Search: “framework”

SP-GCRL: Influence Maximization on Incomplete Social Graphs

arXiv:2605.12513v1 Announce Type: cross Abstract: Influence maximization (IM) in real platforms is challenged by incomplete, noisy social graphs and non-stationary diffusion dynamics. We propose SP-GC

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SPOT: Selective Prompt Projection via Total Variation for Inference-Only Safe Text-to-Image Generation

DGX agent

arXiv:2602.00616v3 Announce Type: replace Abstract: Text-to-Image (T2I) diffusion models enable high quality open ended synthesis, but practical use requires suppressing unsafe generations while prese

safetyarxiv-cs-ai

14 May 2026

Stable Attention Response for Reliable Precipitation Nowcasting

arXiv:2605.13181v1 Announce Type: cross Abstract: Precipitation nowcasting remains challenging due to the highly localized, rapidly evolving, and heterogeneous nature of atmospheric dynamics. Although

STAR: Semantic-Temporal Adaptive Representation Learning for Few-Shot Action Recognition

arXiv:2605.13202v1 Announce Type: cross Abstract: Few-shot action recognition (FSAR) requires models to generalize to novel action categories from only a handful of annotated samples. Despite progress

State-Centric Decision Process

arXiv:2605.12755v1 Announce Type: new Abstract: Language environments such as web browsers, code terminals, and interactive simulations emit raw text rather than states, and provide none of the runtim

Steer-to-Detect: Probing Hidden Representations for Detection of LLM-Generated Texts

arXiv:2605.12890v1 Announce Type: cross Abstract: The rapid advancement of large language models (LLMs) has made machine-generated text increasingly difficult to distinguish from human-written text. W

Stochastic Dimension-Free Zeroth-Order Estimator for High-Dimensional and High-Order PINNs

model-releasesarxiv-cs-lg

arXiv:2603.24002v2 Announce Type: replace Abstract: Physics-Informed Neural Networks (PINNs) for high-dimensional and high-order partial differential equations (PDEs) are primarily constrained by the

STORM: Segment, Track, and Object Re-Localization from a Single Image

arXiv:2511.09771v3 Announce Type: replace Abstract: Accurate 6D pose estimation and tracking are core capabilities for physical AI systems, yet real-world deployment remains brittle and labor-intensiv

applicationsarxiv-cs-cv

Stress-Testing the Reasoning Competence of LLMs With Proofs Under Minimal Formalism

arXiv:2605.12524v1 Announce Type: cross Abstract: We introduce ProofGrid, a benchmark suite for evaluating LLM reasoning through machine-checkable proofs rather than final answers alone. ProofGrid con

SupChain-Bench: Benchmarking Large Language Models for Real-World Supply Chain Management

arXiv:2602.07342v2 Announce Type: replace Abstract: Large language models (LLMs) have shown promise in complex reasoning and tool-based decision making, motivating their application to real-world supp

Survival In-Context: Amortized Bayesian Survival Analysis via Prior-Fitted Networks

arXiv:2603.29475v2 Announce Type: replace Abstract: Survival analysis is crucial for many medical applications, but remains challenging for modern machine learning due to limited data, censoring, and

applicationsarxiv-cs-lg

SymbolSight: Minimizing Inter-Symbol Interference for Reading with Prosthetic Vision

arXiv:2601.17326v2 Announce Type: replace Abstract: Retinal prostheses restore limited visual perception, but low spatial resolution and temporal persistence make reading difficult. In sequential lett

researcharxiv-cs-cv

Systematic Failures in Collective Reasoning under Distributed Information in Multi-Agent LLMs

arXiv:2505.11556v4 Announce Type: replace-cross Abstract: Multi-agent systems built on large language models (LLMs) are expected to enhance decision-making by pooling distributed information, yet syst

Taming the Long Tail: Rebalancing Adversarial Training via Adaptive Perturbation

arXiv:2605.13395v1 Announce Type: cross Abstract: Deep neural networks are highly vulnerable to adversarial examples, i.e.,small perturbations that can significantly degrade model performance. While a

applicationsarxiv-cs-cv

Teacher-Guided Policy Optimization for LLM Distillation

arXiv:2605.13230v1 Announce Type: cross Abstract: The convergence of reinforcement learning and imitation learning has positioned Reverse KL (RKL) as a promising paradigm for on-policy LLM distillatio

Teaching and Learning under Deductive Errors

arXiv:2605.13384v1 Announce Type: new Abstract: Most models of machine teaching and learning assume the learner makes no errors in its internal deductive inference. However, humans and large language

