrieve specific objects by integrating complementary information from multiple modalities. However

safetyarxiv-cs-cv

Multimodal Domain Generalization for Depression Detection: An Attention-Based BiLSTM Network with Domain-Adversarial Training

arXiv:2607.22794v1 Announce Type: cross Abstract: Automatic depression detection with deep learning has shown promise but often suffers from limited generalization due to domain shift arising from int

safetyarxiv-cs-ai

Mwando: Leveraging AI to Preserve and Teach shiKomori

arXiv:2607.23481v1 Announce Type: new Abstract: This paper presents Mwando, a virtual educational assistant designed to support the teaching and preservation of shiKomori, the language of the Comoros

agentsarxiv-cs-cl

Open weights let builders own and control their stack, and provide flexibility to optimized quality and performance, instead of being locked…

Open weights let builders own and control their stack, and provide flexibility to optimized quality and performance, instead of being locked into a handful of closed platforms. We think that choice is

safetytogether-ai--x

Operator Neural Jump ODEs: L^2-optimal prediction in function spaces

arXiv:2607.23110v1 Announce Type: cross Abstract: In this paper, we study the extension of Neural Jump ODEs to infinite-dimensional function spaces. In particular, the underlying process X now takes v

researcharxiv-cs-lg

Optimizing Transformer Neural Network for Real-Time Outlier Detection on FPGAs

arXiv:2607.22786v1 Announce Type: cross Abstract: In this work, we explore how the inference time of a Transformer Neural Network can be efficiently optimized with applications to real-time anomaly de

ORGAN: Object-Centric Representation Learning using Cycle Consistent Generative Adversarial Networks

arXiv:2603.02063v2 Announce Type: replace Abstract: Although data generation is often straightforward, extracting information from data is more difficult. Object-centric representation learning can ex

applicationsarxiv-cs-cv

Physically Verifiable Evidence and LLM-Based Reporting for Bearing Fault Diagnosis

arXiv:2607.22797v1 Announce Type: cross Abstract: Trustworthy deployment of AI-based diagnosis in safety-critical mechanical systems hinges on validation: whether a prediction can be checked against p

local-aiarxiv-cs-ai

Post-Operative Glioma Segmentation via Loss Stabilization, Normalization and Subspace Attention

arXiv:2607.22749v1 Announce Type: cross Abstract: Tracking residual tumor after surgery is essential for catching recurrence early, but automating post-operative glioma segmentation remains a difficul

Quantum Safe-Set Bayesian Optimization for Quality Improvement in Fuselage Assembly

arXiv:2511.22090v2 Announce Type: replace Abstract: Recent efforts in smart manufacturing have enhanced aerospace fuselage assembly processes, particularly by innovating shape adjustment techniques to

applicationsarxiv-cs-lg

Hardware

Real-Time Semantic Segmentation with Optimized RetinaNet Architectures for Embedded Automotive Systems

arXiv:2607.22714v1 Announce Type: cross Abstract: Real-time perception is a foundational requirement for advanced driver assistance systems (ADAS) and autonomous vehicles, yet embedded automotive plat

hardwarearxiv-cs-ai

ReflexTrack: A Feedback-Driven Agent for Training-Free Referring Video Object Segmentation

arXiv:2607.24098v1 Announce Type: new Abstract: Referring video object segmentation (RVOS) requires segmenting a target specified by natural language throughout a video. Recent agentic approaches comb

local-aiarxiv-cs-cv

RMS@CC-MMD 2026: Multimodal Misogyny Detection via Geometric Interaction and Multi-View Consensus

arXiv:2607.22709v1 Announce Type: cross Abstract: The proliferation of internet memes has introduced new complexities to automated content moderation, particularly in detecting misogyny. Memes often r

safetyarxiv-cs-ai

RoadVGGT: Road-Structure-Aware Feed-Forward Road Surface Reconstruction

arXiv:2607.23758v1 Announce Type: new Abstract: Large-scale road surface reconstruction supports high-definition mapping, autonomous-driving perception, annotation, and simulation. Existing road-speci

