Search: “framework”

arXiv:2601.20303v2 Announce Type: replace Abstract: Estimating object mass from visual input is challenging because mass depends jointly on geometric volume and material-dependent density, neither of

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PODiff: Latent Diffusion in Proper Orthogonal Decomposition Space for Scientific Super-Resolution

DGX agent

arXiv:2605.03399v1 Announce Type: new Abstract: Probabilistic super-resolution of high-dimensional spatial fields using diffusion models is often computationally prohibitive due to the cost of operati

model-releasesarxiv-cs-lg

6 May 2026

PriorNet: Prior-Guided Engagement Estimation from Face Video

model-releasesarxiv-cs-cv

arXiv:2605.03615v1 Announce Type: new Abstract: Engagement estimation from face video remains challenging because facial evidence is often incomplete, labeled data are limited, and engagement annotati

Tutorials

PRISM-CTG: A Foundation Model for Cardiotocography Analysis with Multi-View SSL

arXiv:2605.02917v1 Announce Type: new Abstract: Supervised deep learning models for automated CTG analysis are typically constrained by narrowly curated labelled datasets and limited patient cohorts,

tutorialsarxiv-cs-lg

Prism: Efficient Test-Time Scaling via Hierarchical Search and Self-Verification for Discrete Diffusion Language Models

arXiv:2602.01842v3 Announce Type: replace Abstract: Inference-time compute has re-emerged as a practical way to improve LLM reasoning. Most test-time scaling (TTS) algorithms rely on autoregressive de

Proteo-R1: Reasoning Foundation Models for De Novo Protein Design

arXiv:2605.02937v1 Announce Type: new Abstract: Deep learning in de novo protein design has achieved atomic-level fidelity. However, existing models remain largely non-deliberative: they directly synt

psifx -- Psychological and Social Interactions Feature Extraction Package

arXiv:2407.10266v5 Announce Type: replace Abstract: psifx is a plug-and-play multi-modal feature extraction toolkit, aiming to facilitate and democratize the use of state-of-the-art machine learning t

Random test functions, H^{-1} norm equivalence, and stochastic variational physics-informed neural networks

arXiv:2605.03542v1 Announce Type: cross Abstract: The dual norm characterisation of weak solutions of second-order linear elliptic partial differential equations is mathematically natural but computat

Rational Communication Shapes Morphological Composition

arXiv:2605.03510v1 Announce Type: new Abstract: Human languages expand vocabularies by combining existing morphemes rather than inventing arbitrary forms. Communicative efficiency shapes lexical syste

applicationsarxiv-cs-cl

Reasoning-Guided Grounding: Elevating Video Anomaly Detection through Multimodal Large Language Models

arXiv:2605.02912v1 Announce Type: new Abstract: Video Anomaly Detection (VAD) has traditionally been framed as binary classification or outlier detection, providing neither interpretable reasoning nor

researcharxiv-cs-cv

ReCode: Reinforcing Code Generation with Reasoning-Process Rewards

model-releasesarxiv-cs-cl

arXiv:2508.05170v3 Announce Type: replace-cross Abstract: In practice, rigorous reasoning is often a key driver of correct code, while Reinforcement Learning (RL) for code generation often neglects op

Resource-Efficient Reinforcement for Reasoning Large Language Models via Dynamic One-Shot Policy Refinement

arXiv:2602.00815v2 Announce Type: replace Abstract: Large language models (LLMs) have exhibited remarkable performance on complex reasoning tasks, with reinforcement learning under verifiable rewards

Rethinking Temporal Consistency in Video Object-Centric Learning: From Prediction to Correspondence

arXiv:2605.03650v1 Announce Type: new Abstract: The de facto approach in video object-centric learning maintains temporal consistency through learned dynamics modules that predict future object repres

researcharxiv-cs-cv

Revisiting Graph-Tokenizing Large Language Models: A Systematic Evaluation of Graph Token Understanding

arXiv:2605.03514v1 Announce Type: new Abstract: The remarkable success of large language models (LLMs) has motivated researchers to adapt them as universal predictors for various graph tasks. As a wid

RFPrompt: Prompt-Based Expert Adaptation of the Large Wireless Model for Modulation Classification

arXiv:2605.03279v1 Announce Type: new Abstract: Automatic modulation classification (AMC) in real-world deployments demands robustness to distribution shifts arising from hardware impairments, unseen

RoboAlign-R1: Distilled Multimodal Reward Alignment for Robot Video World Models

model-releasesarxiv-cs-ro

arXiv:2605.03821v1 Announce Type: new Abstract: Existing robot video world models are typically trained with low-level objectives such as reconstruction and perceptual similarity, which are poorly ali

