Search: “framework”

VisPCO: Visual Token Pruning Configuration Optimization via Budget-Aware Pareto-Frontier Learning for Vision-Language Models

arXiv:2604.15188v1 Announce Type: new Abstract: Visual token pruning methods effectively mitigate the quadratic computational growth caused by processing high-resolution images and video frames in vis

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Research

WaveSFNet: A Wavelet-Based Codec and Spatial--Frequency Dual-Domain Gating Network for Spatiotemporal Prediction

DGX agent

arXiv:2603.23284v2 Announce Type: replace Abstract: Spatiotemporal predictive learning aims to forecast future frames from historical observations in an unsupervised manner, and is critical to a wide

researcharxiv-cs-cv

17 Apr 2026

Weight Patching: Toward Source-Level Mechanistic Localization in LLMs

model-releasesarxiv-cs-ai

arXiv:2604.13694v1 Announce Type: new Abstract: Mechanistic interpretability seeks to localize model behavior to the internal components that causally realize it. Prior work has advanced activation-sp

When Does Content-Based Routing Work? Representation Requirements for Selective Attention in Hybrid Sequence Models

arXiv:2603.20997v2 Announce Type: replace Abstract: We identify a routing paradox in hybrid sequence models: content-based routing - deciding which tokens deserve expensive attention - requires pairwi

Your LLM Agents are Temporally Blind: The Misalignment Between Tool Use Decisions and Human Time Perception

arXiv:2510.23853v3 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly used to interact with and execute tasks in dynamic environments. However, a critical yet overlook

safetyarxiv-cs-cl

Applications

A Comprehensive Survey on Network Traffic Synthesis: From Statistical Models to Deep Learning

arXiv:2507.01976v2 Announce Type: replace-cross Abstract: Synthetic network traffic generation has emerged as a promising alternative for various data-driven applications in the networking domain. It

applicationsarxiv-cs-lg

A Domain-Specific Language for LLM-Driven Trigger Generation in Multimodal Data Collection

arXiv:2604.13046v1 Announce Type: cross Abstract: Data-driven systems depend on task-relevant data, yet data collection pipelines remain passive and indiscriminate. Continuous logging of multimodal se

local-aiarxiv-cs-cl

A KL Lens on Quantization: Fast, Forward-Only Sensitivity for Mixed-Precision SSM-Transformer Models

arXiv:2604.13440v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) on edge devices faces severe computational and memory constraints, limiting real-time processing and on-device in

local-aiarxiv-cs-lg

A Multi-Stage Optimization Pipeline for Bethesda Cell Detection in Pap Smear Cytology

arXiv:2604.13939v1 Announce Type: new Abstract: Computer vision techniques have advanced significantly in recent years, finding diverse and impactful applications within the medical field. In this pap

AgentSPEX: An Agent SPecification and EXecution Language

arXiv:2604.13346v1 Announce Type: new Abstract: Language-model agent systems commonly rely on reactive prompting, in which a single instruction guides the model through an open-ended sequence of reaso

agentsarxiv-cs-cl

AIM-CoT: Active Information-driven Multimodal Chain-of-Thought for Vision-Language Reasoning

arXiv:2509.25699v2 Announce Type: replace Abstract: Interleaved-Modal Chain-of-Thought (I-MCoT) advances vision-language reasoning, such as Visual Question Answering (VQA). This paradigm integrates sp

Automated co-design of high-performance thermodynamic cycles via graph-based hierarchical reinforcement learning

arXiv:2604.13133v1 Announce Type: new Abstract: Thermodynamic cycles are pivotal in determining the efficacy of energy conversion systems. Traditional design methodologies, which rely on expert knowle

Hardware

Automatic Charge State Tuning of 300 mm FDSOI Quantum Dots Using Neural Network Segmentation of Charge Stability Diagram

arXiv:2604.13662v1 Announce Type: cross Abstract: Tuning of gate-defined semiconductor quantum dots (QDs) is a major bottleneck for scaling spin qubit technologies. We present a deep learning (DL) dri

hardwarearxiv-cs-cv

Beyond Static Personas: Situational Personality Steering for Large Language Models

arXiv:2604.13846v1 Announce Type: new Abstract: Personalized Large Language Models (LLMs) facilitate more natural, human-like interactions in human-centric applications. However, existing personalizat

Bias-Corrected Adaptive Conformal Inference for Multi-Horizon Time Series Forecasting

arXiv:2604.13253v1 Announce Type: new Abstract: Adaptive Conformal Inference (ACI) provides distribution-free prediction intervals with asymptotic coverage guarantees for time series under distributio

