Search: “framework”

Learning to Solve Compositional Geometry Routing Problems

arXiv:2605.18094v1 Announce Type: new Abstract: We study the Compositional Geometry Routing Problem (CGRP), a unified superclass of traditional routing problems that covers point-only, line-only, area

applicationsarxiv-cs-ai

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Learning Unbiased Permutations via Flow Matching

DGX agent

arXiv:2605.16755v1 Announce Type: cross Abstract: Learning permutations is fundamental to sorting, ranking, and matching, but existing differentiable methods based on entropy-regularized Sinkhorn prod

researcharxiv-cs-ai

19 May 2026

Learning-Zone Energy: Online Data Selection for Efficient RL Post-Training

arXiv:2605.17003v1 Announce Type: cross Abstract: Reinforcement Learning (RL) post-training has emerged as the dominant paradigm for eliciting mathematical reasoning in Large Language Models (LLMs), y

Linguistic Uncertainty and Reply Engagement on X: A Cross-Domain Replication of the Uncertainty-Reply Asymmetry

arXiv:2605.16289v1 Announce Type: cross Abstract: Linguistic uncertainty is common in social media, but its relationship with engagement remains unclear across languages and topics. Using 2,258 Englis

safetyarxiv-cs-cl

Lipschitz-Guided Design of Interpolation Schedules in Generative Models

arXiv:2509.01629v3 Announce Type: replace-cross Abstract: We study the design of interpolation schedules in flow and diffusion-based generative models from both statistical and numerical perspectives.

LISA: Language-guided Interference-aware Spatial-Frequency Attention for Driver Gaze Estimation

arXiv:2605.17287v1 Announce Type: new Abstract: Driver gaze estimation serves as a fundamental metric for evaluating driver attentiveness in modern monitoring systems. Beyond being vulnerable to sudde

LiteFrame: Efficient Vision Encoders Unlock Frame Scaling in Video LLMs

arXiv:2605.17260v1 Announce Type: new Abstract: The fundamental challenge in scaling Video Large Language Models (Video LLMs) to long-form video lies in managing the explosion of visual-token context

LLM Agents Are the Antidote to Walled Gardens

arXiv:2506.23978v3 Announce Type: replace-cross Abstract: While the Internet's core infrastructure was designed to be open and universal, today's application layer is dominated by closed, proprietary

applicationsarxiv-cs-cl

LLMForge: Multi-Backend Hardware-Aware Neural Architecture Search with Infinite-Head Attention for Edge Language Models

arXiv:2605.17653v1 Announce Type: cross Abstract: Sub-billion-parameter Transformer language models are increasingly deployed on edge devices, where the privacy, latency, and operating-cost advantages

Long Context Modeling with Ranked Memory-Augmented Retrieval

arXiv:2503.14800v3 Announce Type: replace-cross Abstract: Effective long-term memory management is crucial for language models handling extended contexts. We introduce the Enhanced Ranked Memory Augme

Local Ai

LongDPM: Overlap-Aware 4D Reconstruction from Long Monocular Videos

arXiv:2605.17303v1 Announce Type: new Abstract: Recovering a dynamic 3D scene from a long monocular video is crucial for dense geometry, camera motion, and temporal correspondence to remain consistent

local-aiarxiv-cs-cv

LongMINT: Evaluating Memory under Multi-Target Interference in Long-Horizon Agent Systems

arXiv:2605.18565v1 Announce Type: cross Abstract: Real-world agents operate over long and evolving horizons, where information is repeatedly updated and may interfere across memories, requiring accura

LoopQ: Quantization for Recursive Transformers

arXiv:2605.16343v1 Announce Type: cross Abstract: Looped language models (LoopLMs) improve parameter efficiency by recursively reusing Transformer blocks, enabling deeper computation under a fixed mod

Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model

arXiv:2512.01030v3 Announce Type: replace Abstract: Recovering pixel-wise geometric properties from a single image is fundamentally ill-posed due to appearance ambiguity and non-injective mappings bet