TeleGate: Whole-Body Humanoid Teleoperation via Gated Expert Selection with Motion Prior

arXiv:2602.09628v2 Announce Type: replace Abstract: Real-time whole-body teleoperation is a critical method for humanoid robots to perform complex tasks in unstructured environments. However, developi

safetyarxiv-cs-ro

Test-time Offline Reinforcement Learning on Goal-related Experience

arXiv:2507.18809v2 Announce Type: replace Abstract: Foundation models compress a large amount of information in a single, large neural network, which can then be queried for individual tasks. There ar

safetyarxiv-cs-lg

The Bayesian Origin of the Probability Weighting Function in Human Representation of Probabilities

arXiv:2510.04698v3 Announce Type: replace-cross Abstract: Humans systematically misrepresent probability in a stereotyped inverse-S pattern. It has been documented for decades, but its origin remains

The critical slowing down in diffusion models

arXiv:2605.12597v1 Announce Type: cross Abstract: Computational sampling has been central to the sciences since the mid-20th century. While machine-learning-based approaches have recently enabled majo

The Horizon Threshold in Cooperative Multi-Agent Reward-Free Exploration

arXiv:2602.01453v3 Announce Type: replace Abstract: We study cooperative multi-agent reinforcement learning in the setting of reward-free exploration, where multiple agents jointly explore an unknown

safetyarxiv-cs-lg

The Joint Gromov Wasserstein Objective for Multiple Object Matching

arXiv:2511.16868v2 Announce Type: replace Abstract: The Gromov-Wasserstein (GW) distance serves as a powerful tool for matching objects in metric spaces. However, its traditional formulation is constr

applicationsarxiv-cs-cv

Think Twice, Act Once: Verifier-Guided Action Selection For Embodied Agents

arXiv:2605.12620v1 Announce Type: new Abstract: Building generalist embodied agents capable of solving complex real-world tasks remains a fundamental challenge in AI. Multimodal Large Language Models

TokaMind for Power Grid: Cross-Domain Transfer from Fusion Plasma

arXiv:2605.11033v1 Announce Type: cross Abstract: TokaMind is a multi-modal transformer (MMT) foundation model pre-trained on tokamak plasma diagnostics data from MAST, where it was shown to outperfor

ToolWeave: Structured Synthesis of Complex Multi-Turn Tool-Calling Dialogues

arXiv:2605.12521v1 Announce Type: cross Abstract: Multi-turn tool calling is essential for LLMs to function as autonomous agents, yet synthesizing the training data required for these capabilities rem

Topology-Preserving Neural Operator Learning via Hodge Decomposition

arXiv:2605.13834v1 Announce Type: cross Abstract: In this paper, we study solution operators of physical field equations on geometric meshes from a function-space perspective. We reveal that Hodge ort

Training LLMs with Reinforcement Learning for Intent-Aware Personalized Question Answering

arXiv:2605.12645v1 Announce Type: cross Abstract: Effective personalized question answering (PQA) in language models requires grounding responses in the user's underlying intent, where intent refers t

TRIAGE: Evaluating Prospective Metacognitive Control in LLMs under Resource Constraints

arXiv:2605.13414v1 Announce Type: new Abstract: Deploying language models as autonomous agents requires more than per-task accuracy: when an agent faces a queue of problems under a finite token budget

Uncertainty-Aware 3D Position Refinement for Multi-UAV Systems

arXiv:2605.13500v1 Announce Type: new Abstract: Reliable real-time 3D localization is essential for multi-UAV navigation, collision avoidance, and coordinated flight, yet onboard estimates can degrade

agentsarxiv-cs-ro

Tutorials

Uncovering Latent Pathological Signatures in Pulmonary CT via Cross-Window Knowledge Distillation

arXiv:2605.12562v1 Announce Type: cross Abstract: Multi-window CT imaging captures complementary pathological information across anatomical structures of differing densities, yet existing deep learnin

tutorialsarxiv-cs-ai

Unified generalization analysis for physics informed neural networks

arXiv:2605.13260v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) and their variational counterparts (VPINNs) are neural networks that incorporate physical laws, making them use

Unweighted ranking for value-based decision making with uncertainty

arXiv:2605.13601v1 Announce Type: new Abstract: As intelligent systems are increasingly implemented in our society to make autonomous decisions, their commitment to human values raises serious concern

Utility-Oriented Visual Evidence Selection for Multimodal Retrieval-Augmented Generation

arXiv:2605.13277v1 Announce Type: cross Abstract: Visual evidence selection is a critical component of multimodal retrieval-augmented generation (RAG), yet existing methods typically rely on semantic