Robust Path Tracking for Vehicles via Continuous-Time Residual Learning: An ICODE-MPPI Approach

arXiv:2605.03260v1 Announce Type: new Abstract: Model Predictive Path Integral (MPPI) control is a powerful sampling-based strategy for nonlinear autonomous systems. However, its performance is often

agentsarxiv-cs-ro

Robustness and Transferability of Pix2Geomodel for Bidirectional Facies Property Translation in a Complex Reservoir

arXiv:2605.03919v1 Announce Type: cross Abstract: Reservoir geomodeling is central to subsurface characterization, but it remains challenging because conditioning data are sparse, geological heterogen

applicationsarxiv-cs-cv

Rose-SQL: Role-State Evolution Guided Structured Reasoning for Multi-Turn Text-to-SQL

arXiv:2605.03720v1 Announce Type: new Abstract: Recent advances in Large Reasoning Models (LRMs) trained with Long Chain-of-Thought have demonstrated remarkable capabilities in code generation and mat

Runtime Evaluation of Procedural Content Generation in an Endless Runner Game Using Autonomous Agents

arXiv:2605.01783v1 Announce Type: new Abstract: Procedural Content Generation (PCG) enables game content to be created algorithmically without direct manual level-design effort, but it introduces a se

agentsarxiv-cs-ai

S^2tory: Story Spine Distillation for Movie Script Summarization

arXiv:2605.03244v1 Announce Type: new Abstract: Movie scripts pose a fundamental challenge for automatic summarization due to their non-linear, cross-cut narrative structure, which makes surface-level

agentsarxiv-cs-cl

Safety in Embodied AI: A Survey of Risks, Attacks, and Defenses

arXiv:2605.02900v1 Announce Type: cross Abstract: Embodied Artificial Intelligence (Embodied AI) integrates perception, cognition, planning, and interaction into agents that operate in open-world, saf

safetyarxiv-cs-cv

SAM-NER: Semantic Archetype Mediation for Zero-Shot Named Entity Recognition

model-releasesarxiv-cs-cl

arXiv:2605.03706v1 Announce Type: new Abstract: Zero-shot Named Entity Recognition (ZS-NER) remains brittle under domain and schema shifts, where unseen label definitions often misalign with a large l

SCALER:Synthetic Scalable Adaptive Learning Environment for Reasoning

arXiv:2601.04809v5 Announce Type: replace Abstract: Reinforcement learning (RL) offers a principled way to enhance the reasoning capabilities of large language models, yet its effectiveness hinges on

applicationsarxiv-cs-ai

Scaling Unsupervised Multi-Source Federated Domain Adaptation through Group-Wise Discrepancy Minimization

arXiv:2510.08150v3 Announce Type: replace Abstract: Unsupervised multi-source domain adaptation (UMDA) leverages labeled data from multiple source domains to generalize to an unlabeled target. While f

SCGNN: Semantic Consistency enhanced Graph Neural Network Guided by Granular-ball Computing

model-releasesarxiv-cs-ai

arXiv:2605.02617v2 Announce Type: new Abstract: Capturing semantic consistency among nodes is crucial for effective graph representation learning. Existing approaches typically rely on k-nearest neigh

SCION: Size-aware Policy Orchestration for Nonstationary Object Caches (Long Paper Version)

arXiv:2605.01055v1 Announce Type: cross Abstract: Object caches underpin cloud and edge services, but production workloads are heterogeneous, nonstationary, and throughput-constrained. Recent simple n

Scoring Edit Impact in Grammatical Error Correction via Embedded Association Graphs

arXiv:2604.06573v2 Announce Type: replace Abstract: A Grammatical Error Correction (GEC) system produces a sequence of edits to correct an erroneous sentence. The quality of these edits is typically e

SEAD: Self-Evolving Agent for Multi-Turn Service Dialogue

arXiv:2602.03548v3 Announce Type: replace Abstract: Large Language Models have demonstrated remarkable capabilities in open-domain dialogues. However, current methods exhibit suboptimal performance in

agentsarxiv-cs-cl

SERE: Structural Example Retrieval for Enhancing LLMs in Event Causality Identification

arXiv:2605.03701v1 Announce Type: new Abstract: Event Causality Identification (ECI) requires models to determine whether a given pair of events in a context exhibits a causal relationship. While Larg

safetyarxiv-cs-cl

SOAR: Real-Time Joint Optimization of Order Allocation and Robot Scheduling in Robotic Mobile Fulfillment Systems

arXiv:2605.03842v1 Announce Type: cross Abstract: Robotic Mobile Fulfillment Systems (RMFS) rely on mobile robots for automated inventory transportation, coordinating order allocation and robot schedu

agentsarxiv-cs-ro

Soft Tournament Equilibrium

arXiv:2604.04328v3 Announce Type: replace-cross Abstract: The evaluation of general-purpose artificial agents, particularly those based on LLMs, presents a significant challenge due to the non-transit