LPG: Balancing Efficiency and Policy Reasoning in Latent Policy Guardrails

arXiv:2605.17329v1 Announce Type: cross Abstract: Guardrails are a critical safety layer for modern AI systems, but their operating regime is changing. As LLMs are deployed as customized assistants, s

safetyarxiv-cs-ai

LSDTs: LLM-Augmented Semantic Digital Twins for Adaptive Knowledge-Intensive Infrastructure Planning

arXiv:2508.06799v3 Announce Type: replace-cross Abstract: Digital Twins (DTs) offer powerful tools for managing complex infrastructure systems, but their effectiveness is often limited by challenges i

applicationsarxiv-cs-ai

Lying with Truths: Open-Channel Multi-Agent Collusion for Belief Manipulation via Generative Montage

arXiv:2601.01685v2 Announce Type: replace-cross Abstract: As large language models (LLMs) transition to autonomous agents synthesizing real-time information, their reasoning capabilities introduce an

agentsarxiv-cs-ai

Tutorials

Machine Learning Enabled Graph Analysis of Particulate Composites: Application to Solid-state Battery Cathodes

arXiv:2512.16085v2 Announce Type: replace-cross Abstract: Particulate composites underpin many solid-state chemical and electrochemical systems, where microstructural features such as multiphase bound

tutorialsarxiv-cs-cv

Machine Unlearning for Masked Diffusion Language Models

arXiv:2605.18253v1 Announce Type: cross Abstract: Recent masked diffusion language models (MDLMs), such as LLaDA and Dream, have achieved performance comparable to autoregressive large language models

Mamba-VGGT: Persistent Long-Sequence Video Geometry Grounded Transformer via External Sliding Window Mamba Memory

arXiv:2605.17478v1 Announce Type: new Abstract: Visual Geometry Grounded Transformers (VGGT) have set new benchmarks in high-fidelity 3D scene reconstruction. However, as the sequence length increases

safetyarxiv-cs-cv

MCQ Difficulty Prediction via Modeling Learner Heterogeneity Using Data-Driven Cognitive Profiling

arXiv:2605.16290v1 Announce Type: cross Abstract: Predicting the difficulty of multiple-choice questions (MCQs) is important for effective assessment, yet current methods typically assume a unimodal s

Mechanistically Interpretable Neural Encoding Reveals Fine-Grained Functional Selectivity in Human Visual Cortex

arXiv:2605.16468v1 Announce Type: cross Abstract: A central goal in understanding human vision is to uncover the visual features that drive neuronal activity. A growing body of work has used artificia

Local Ai

MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents

arXiv:2605.18652v1 Announce Type: new Abstract: Recent GUI agents have made substantial progress in visual grounding and action prediction, yet they remain brittle in long-horizon tasks that require m

local-aiarxiv-cs-cv

Memory-Augmented Query Intent Understanding for Efficient Chat-based Image Retrieval

arXiv:2605.17365v1 Announce Type: new Abstract: Different from traditional text-to-image retrieval tasks, chat-based image retrieval allows the human-interactive system to iteratively clarify and refi

Memory-Guided Tree Search with Cross-Branch Knowledge Transfer for LLM Solver Synthesis

arXiv:2605.17539v1 Announce Type: new Abstract: Combinatorial optimization (CO) underlies decision-making from logistics to chip design, where infeasible solutions are operationally unusable and small

MemRepair: Hierarchical Memory for Agentic Repository-Level Vulnerability Repair

arXiv:2605.17444v1 Announce Type: cross Abstract: Modern software ecosystems face a rapidly growing number of disclosed vulnerabilities, increasing the need for automated repair techniques that can op

agentsarxiv-cs-ai

Merlin's Whisper: Enabling Efficient Reasoning in Large Language Models via Black-box Persuasive Prompting

model-releasesarxiv-cs-cl

arXiv:2510.10528v3 Announce Type: replace Abstract: Large reasoning models (LRMs) have demonstrated remarkable proficiency in tackling complex tasks through step-by-step thinking. However, this length

Mirror Mean-Field Langevin Dynamics

arXiv:2505.02621v2 Announce Type: replace Abstract: The mean-field Langevin dynamics (MFLD) minimizes an entropy-regularized nonlinear convex functional on the Wasserstein space over R^d, and has gain

Mitigating Conversational Inertia in Multi-Turn Agents

arXiv:2602.03664v3 Announce Type: replace Abstract: Large language models excel as few-shot learners when provided with appropriate demonstrations, yet this strength becomes problematic in multiturn a

safetyarxiv-cs-ai

Mixture-of-Experts Can Surpass Dense LLMs Under Strictly Equal Resource

arXiv:2506.12119v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) language models dramatically expand model capacity and achieve remarkable performance without increasing per-token co