BOAT: Navigating the Sea of In Silico Predictors for Antibody Design via Multi-Objective Bayesian Optimization

arXiv:2604.13980v1 Announce Type: new Abstract: Antibody lead optimization is inherently a multi-objective challenge in drug discovery. Achieving a balance between different drug-like properties is cr

C^2T: Captioning-Structure and LLM-Aligned Common-Sense Reward Learning for Traffic--Vehicle Coordination

arXiv:2604.13098v1 Announce Type: cross Abstract: State-of-the-art (SOTA) urban traffic control increasingly employs Multi-Agent Reinforcement Learning (MARL) to coordinate Traffic Light Controllers (

safetyarxiv-cs-cv

Can Coding Agents Be General Agents?

arXiv:2604.13107v1 Announce Type: cross Abstract: As coding agents have seen rapid capability and adoption gains, users are applying them to general tasks beyond software engineering. In this post, we

agentsarxiv-cs-lg

Character Beyond Speech: Leveraging Role-Playing Evaluation in Audio Large Language Models via Reinforcement Learning

arXiv:2604.13804v1 Announce Type: new Abstract: The rapid evolution of multimodal large models has revolutionized the simulation of diverse characters in speech dialogue systems, enabling a novel inte

Correct Chains, Wrong Answers: Dissociating Reasoning from Output in LLM Logic

arXiv:2604.13065v1 Announce Type: new Abstract: LLMs can execute every step of chain-of-thought reasoning correctly and still produce wrong final answers. We introduce the Novel Operator Test, a bench

Decoding the Delta: Unifying Remote Sensing Change Detection and Understanding with Multimodal Large Language Models

model-releasesarxiv-cs-cv

arXiv:2604.14044v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) excel in general vision-language tasks, their application to remote sensing change understanding is hinde

Design and Behavior of Sparse Mixture-of-Experts Layers in CNN-based Semantic Segmentation

arXiv:2604.13761v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) layers have been shown to substantially increase model capacity without a proportional increase in computational cost an

Driving Engagement in Daily Fantasy Sports with a Scalable and Urgency-Aware Ranking Engine

arXiv:2604.13796v1 Announce Type: cross Abstract: In daily fantasy sports (DFS), match participation is highly time-sensitive. Users must act within a narrow window before a game begins, making match

local-aiarxiv-cs-lg

Tutorials

Empowering Targeted Neighborhood Search via Hyper Tour for Large-Scale TSP

arXiv:2510.20169v3 Announce Type: replace Abstract: Traveling Salesman Problem (TSP) is a classic NP-hard problem that has garnered significant attention from both academia and industry. While neural-

tutorialsarxiv-cs-lg

Explainable Fall Detection for Elderly Care via Temporally Stable SHAP in Skeleton-Based Human Activity Recognition

arXiv:2604.13279v1 Announce Type: new Abstract: Fall detection in elderly care requires not only accurate classification but also reliable explanations that clinicians can trust. However, existing pos

local-aiarxiv-cs-cv

First-See-Then-Design: A Multi-Stakeholder View for Optimal Performance-Fairness Trade-Offs

arXiv:2604.14035v1 Announce Type: new Abstract: Fairness in algorithmic decision-making is often defined in the predictive space, where predictive performance - used as a proxy for decision-maker (DM)

Flow-based Generative Modeling of Potential Outcomes and Counterfactuals

model-releasesarxiv-cs-lg

arXiv:2505.16051v4 Announce Type: replace-cross Abstract: Predicting potential and counterfactual outcomes from observational data is central to individualized decision-making, particularly in clinica

Form Without Function: Agent Social Behavior in the Moltbook Network

arXiv:2604.13052v1 Announce Type: cross Abstract: Moltbook is a social network where every participant is an AI agent. We analyze 1,312,238 posts, 6.7~million comments, and over 120,000 agent profiles

agentsarxiv-cs-cl

Granularity-Aware Transfer for Tree Instance Segmentation in Synthetic and Real Forests

arXiv:2604.13722v1 Announce Type: new Abstract: We address the challenge of synthetic-to-real transfer in forestry perception where real data have only coarse Tree labels while synthetic data provide

Hierarchical Reinforcement Learning with Runtime Safety Shielding for Power Grid Operation

model-releasesarxiv-cs-lg

arXiv:2604.14032v1 Announce Type: cross Abstract: Reinforcement learning has shown promise for automating power-grid operation tasks such as topology control and congestion management. However, its de

KMMMU: Evaluation of Massive Multi-discipline Multimodal Understanding in Korean Language and Context

arXiv:2604.13058v1 Announce Type: new Abstract: We introduce KMMMU, a native Korean benchmark for evaluating multimodal understanding in Korean cultural and institutional settings. KMMMU contains 3,46

