Search: “framework”

MATCHA: Efficient Deployment of Deep Neural Networks on Multi-Accelerator Heterogeneous Edge SoCs

model-releasesarxiv-cs-lg

arXiv:2604.09124v1 Announce Type: cross Abstract: Deploying DNNs on System-on-Chips (SoC) with multiple heterogeneous acceleration engines is challenging, and the majority of deployment frameworks can

13 Apr 2026

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Tutorials

RetinexDualV2: Physically-Grounded Dual Retinex for Generalized UHD Image Restoration

DGX agent

arXiv:2603.27979v2 Announce Type: replace Abstract: We propose RetinexDualV2, a unified, physically grounded dual-branch framework for diverse Ultra-High-Definition (UHD) image restoration. Unlike gen

tutorialsarxiv-cs-cv

13 Apr 2026

The AI Codebase Maturity Model: From Assisted Coding to Self-Sustaining Systems

model-releasesarxiv-cs-ai

arXiv:2604.09388v1 Announce Type: cross Abstract: AI coding tools are widely adopted, but most teams plateau at prompt-and-review without a framework for systematic progression. This paper presents th

13 Apr 2026

Towards Context-Aware Image Anonymization with Multi-Agent Reasoning

arXiv:2603.27817v3 Announce Type: replace-cross Abstract: Street-level imagery contains personally identifiable information (PII), some of which is context-dependent. Existing anonymization methods ei

13 Apr 2026

Event-Centric World Modeling with Memory-Augmented Retrieval for Embodied Decision-Making

arXiv:2604.07392v1 Announce Type: cross Abstract: Autonomous agents operating in dynamic and safety-critical environments require decision-making frameworks that are both computationally efficient and

safetyarxiv-cs-ro

Incorporating Social Awareness into Control of Unknown Multi-Agent Systems: A Real-Time Spatiotemporal Tubes Approach

arXiv:2510.25597v2 Announce Type: replace-cross Abstract: This paper presents a decentralized control framework that incorporates social awareness into multi-agent systems with unknown dynamics to ach

safetyarxiv-cs-ro

Applications

Probabilistic Predictions of Process-Induced Deformation in Carbon/Epoxy Composites Using a Deep Operator Network

arXiv:2512.13746v4 Announce Type: replace-cross Abstract: Fiber reinforcement and polymer matrix respond differently to manufacturing conditions due to mismatch in coefficient of thermal expansion and

applicationsarxiv-cs-lg

Smoothing the Edges: Smooth Optimization for Sparse Regularization using Hadamard Overparametrization

arXiv:2307.03571v4 Announce Type: replace Abstract: We present a framework for smooth optimization of explicitly regularized objectives for (structured) sparsity. These non-smooth and possibly non-con

Adaptive-Group Process Rewards for GUI Agents

arXiv:2610.17710v1 Announce Type: new Abstract: Training graphical user interface (GUI) agents with reinforcement learning suffers from sparse outcome rewards, leading to inefficient learning. Process

Beyond Benchmark Accuracy: A Diagnostic Test for LLM Chemical Prediction

model-releasesarxiv-cs-cl

arXiv:2610.19906v1 Announce Type: new Abstract: LLMs have achieved strong performance on chemical prediction benchmarks. However, existing evaluation methods typically provide target entity identity i

ClawLoop: Self-Improving Agents via Harness-Native Training Loop

arXiv:2610.14118v1 Announce Type: new Abstract: The rapid advancement of Large Language Models (LLMs) has driven their deployment toward general-purpose harness environments, where LLM-based agents op

Do Vision CIL Methods Transfer to Protein? A Diagnostic Benchmark of Frozen Protein Encoders

model-releasesarxiv-cs-lg

arXiv:2610.18879v1 Announce Type: new Abstract: Protein function annotation operates over an expanding label space, making class-incremental learning (CIL) a natural framework for incorporating newly

Dual-arm Cooperation for Tabletop Wiping with Temporal Object Removal

arXiv:2610.19527v1 Announce Type: new Abstract: We devise a dual-arm cooperative planning framework for wiping table surface in the presence of scattered objects. Unlike conventional surface-cleaning

researcharxiv-cs-ro

Event-Centric Earthquake Monitoring with a Multi-Station Transformer

arXiv:2610.17404v1 Announce Type: cross Abstract: Earthquake catalogs underpin studies such as fault structure, earthquake processes and seismic hazard, and their value depends on being both complete

researcharxiv-cs-ai

Gap Detection: Mitigating Homogenization through Demand and Defensibility

arXiv:2610.20162v1 Announce Type: new Abstract: Language models often produce semantically similar answers to open-ended questions, even when many plausible alternatives exist. Generating useful alter

researcharxiv-cs-cl

Generative World Simulation with DAO and JING

arXiv:2610.19726v1 Announce Type: new Abstract: We present a Generative World Simulation framework that couples persistent shared world state with continuous first-person audiovisual generation. The f