Modelling Customer Trajectories with Reinforcement Learning for Practical Retail Insights

arXiv:2605.18449v1 Announce Type: cross Abstract: Understanding customer movement within retail spaces is essential for optimizing store layouts. Real-world trajectory data can provide highly accurate

agentsarxiv-cs-ai

Monitoring the Internal Monologue: Probe Trajectories Reveal Reasoning Dynamics

arXiv:2605.18549v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) introduce new opportunities for safety monitoring through their Chain of Thought (CoT) reasoning. However, CoT is not alwa

safetyarxiv-cs-cl

Motion Cues from Image-based Point Tracking for LiDAR Scene Flow Estimation

arXiv:2605.16922v1 Announce Type: new Abstract: LiDAR scene flow estimation is essential for autonomous driving, as it provides 3D motion for each point. Self-supervised approaches use static-dynamic

agentsarxiv-cs-cv

Motion-Uncertainty-Aware Next-Best-View Planning for Moving Object Reconstruction

arXiv:2605.17593v1 Announce Type: new Abstract: Active 3D reconstruction of moving objects requires selecting informative viewpoints while accounting for object motion uncertainty during the decision-

applicationsarxiv-cs-ro

Multi-hop Relational Contrastive Learning: Extending Spatial Contrastive Pre-training Beyond Pairwise Relations

arXiv:2605.16456v1 Announce Type: new Abstract: Understanding how objects relate to each other in space is fundamental to scene understanding, yet most contrastive pre-training approaches only model p

Multi-Order Matching Network for Alignment-Free Depth Super-Resolution

arXiv:2511.16361v3 Announce Type: replace Abstract: Recent guided depth super-resolution methods are premised on the assumption of strict spatial alignment between depth and RGB, achieving high-qualit

safetyarxiv-cs-cv

Multi-task Linear Regression without Eigenvalue Lower Bounds: Adaptivity, Robustness and Safety

arXiv:2605.17126v1 Announce Type: cross Abstract: We study the multi-task linear regression problem in the presence of contaminated tasks. We address the setting where the unknown parameters of a majo

safetyarxiv-cs-lg

Multimodal Cultural Heritage Knowledge Graph Extension with Language and Vision Models

arXiv:2605.17669v1 Announce Type: new Abstract: The preservation and interpretation of cultural heritage increasingly rely on digital technologies, among which Knowledge Graphs (KGs) stand out for the

MUSE: Multimodal Uncertainty Quantification of State Estimation

arXiv:2605.17421v1 Announce Type: new Abstract: Accurate visual state estimation has been a central topic in robotics with a wide range of applications in robot navigation, autonomous driving, and aut

agentsarxiv-cs-ro

Mutual Enhancement Between Global Tokens and Patch Tokens: From Theory to Practice

arXiv:2605.16384v1 Announce Type: cross Abstract: Accurate and effective discrete image tokenization is crucial for long image sequence processing. However, current methods rigidly compress all conten

MV-Gate: Insider Threat Detection via Multi-View Behavioral Statistics and Semantic Modeling

arXiv:2605.17761v1 Announce Type: cross Abstract: Insider threats often reveal early anomalies through disruptions in behavioral statistics-such as altered recurrence patterns or short-versus long-ter

Nash: Neural Adaptive Shrinkage for Structured High-Dimensional Regression

arXiv:2505.11143v2 Announce Type: replace-cross Abstract: Sparse linear regression is a fundamental tool in data analysis. However, traditional approaches often fall short when covariates exhibit stru

Nested Spatio-Temporal Time Series Forecasting

arXiv:2605.16447v1 Announce Type: cross Abstract: Spatiotemporal forecasting is critical for real-world applications like traffic management, yet capturing reliable interactions remains challenging un

applicationsarxiv-cs-ai

Network Knowledge Prior Guided Learning for Data-Efficient Surface Defect Detection

arXiv:2605.17780v1 Announce Type: new Abstract: Deep learning-based methods have become the de facto standard for industrial defect detection. However, their data-hungry nature and inherent 'black-box

applicationsarxiv-cs-cv

Neural Visual Decoding via Cognitive guided Adaptive Blurring and Information Constrained Alignment

arXiv:2605.16418v1 Announce Type: cross Abstract: EEG-based visual decoding aims to establish a mapping between neural signals and visual semantics. However, it remains constrained by the dual challen

safetyarxiv-cs-ai

NeuroLiDAR: Adaptive Frame Rate Depth Sensing via Neuromorphic Event-LiDAR Fusion

arXiv:2605.16805v1 Announce Type: new Abstract: LiDARs are widely used for 3D depth reconstruction, but their performance is often limited by inherent hardware constraints that impose trade-offs betwe

No Plan, Yet Human: A Reactive Robotics Model Predicts Human Planning Failures on a Clinical Task

arXiv:2605.16514v1 Announce Type: cross Abstract: Understanding why some sequential planning problems are harder than others requires models that go beyond average performance. They should capture the

Non-Colliding Biometric Identities for Digital Entities: Geometry, Capacity, and Million-Scale Virtual Identity Provisioning

arXiv:2605.18238v1 Announce Type: new Abstract: Digital entities such as AI agents and humanoid robots increasingly operate alongside real humans, yet their identity infrastructure is based on credent