agentsarxiv-cs-cv

Robust 6-DoF Object Pose Tracking with Built-In Recovery under Occlusions and Rapid Object Motions

arXiv:2607.23468v1 Announce Type: new Abstract: Real-time 6-DoF object pose tracking is essential for many robotics applications, and several approaches exist. Yet even today's approaches remain unrel

safetyarxiv-cs-cv

Robust Conformalized Selection with Noisy Responses

arXiv:2607.22985v1 Announce Type: cross Abstract: Conformalized selection has been widely applied to select high-quality candidates from large datasets with rigorous uncertainty quantification, such a

local-aiarxiv-cs-lg

SADe: Sparse-Atom Support Decontamination for Few-Shot Segmentation with Weak Support Annotations

arXiv:2607.24706v1 Announce Type: new Abstract: Few-shot segmentation (FSS) commonly assumes clean pixel-level support masks, yet practical support supervision often uses boxes, scribbles, coarse mask

SCTA: An Agentic Framework for Stable and Interpretable Target Gene Discovery from Single-Cell RNA Sequencing

arXiv:2607.23821v1 Announce Type: new Abstract: Identifying therapeutic target genes from single-cell RNA sequencing (scRNA-seq) data remains a fundamental challenge in translational biology. Unlike b

agentsarxiv-cs-lg

Self-Distillation of Hidden Layers for Self-Supervised Representation Learning

arXiv:2603.15553v2 Announce Type: replace Abstract: The landscape of self-supervised learning (SSL) is currently dominated by generative approaches (e.g. MAE) that reconstruct raw low-level data, and

SF-AMS: Strategic Forgetting for Structured Memory in LLM Agent

arXiv:2607.22562v1 Announce Type: new Abstract: Managing long-context dependencies remains a primary bottleneck in LLM agents, as redundant and irrelevant information can degrade multi-step reasoning.

agentsarxiv-cs-ai

SLA-Constrained Carbon-Aware Routing in Geo-Distributed Serverless Clouds

arXiv:2607.22806v1 Announce Type: new Abstract: Modern cloud deployments distribute applications across multiple geographic regions, yet standard routing mechanisms prioritize latency while ignoring t

local-aiarxiv-cs-lg

SLAM-Former: Putting SLAM into One Transformer

arXiv:2509.16909v2 Announce Type: replace Abstract: We present SLAM-Former, a neural approach that integrates full SLAM capabilities into a single transformer. Similar to traditional SLAM systems, SLA

Hardware

Source-Aware Reranking for Retrieval-Augmented Generation: A Reliability Prior Approach

arXiv:2607.22584v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation pipelines rank retrieved documents by semantic similarity alone, without accounting for source provenance or cre

hardwarearxiv-cs-ai

Spatial Prediction of Soil Microplastics and Organic Matter Using Graph Attention Networks

arXiv:2607.22875v1 Announce Type: cross Abstract: Accurate estimation of soil microplastics and organic matter is essential to assess ecosystem health and support sustainable land use. This study pres

local-aiarxiv-cs-ai

Spectral-Aware Analytic Class-Incremental Learning for Long-Tailed Distributions

arXiv:2607.22931v1 Announce Type: cross Abstract: Analytic Continual Learning (ACL) offers a computationally efficient alternative to gradient-based approaches. Recent ACL methods are based on Recursi

StageGuard: Physiologically Constrained Sleep Staging

arXiv:2607.23284v1 Announce Type: new Abstract: Automated sleep staging is increasingly used in large-scale studies to derive sleep-architecture endpoints: total sleep time, REM latency, sleep efficie

safetyarxiv-cs-lg

Statistically Supported LLM Ingredient and Recipe Data Collection in Computational Nutrition

arXiv:2607.23273v1 Announce Type: cross Abstract: Computational nutrition needs precise ingredient data, but current databases are incomplete, inconsistent, and built for human reference rather than a