researcharxiv-cs-cv

Learning From a Steady Hand: A Weakly Supervised Agent for Robot Assistance under Microscopy

arXiv:2601.20776v2 Announce Type: replace Abstract: This paper rethinks steady-hand robotic manipulation by using a weakly supervised framework that fuses calibration-aware perception with admittance

agentsarxiv-cs-ro

Applications

Learning Who Benefits Most: Multi-Treatment Causal Ranking for Population Health Stratification

arXiv:2610.19782v1 Announce Type: new Abstract: Population health stratification frameworks, such as the Italian DM77, organize patients by clinical need and care pathways but offer limited guidance o

applicationsarxiv-cs-lg

LLM-Based Policy Compliance Verification of Loan Applications

arXiv:2610.20155v1 Announce Type: cross Abstract: Banks rely on extensive internal policy frameworks to ensure that corporate lending decisions comply with regulatory requirements and internal risk st

safetyarxiv-cs-cl

Transparent Information Flow Modeling for Role-Aware AI Act Assessment

arXiv:2610.16916v1 Announce Type: new Abstract: The European Union's Artificial Intelligence Act introduces a structured framework for governing high-risk AI systems, emphasizing transparency, risk ma

safetyarxiv-cs-ai

WorkBorne: Discovering Agentic Tasks from Real-World Artifact Transitions

arXiv:2610.14915v1 Announce Type: new Abstract: Developing terminal-based agents for long-horizon execution demands synthetic tasks that tightly couple complex instructions with authentic, interactive

A Survey of Flow Matching in Reinforcement Learning

arXiv:2610.16275v1 Announce Type: new Abstract: Flow Matching (FM) has recently emerged as a principled and efficient generative modeling framework for reinforcement learning (RL), enabling expressive

safetyarxiv-cs-lg

All-St3R SLAM: Real-time RGB Dynamic SLAM with Pixel-wise Motion Masking

arXiv:2610.16143v1 Announce Type: new Abstract: SLAM (Simultaneous Localization and Mapping) is a core technology in autonomous systems that enables them to estimate their own position and build a map

agentsarxiv-cs-cv

Augmenting Real-time Visualization in Minimally Invasive Surgery with Particle Filtering and Depth-Aware Occlusion Handling

arXiv:2610.18422v1 Announce Type: cross Abstract: We present a real-time, hybrid framework for occlusion handling and depth-aware tracking in minimally invasive surgeries (MIS). Occlusions caused by s

researcharxiv-cs-ro

Can Renyi Accountants Beat Lossless Accountants for DP-SGD?

arXiv:2610.17120v1 Announce Type: new Abstract: Recent frameworks in differential privacy (DP), such as privacy loss distributions and f-DP, provide lossless representations of the privacy leakage of

Distributional Regression for Arbitrary Response Variables Using ReLU Neural Networks

arXiv:2610.16142v1 Announce Type: cross Abstract: This paper develops a unified framework for distributional regression with arbitrary response variables. Rather than relying on scalar thresholds or E

Enhanced Trading Systems with Intelligent Market Analysis

arXiv:2610.13998v1 Announce Type: new Abstract: This paper proposes a hybrid reinforcement learning trading framework integrating intraday market data with transformer-based financial sentiment signal

agentsarxiv-cs-lg

Metric-Driven Reinforcement Learning for Object Hallucination Reduction in LVLM-Based Image Captioning

arXiv:2610.14976v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have excelled in joint visual and language understanding, particularly in image captioning. However, LVLMs remain p

researcharxiv-cs-cv

Tutorials

Pro-t-VAE: Closed-Form Student's t Mixtures for Robust Prototype Discovery

arXiv:2610.14894v1 Announce Type: new Abstract: We present a robust deep generative framework for unsupervised image prototype discovery, built on a heavy-tailed Student's t mixture prior, that bridge

tutorialsarxiv-cs-lg

Refined Grid Sampling for Efficient Implicit Neural Representations of Large-Scale Scientific Data

arXiv:2610.14205v1 Announce Type: new Abstract: Implicit neural representations (INRs) offer a powerful framework for modeling high-dimensional physical fields, but their training remains inefficient

ScenePlacer: Reformulating Scene-Level Object Pose Estimation as Visibility Field Learning

arXiv:2610.15734v1 Announce Type: new Abstract: We present ScenePlacer, a framework for scene-level pose estimation of objects generated by state-of-the-art native shape generation models, placing gen

safetyarxiv-cs-cv

Semantic Edge-Cloud Communication for Real-Time Urban Traffic Digital Twins

arXiv:2610.14187v1 Announce Type: cross Abstract: Urban traffic systems are becoming increasingly complex, demanding real-time traffic perception, proactive collision prediction, and intelligent manag

safetyarxiv-cs-cv

XAI-Guided Fourier Domain Generalisation for Pure-Simulation Sim-to-Real Deep Reinforcement Learning

