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Prescribed-Basis Coefficient-to-Coefficient Neural Operator for Partial Differential Equations

arXiv:2510.10350v3 Announce Type: replace-cross Abstract: Operator learning provides a data-driven approach to approximating solution operators of partial differential equations, but its effectiveness

safetyarxiv-cs-lg

Principles of Robot Autonomy

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DGX agent

arXiv:2608.03496v1 Announce Type: cross Abstract: Autonomous robots are moving rapidly from research labs into everyday life - on roads, in the air, in warehouses, and in space. Robot autonomy is no l

agentsarxiv-cs-ai

5 Aug 2026

PRISM: Powerful Time Series to Image (TS2I) Representations for Multivariate Anomaly Detection

arXiv:2608.03926v1 Announce Type: cross Abstract: Time series anomaly detection (TSAD) underpins applications in predictive maintenance, finance, and cloud computing, however performance remains sensi

applicationsarxiv-cs-ai

PRISMA: Improving the Accuracy-Latency Frontier of Diffusion-based PDE Solvers Using Physics-Informed Spectral Attention

arXiv:2512.01370v2 Announce Type: replace-cross Abstract: Diffusion-based solvers for partial differential equations (PDEs) are often bottle-necked by slow gradient-based test-time optimization routin

Privacy-Preserving AI Verification via Minimal Information Disclosure

arXiv:2608.02774v1 Announce Type: cross Abstract: AI verification crosses a trust boundary: a verifier must learn enough to establish an authorized claim, yet the same evidence can reveal sensitive de

PRIVEE: Privacy-Preserving Vertical Federated Learning Against Feature Inference Attacks

arXiv:2512.12840v2 Announce Type: replace-cross Abstract: Vertical Federated Learning (VFL) enables collaborative model training across organizations that share common user samples but hold disjoint f

researcharxiv-cs-ai

Probing Character-level Transformers for the Spanish L-shaped Morphome

arXiv:2608.03452v1 Announce Type: new Abstract: When a transformer learns an irregular morphological pattern, what has it learned? Our test case is the Spanish L-shaped morphome, a complex irregular p

local-aiarxiv-cs-cl

Tutorials

Progressive Learning of a Diffusion-based Inpainting Model for Separating Overlapped Fingerprints

arXiv:2608.03937v1 Announce Type: new Abstract: Overlapped friction ridge patterns are a recurring problem in latent fingerprints recovered from crime scenes and in live-scan scenarios where residual

tutorialsarxiv-cs-cv

ProPRL: Property-Aware Prerequisite Relation Learning in Educational Knowledge Graphs

arXiv:2608.03006v1 Announce Type: new Abstract: Prerequisite relation learning is central to adaptive instruction, yet existing methods often formulate it as conventional link prediction, limiting the

applicationsarxiv-cs-ai

Provably Learning Multi-Head Attention with Queries

model-releasesarxiv-cs-lg

arXiv:2608.03294v1 Announce Type: new Abstract: We study the problem of learning multi-head softmax attention from black-box input-output access. The learner may query arbitrary real-valued token sequ

PULSE: An Executable Contract Language for Spatiotemporal Knowledge Graph Engineering

arXiv:2608.02630v1 Announce Type: new Abstract: Knowledge graph engineering often distributes accepted state, observations, constraints, processes, and hypothetical scenarios across artifacts whose co

Quality Control Algorithms for Pattern Counting

arXiv:2608.03439v1 Announce Type: cross Abstract: In recent work, Marcussen, Rubinfeld, and Sudan introduced the notion of quality control problems, which aim to capture the task of determining if a g

researcharxiv-cs-lg

Quantifying Hallucinations in Language Language Models on Medical Textbooks

arXiv:2603.09986v3 Announce Type: replace-cross Abstract: Hallucinations, the tendency for large language models to provide responses with factually incorrect and unsupported claims, is a serious prob

Quantization Effects on Biomedical LLM Reliability

model-releasesarxiv-cs-lg

arXiv:2608.03854v1 Announce Type: new Abstract: When decoder language models are used as classifiers, predicted class probabilities depend on implementation choices, including the prompt template, ver

Quo Vadis, World Modeling?

arXiv:2608.02713v1 Announce Type: cross Abstract: Continually improving agents require dynamic interaction feedback beyond static supervision, yet direct real-environment interaction is costly, slow,

Qwen-3D: A Generalist 3D Vision-Language Model for Spatial Understanding

model-releasesarxiv-cs-cv

arXiv:2608.02980v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have achieved remarkable success on images and short videos, yet scaling them to long videos remains challenging due to f