Vector-Quantized Discrete Latent Factors Meet Financial Priors: Dynamic Cross-Sectional Stock Ranking Prediction for Portfolio Construction

arXiv:2605.13407v1 Announce Type: new Abstract: Predicting cross-sectional stock returns is challenging due to low signal-to-noise ratios and evolving market regimes. Classical factor models offer int

VERA-MH: Validation of Ethical and Responsible AI in Mental Health

arXiv:2605.13318v1 Announce Type: new Abstract: Chatbot usage has increased, including in fields for which they were never developed for--notably mental health support. To that end, we introduce Valid

ViDR: Grounding Multimodal Deep Research Reports in Source Visual Evidence

model-releasesarxiv-cs-cv

arXiv:2605.13034v1 Announce Type: new Abstract: Recent deep research systems have improved the ability of large language models to produce long, grounded reports through iterative retrieval and reason

Tutorials

VIPO: Value Function Inconsistency Penalized Offline Reinforcement Learning

arXiv:2504.11944v3 Announce Type: replace-cross Abstract: Offline reinforcement learning (RL) learns effective policies from pre-collected datasets, offering a practical solution for applications wher

tutorialsarxiv-cs-ai

WD-FQDet: Multispectral Detection Transformer via Wavelet Decomposition and Frequency-aware Query Learning

arXiv:2605.13621v1 Announce Type: new Abstract: Infrared-visible object detection improves detection performance by combining complementary features from multispectral images. Existing backbone-specif

safetyarxiv-cs-cv

What Do You Think I Think? Accounting for Human Beliefs Using Second-Order Theory of Mind

arXiv:2605.12745v1 Announce Type: cross Abstract: Discrepancies between an agent's actual knowledge and what a person thinks the agent knows can hinder interactions. If an agent could detect such disc

What Limits Vision-and-Language Navigation ?

arXiv:2605.13328v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) is a cornerstone of embodied intelligence. However, current agents often suffer from significant performance degr

What properties of reasoning supervision are associated with improved downstream model quality?

arXiv:2605.13290v1 Announce Type: new Abstract: Validating training data for reasoning models typically requires expensive trial-and-error fine-tuning cycles. In this work, we investigate whether the

What to Ignore, What to React: Visually Robust RL Fine-Tuning of VLA Models

arXiv:2605.13105v1 Announce Type: new Abstract: Reinforcement learning (RL) fine-tuning has shown promise for Vision-Language-Action (VLA) models in robotic manipulation, but deployment-time visual sh

safetyarxiv-cs-ro

When and Why is Optimistic Multiplicative Weights Slow? The Geometry of Energy Dissipation

arXiv:2605.13242v1 Announce Type: cross Abstract: This paper studies the convergence of the Optimistic Multiplicative Weights Update algorithm (OMWU) in two player zero-sum games. Recent works have id

When Attention Closes: How LLMs Lose the Thread in Multi-Turn Interaction

arXiv:2605.12922v1 Announce Type: new Abstract: Large language models can follow complex instructions in a single turn, yet over long multi-turn interactions they often lose the thread of instructions

When Backdoors Meet Partial Observability: Attacking Real-World Reinforcement Learning

arXiv:2601.14104v2 Announce Type: replace-cross Abstract: Backdoor attacks can cause reinforcement learning (RL) policies to behave normally under clean inputs while executing malicious behaviors when

safetyarxiv-cs-cv

Tutorials

Why is 'Chicago' Predictive of Deceptive Reviews? Using LLMs to Discover Language Phenomena from Lexical Cues

arXiv:2511.13658v2 Announce Type: replace-cross Abstract: Deceptive reviews mislead consumers, harm businesses, and undermine trust in online marketplaces. Machine learning classifiers can learn from

tutorialsarxiv-cs-lg

X-Restormer++: 1st Place Solution for the UG2+ CVPR 2026 All-Weather Restoration Challenge

arXiv:2605.13258v1 Announce Type: cross Abstract: In this work, we present our winning solution for the 8th UG2+ Challenge (CVPR 2026) Track 1: Image Restoration under All-weather Conditions. Our meth

ZeD-MAP: Bundle Adjustment Guided Zero-Shot Depth Maps for Real-Time Aerial Imaging

arXiv:2604.04667v2 Announce Type: replace Abstract: Real-time depth reconstruction from ultra-high-resolution UAV imagery is essential for time-critical geospatial tasks such as disaster response, yet

researcharxiv-cs-cv