arXiv:2610.16478v1 Announce Type: cross Abstract: Deep reinforcement learning has shown strong potential for vision-based autonomous driving, but policies trained in simulation often suffer severe per

safetyarxiv-cs-cv

DistressBench: Evaluating Multi-Dimensional Crisis Support in Large Language Models

arXiv:2610.12758v1 Announce Type: new Abstract: Language models have been adopted faster than evaluation practices that reliably assess their risks, and a growing share of use is affective rather than

safetyarxiv-cs-cl

12 Oct 2026

Localized Generative Design of Ship Hulls with Diffusion Models and High-Fidelity Assessment

model-releasesarxiv-cs-ai

arXiv:2610.12870v1 Announce Type: cross Abstract: Practical ship design requires localized refinement and performance evaluation. This paper presents a reward-directed diffusion framework for localize

12 Oct 2026

PSI-SINDy: Post-Selection Inference for Sparse Identification of Nonlinear Dynamics

arXiv:2610.11486v1 Announce Type: cross Abstract: Sparse identification of nonlinear dynamics (SINDy) is a data-driven framework for discovering governing dynamics from time-series data by identifying

safetyarxiv-cs-lg

9 Oct 2026

GAGR-Lab: Evaluating Joint Spatial-Geometric and Analytic Function Reasoning

model-releasesarxiv-cs-cl

arXiv:2610.10201v1 Announce Type: cross Abstract: Joint spatial-geometric and analytic function reasoning requires translating a perceived spatial configuration into a symbolic function whose executed

Learning Unknown Constraints without Unsafe Data via Optimality and Counterfactual Regularization

model-releasesarxiv-cs-lg

arXiv:2610.09350v1 Announce Type: cross Abstract: Learning from demonstrations (LfD) provides a framework for inferring unknown constraints from locally optimal, constraint-satisfying expert behavior.

Tokka-Bench: Evaluating Tokenizers Across 100 Natural and 20 Programming Languages

model-releasesarxiv-cs-cl

arXiv:2610.08794v1 Announce Type: new Abstract: Large language models rely on subword tokenizers whose quality varies across languages, yet no standardized multi-metric framework exists for broad comp

TRACK: Telemetry-Based Racing Analysis and Coaching Kit in Sim Racing Games

arXiv:2610.10061v1 Announce Type: cross Abstract: This paper presents TRACK (Telemetry-Based Racing Analysis and Coaching Kit), which is a framework for analyzing driving performance in sim racing and

agentsarxiv-cs-lg

Beyond Scalar IoU: Structured Verification from Rollout Groups for Video Temporal Grounding

arXiv:2610.07601v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) provides a natural framework for adapting pretrained models to video temporal grounding, where gen

safetyarxiv-cs-ai

Emoception: Selective Affective Layer Fine-Tuning of Video Vision Transformers for Player Arousal Change Recognition From Gameplay Footage

arXiv:2610.07603v1 Announce Type: cross Abstract: This article proposes Selective Affective Layer Fine-Tuning (SALFT), an efficient adaptation framework for Video Vision Transformers in player arousal

researcharxiv-cs-ai

High-Dimensional Statistical Inference for Sparse Support Vector Machines

arXiv:2610.08345v1 Announce Type: cross Abstract: Using a replica-symmetric high-dimensional characterization, we develop an inferential framework for sparse support vector machines when the sample si

SENSE: State-aware Emotion Navigation Storytelling Engine

arXiv:2610.07666v1 Announce Type: cross Abstract: This paper presents SENSE, a state-aware framework for generating playable branching visual novels with multi-track emotional navigation. Integrating

researcharxiv-cs-ai

Billion-Scale Thumbnail Optimization for Uncurated Short-Form Videos via Multi-Armed Bandits

arXiv:2610.04931v1 Announce Type: new Abstract: This paper introduces a real-time thumbnail optimization system deployed at a global O(B) scale on a major short-form video platform. Unlike traditional

Human-in-the-Loop Neuro-Symbolic Drift Anticipation for Reliable Visual SLAM

arXiv:2610.05757v1 Announce Type: new Abstract: This paper introduces Hybrid DeepSEE (HDS), a Human-in-the-Loop (HITL) neuro-symbolic framework for proactive drift anticipation in Visual SLAM (V-SLAM)

researcharxiv-cs-ro

Local Ai

Hybrid-Basis Feature Forecasting for Diffusion Sampling Acceleration

arXiv:2610.05254v1 Announce Type: new Abstract: We propose Hybrid-Basis Feature Forecasting (HybridFF), a training-free, plug-and-play framework for accelerating diffusion sampling. To capture local s

local-aiarxiv-cs-cv

Applications

Kepler4D: Controllable Future Video Generation via 4D Scene State Evolution

arXiv:2610.04152v1 Announce Type: new Abstract: Video world models aim to preserve scene structure and predict how dynamic objects evolve beyond visual observations. We present Kepler4D, a framework f

applicationsarxiv-cs-cv