Reachability Is Not Realization: Tracing the Sources of LLM Benchmark Gains

arXiv:2608.03219v1 Announce Type: new Abstract: Benchmark gains are often treated as evidence of greater LLM capability. Yet the same gain can reflect different changes in model behavior. A model may

RealWeather: Realistic and Scene-Faithful Weather Translation with Driving World Models

arXiv:2608.02953v1 Announce Type: new Abstract: Realistic weather translation is valuable for developing and evaluating autonomous driving systems, yet collecting paired videos of the same scenes unde

safetyarxiv-cs-cv

ReCamDriving: LiDAR-Free Camera-Controlled Video Synthesis for Novel Trajectories

arXiv:2512.03621v3 Announce Type: replace Abstract: Synthesizing multi-pass videos is important for autonomous driving. While current repair-based methods often struggle with out-of-distribution artif

agentsarxiv-cs-cv

Rectify Then Diffuse: Disentangling Concepts Before Denoising Trajectory Unfolds

arXiv:2608.03135v1 Announce Type: cross Abstract: Text-to-image diffusion models can generate individual concepts well, but they often omit or merge concepts incorrectly with multiple concepts. We tra

Recurrent Contrastive Learning for Imbalanced Medical Image Classification

arXiv:2608.03304v1 Announce Type: new Abstract: Medical image classification often suffers from class imbalance due to the inherent disparities in disease incidence. Existing approaches, such as class

researcharxiv-cs-cv

ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning

arXiv:2608.03972v1 Announce Type: new Abstract: On-policy training has emerged as a powerful post-training paradigm for improving the reasoning capabilities of large language models, and is often enha

Reinforcement Learning with Evolving Rubrics as Rewards for Audio Reasoning

arXiv:2608.02831v1 Announce Type: cross Abstract: Audio reasoning is essential for machine understanding of the acoustic world. Reinforcement learning with verifiable rewards can elicit such reasoning

safetyarxiv-cs-cl

Relational Priors as Convergence Pressure in LLM-Based Multi-Agent Systems

arXiv:2608.03239v1 Announce Type: new Abstract: Large language model-based multi-agent systems (LLM-MAS) are designed through roles, debate protocols, and aggregation rules. These choices create impli

safetyarxiv-cs-cl

Representing Random Utility Choice Models with Neural Networks

arXiv:2207.12877v3 Announce Type: replace Abstract: Motivated by the successes of deep learning, we propose a class of neural network-based discrete choice models, called RUMnets, inspired by the rand

applicationsarxiv-cs-lg

Residual Flow Matching with Dynamic Cross-Interaction for 3D Multi-Person Motion Prediction

arXiv:2608.03379v1 Announce Type: new Abstract: 3D multi-person motion prediction requires modeling both individual kinematics and inter-person interactions. While Flow Matching is effective for multi

agentsarxiv-cs-cv

Resume Means Resume: A Machine-Checked Conformance Contract for Checkpoint, Interrupt, and Resume Semantics in Workflow Persistence Layers

arXiv:2608.03836v1 Announce Type: new Abstract: A framework that persists execution state so a run can be interrupted, survive a crash, and continue must decide what a resume means for effects that al

agentsarxiv-cs-lg

Rethinking Modality Reliability in Multimodal Sentiment Analysis with Incomplete Observations

arXiv:2608.03611v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) integrates text, audio, and vision to infer human affect, yet real-world multimodal observations are often incomplet

Rethinking Self-Evolving Agent Skills: Feedback Dynamics over Multiple Rounds

arXiv:2608.02636v1 Announce Type: cross Abstract: Self-evolving skill systems promise to improve agents by turning execution feedback into persistent skill updates without changing the underlying mode

Rethinking Uncertainty Quantification and Entanglement in Image Segmentation

arXiv:2603.18792v2 Announce Type: replace Abstract: Uncertainty quantification (UQ) is crucial in safety-critical applications such as medical image segmentation. Total uncertainty is typically decomp

safetyarxiv-cs-cv

Reversing Arrows in Large Language Models

arXiv:2608.03512v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance on text-to-knowledge graph generation and related tasks. Nevertheless, it is still unclear