SpecMD: A Comprehensive Study on Speculative Expert Prefetching

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Mixture-of-Experts (MoE) models enable sparse expert activation, meaning that only a subset of the model’s parameters is used during each inference. However, to translate this sparsity into practical

Speculative Coupled Decoding for Training-Free Lossless Acceleration of Autoregressive Visual Generation

arXiv:2510.24211v2 Announce Type: replace Abstract: Autoregressive (AR) modeling has recently emerged as a promising new paradigm in visual generation, but its practical adoption is severely constrain

researcharxiv-cs-cv

Stable Multimodal Graph Unlearning via Feature-Dimension Aware Quantile Selection

arXiv:2605.03303v1 Announce Type: new Abstract: Graph unlearning remains a critical technique for supporting privacy-preserving and sustainable multimodal graph learning. However, we observe that exis

Steer Like the LLM: Activation Steering that Mimics Prompting

arXiv:2605.03907v1 Announce Type: new Abstract: Large language models can be steered at inference time through prompting or activation interventions, but activation steering methods often underperform

Stochastic Schrodinger Diffusion Models for Pure-State Ensemble Generation

arXiv:2605.03573v1 Announce Type: cross Abstract: In quantum machine learning (QML), classical data are often encoded as quantum pure states and processed directly as quantum representations, motivati

Strategy-Aware Optimization Modeling with Reasoning LLMs

arXiv:2605.02545v1 Announce Type: new Abstract: Large language models (LLMs) can generate syntactically valid optimization programs, yet often struggle to reliably choose an effective modeling strateg

applicationsarxiv-cs-ai

Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation

arXiv:2605.03849v1 Announce Type: new Abstract: Distillation-based acceleration has become foundational for making autoregressive streaming video diffusion models practical, with distribution matching

safetyarxiv-cs-cv

Structured Diffusion Bridges: Inductive Bias for Denoising Diffusion Bridges

arXiv:2605.02973v1 Announce Type: new Abstract: Modality translation is inherently under-constrained, as multiple cross-modal mappings may yield the same marginals. Recent work has shown that diffusio

safetyarxiv-cs-lg

T^2PO: Uncertainty-Guided Exploration Control for Stable Multi-Turn Agentic Reinforcement Learning

arXiv:2605.02178v1 Announce Type: new Abstract: Recent progress in multi-turn reinforcement learning (RL) has significantly improved reasoning LLMs' performances on complex interactive tasks. Despite

Talk is Cheap, Communication is Hard: Dynamic Grounding Failures and Repair in Multi-Agent Negotiation

arXiv:2605.01750v1 Announce Type: cross Abstract: Grounding is the collaborative process of establishing mutual belief sufficient for the current communicative purpose. While static grounding maps lan

Task-Aware Scanning Parameter Configuration for Robotic Inspection Using Vision Language Embeddings and Hyperdimensional Computing

model-releasesarxiv-cs-cv

arXiv:2605.03909v1 Announce Type: cross Abstract: Robotic laser profiling is widely used for dimensional verification and surface inspection, yet measurement fidelity is often dominated by sensor conf

Tempered Guided Diffusion

arXiv:2605.03712v1 Announce Type: cross Abstract: Training-free conditional diffusion provides a flexible alternative to task-specific conditional model training, but existing samplers often allocate

Tenability and Weak Semantics: Modeling Non-uniform Defense -- Extended Version

model-releasesarxiv-cs-ai

arXiv:2605.02024v1 Announce Type: new Abstract: In Dung-style abstract argumentation, various semantics capture notions of acceptability of arguments. The admissibility semantics capture the notion th

The Conversations Beneath the Code: Triadic Data for Long-Horizon Software Engineering Agents

arXiv:2605.02244v1 Announce Type: cross Abstract: Frontier software engineering agents have saturated short-horizon benchmarks while regressing on the work that constitutes senior engineering: long-ho

agentsarxiv-cs-ai

The Design and Composition of Structural Causal Decision Processes

arXiv:2605.02681v1 Announce Type: cross Abstract: We present two new classes of causal models of decision-making agents. Our approach is motivated by the needs of modeling the economics of computing s

To Use AI as Dice of Possibilities with Timing Computation

arXiv:2605.01134v1 Announce Type: new Abstract: The dominant noun-based modeling paradigm has fundamentally constrained AI development, precluding any adequate representation of the future as an open

researcharxiv-cs-ai