Memp: Exploring Agent Procedural Memory

arXiv:2508.06433v4 Announce Type: replace Abstract: Large Language Models (LLMs) based agents excel at diverse tasks, yet they suffer from brittle procedural memory that is manually engineered or enta

agentsarxiv-cs-cl

MM-Doc-R1: Training Agents for Long Document Visual Question Answering through Multi-turn Reinforcement Learning

arXiv:2604.13579v1 Announce Type: new Abstract: Conventional Retrieval-Augmented Generation (RAG) systems often struggle with complex multi-hop queries over long documents due to their single-pass ret

Applications

MSGS: Multispectral 3D Gaussian Splatting

arXiv:2604.13340v1 Announce Type: new Abstract: We present a multispectral extension to 3D Gaussian Splatting (3DGS) for wavelength-aware view synthesis. Each Gaussian is augmented with spectral radia

applicationsarxiv-cs-cv

Multi-modal panoramic 3D outdoor datasets for place categorization

arXiv:2604.13142v1 Announce Type: cross Abstract: We present two multi-modal panoramic 3D outdoor (MPO) datasets for semantic place categorization with six categories: forest, coast, residential area,

Multistage Conditional Compositional Optimization

arXiv:2604.14075v1 Announce Type: cross Abstract: We introduce Multistage Conditional Compositional Optimization (MCCO) as a new paradigm for decision-making under uncertainty that combines aspects of

On the Fundamental Limitations of Dual Static CVaR Decompositions in Markov Decision Processes

arXiv:2507.14005v2 Announce Type: replace Abstract: It was recently shown that dynamic programming (DP) methods for finding static CVaR-optimal policies in Markov Decision Processes (MDPs) can fail wh

Optimized Human-Robot Co-Dispatch Planning for Petro-Site Surveillance under Varying Criticalities

arXiv:2602.07924v2 Announce Type: replace Abstract: Securing petroleum infrastructure requires balancing autonomous system efficiency with human judgment for threat escalation, a challenge unaddressed

agentsarxiv-cs-ro

Pareto-Optimal Offline Reinforcement Learning via Smooth Tchebysheff Scalarization

arXiv:2604.13175v1 Announce Type: new Abstract: Large language models can be aligned with human preferences through offline reinforcement learning (RL) on small labeled datasets. While single-objectiv

PAT-VCM: Plug-and-Play Auxiliary Tokens for Video Coding for Machines

arXiv:2604.13294v1 Announce Type: new Abstract: Existing video coding for machines is often trained for a specific downstream task and model. As a result, the compressed representation becomes tightly

Person Re-Identification via Generalized Class Prototypes

arXiv:2510.17043v2 Announce Type: replace Abstract: Advanced feature extraction methods have significantly contributed to enhancing the task of person re-identification. In addition, modifications to

Physically-Guided Optical Inversion Enable Non-Contact Side-Channel Attack on Isolated Screens

arXiv:2604.13419v1 Announce Type: new Abstract: Noncontact exfiltration of electronic screen content poses a security challenge, with side-channel incursions as the principal vector. We introduce an o

Applications

PostureObjectstitch: Anomaly Image Generation Considering Assembly Relationships in Industrial Scenarios

arXiv:2604.13863v1 Announce Type: new Abstract: Image generation technology can synthesize condition-specific images to supplement real-world industrial anomaly data and enhance anomaly detection mode

applicationsarxiv-cs-cv

PRiMeFlow: Capturing Complex Expression Heterogeneity in Perturbation Response Modelling

arXiv:2604.13986v1 Announce Type: new Abstract: Predicting the effects of perturbations in-silico on cell state can identify drivers of cell behavior at scale and accelerate drug discovery. However, m

Randomized Neural Networks for Integro-Differential Equations with Application to Neutron Transport

arXiv:2604.13830v1 Announce Type: cross Abstract: Integro-differential equations arise in a wide range of applications, including transport, kinetic theory, radiative transfer, and multiphysics modeli

Reconstruction of a 3D wireframe from a single line drawing via generative depth estimation

arXiv:2604.13549v1 Announce Type: new Abstract: The conversion of 2D freehand sketches into 3D models remains a pivotal challenge in computer vision, bridging the gap between human creativity and digi

ReConText3D: Replay-based Continual Text-to-3D Generation

model-releasesarxiv-cs-cv

arXiv:2604.13730v1 Announce Type: new Abstract: Continual learning enables models to acquire new knowledge over time while retaining previously learned capabilities. However, its application to text-t

Rethinking Uncertainty in Segmentation: From Estimation to Decision

arXiv:2604.13262v1 Announce Type: new Abstract: In medical image segmentation, uncertainty estimates are often reported but rarely used to guide decisions. We study the missing step: how uncertainty m

safetyarxiv-cs-cv