Tutorials

Revisiting TD Target Aggregation under Uncertainty in Q-Learning

arXiv:2608.03069v1 Announce Type: new Abstract: Deep Q-Networks (DQNs) learn value functions through bootstrapped temporal-difference updates, where future returns are approximated using a greedy maxi

tutorialsarxiv-cs-lg

RIDGE: Re-Noising with Internal Dynamic Guidance for Image Editing

arXiv:2608.03059v1 Announce Type: new Abstract: Inversion-free flow-based image editing avoids latent inversion, but still requires a target-side state at every editing step. The widely used equal-dis

safetyarxiv-cs-cv

Risk Occupancy: A New and Efficient Paradigm through Vehicle-Road-Cloud Collaboration

arXiv:2408.07367v3 Announce Type: replace Abstract: This paper proposes a novel 4D risk occupancy (RiskOcc) perception paradigm under the Vehicle-Road-Cloud integrated architecture, which unifies obje

local-aiarxiv-cs-ro

Risky Business: Measuring The Faithfulness-Safety Tension

arXiv:2608.03745v1 Announce Type: new Abstract: Chain-of-Thought (CoT) reasoning offers a promising window into model monitoring. However, monitoring relies on faithfulness, i.e., the model output str

RoboReact: Agentic Skill Distillation from Generated Egocentric Videos for Generalizable Whole-Body Manipulation

arXiv:2608.03387v1 Announce Type: new Abstract: Humanoid robots have the potential to perform dexterous manipulation in human environments, yet acquiring diverse and generalizable skills remains costl

agentsarxiv-cs-ro

Robust Biharmonic Skinning Using Geometric Fields

arXiv:2406.00238v3 Announce Type: replace-cross Abstract: Bounded bihramonic weights are a popular tool used to rig and deform characters for animation, to compute reduced-order simulations, and to de

researcharxiv-cs-lg

Robust Counterfactual Policy Optimisation via Nondeterministic Causal Models

arXiv:2608.02893v1 Announce Type: cross Abstract: Counterfactual inference approaches for sequential decision-making typically assume deterministic causal models, where all randomness stems from laten

Robust General Utility for Reinforcement Learning

arXiv:2608.03562v1 Announce Type: new Abstract: Reinforcement learning (RL) with general utility extends classic RL by optimizing an arbitrary utility functional of the policy-induced occupancy measur

safetyarxiv-cs-lg

Robust Low-Tubal-Rank Tensor Completion under Cross-Concentrated Sampling

arXiv:2608.03928v1 Announce Type: cross Abstract: Tensor cross-concentrated sampling (t-CCS) bridges entrywise sampling and t-CUR slice-wise sampling by observing entries only within selected horizont

researcharxiv-cs-lg

Route-Align-Verify for Functional Correctness in Code Generation

arXiv:2608.03341v1 Announce Type: cross Abstract: Large language models (LLMs) have substantially improved code generation, yet achieving strong functional correctness remains difficult, especially fo

Rubrics as Privileged Information for Open-Ended Generation

arXiv:2608.02948v1 Announce Type: cross Abstract: On-policy self-distillation (OPSD), where a single model acts as both student and teacher with different contexts, has shown promise in verifiable dom

S^3-Diff: Structural Semantic Synergy Diffusion Model for High Fidelity Super Resolution of Pathological Images

arXiv:2608.03540v1 Announce Type: new Abstract: Digital pathology relies on high-resolution whole slide images for accurate diagnosis, yet limitations in imaging devices, storage, and transmission oft

researcharxiv-cs-cv

S^3: Improving Agent Safety through Multi-Stage Defense

arXiv:2608.02683v1 Announce Type: cross Abstract: Large Language Model (LLM) agents rely on multi-stage agentic workflows, with stages such as memory, planning, and tool execution, to accomplish compl

SAGE: Semantic Explainability of Attention-Based Survival Models in Computational Pathology

arXiv:2608.02803v1 Announce Type: cross Abstract: Attention-based multiple instance learning (ABMIL) is the predominant approach for slide-level prediction in computational pathology, yet its attentio

local-aiarxiv-cs-ai

SAKI: Score-Aware Low-Rank Key Indexing for Long-Context KV Retrieval

model-releasesarxiv-cs-lg

arXiv:2608.03228v1 Announce Type: new Abstract: Existing low rank KV cache methods preserve either model weights or key variance, neither of which directly reflects the attention scores used during in

SAMSEM -- A Generic and Scalable Approach for IC Metal Line Segmentation

arXiv:2603.16548v2 Announce Type: replace-cross Abstract: In light of globalized hardware supply chains, the assurance of hardware components has gained significant interest, particularly in cryptogra

applicationsarxiv-cs-cv

SAT-Edge-Agent: Hardware-in-the-Loop Edge-Agent Orchestration for Onboard Satellite Intelligence

arXiv:2608.03728v1 Announce Type: new Abstract: Onboard satellite intelligence requires a task layer that translates mission intent into local tool calls, exposes execution state, and returns machine-

local-aiarxiv-cs-ai