Search: “papers”

Dreamer-SAC: Off-Policy Learning in Latent World Models for Sample-Efficient Autonomous Driving

arXiv:2608.10386v1 Announce Type: new Abstract: Sample-efficient reinforcement learning for autonomous driving is often limited by the trade-off between data efficiency and model bias. While world mod

safetyarxiv-cs-lg

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DriveVLA-M0: Failure-Aware Memory Augmentation for Autonomous Driving

DGX agent

arXiv:2608.10413v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for end-to-end autonomous driving by enabling unified reasoning across

model-releasesarxiv-cs-cv

12 Aug 2026

Dual Stress: Runtime Safety Monitoring for Safety-Constrained MPC Navigation

arXiv:2608.10791v1 Announce Type: new Abstract: Runtime hazard monitors for autonomous naviga- tion are conventionally built from geometric quantities: predicted clearance, time to collision, and requ

safetyarxiv-cs-ro

Efficient Weak-Entropy PINN for Solving Hyperbolic Conservation Laws

arXiv:2608.10389v1 Announce Type: cross Abstract: In recent years, neural networks have significantly advanced numerical solutions of partial differential equations (PDEs). However, solving PDEs with

Energy and Performance Benchmarking of Deep Learning Models for Breast Cancer Detection

arXiv:2608.09996v1 Announce Type: cross Abstract: Recent advances in machine learning have greatly improved breast cancer detection, enabling more accurate and timely diagnosis. Deep learning (DL) mod

Entropy-Centric Explainable AI for Remote Sensing Image Segmentation

arXiv:2608.11064v1 Announce Type: cross Abstract: Artificial intelligence (AI) has become a powerful approach to solving complex problems in critical domains. Many concerns arise regarding the decisio

Applications

Evidence-Based Scientific Question Discovery: A Framework with Historical Backtesting

arXiv:2608.09968v1 Announce Type: cross Abstract: Current AI systems are optimized for answering questions; the scientific enterprise is bottlenecked earlier, at discovering the questions worth invest

applicationsarxiv-cs-ai

EVIL-Detect for NLPCC 2026 Shared Task 6: LLM-Generated Text Detection

arXiv:2608.10698v1 Announce Type: new Abstract: The rapid development of large language models (LLMs) has increased the need for reliable detection of LLM-generated text, especially in realistic Chine

researcharxiv-cs-cl

FADE: From Passive Verification to Active Discovery in Counterfactual Video Understanding

model-releasesarxiv-cs-cv

arXiv:2608.10764v1 Announce Type: new Abstract: Counterfactual video understanding evaluates whether models grasp physical and commonsense regularities. However, existing multiple-choice question (MCQ

Applications

Graphical Models of False Information and Fact Checking Ecosystems

arXiv:2208.11582v2 Announce Type: replace-cross Abstract: The wide spread of false information online, including misinformation and disinformation, has become a major problem for our highly digitised

applicationsarxiv-cs-ai

Grid-Preserving Knowledge Distillation: Transferring Convolutional Inductive Bias to Vision Transformers under Data Scarcity

arXiv:2608.10723v1 Announce Type: new Abstract: Vision Transformers underperform convolutional networks when training data is scarce, and distilling convolutional inductive biases from a CNN teacher i

local-aiarxiv-cs-cv

Gromov-Wasserstein Quantization and Clustering: Structure, Rates, and Algorithms

arXiv:2608.11016v1 Announce Type: cross Abstract: Clustering is a fundamental class of data analysis techniques with the most important representatives being centroid-based methods like k-means. Such

Hardware

Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4

arXiv:2608.10103v1 Announce Type: cross Abstract: High-performance Tensor Core kernels rely on a low-level PTX pipeline built from asynchronous data movement with cp.async, warp-level matrix loads wit

hardwarearxiv-cs-ai

HexEval: An Evidence-Driven Hexagonal Framework for Multidimensional Scholar Assessment

arXiv:2608.10584v1 Announce Type: new Abstract: Scholar assessment plays a fundamental role in faculty recruitment, funding allocation, academic promotion, and talent discovery. Existing scholar asses

Agents

Hierarchical Compositionality for An Assistive AI Agent

arXiv:2608.10330v1 Announce Type: new Abstract: AI agents are increasingly being developed to assist humans in various applications, and Large Language Models and other deep network architectures are

agentsarxiv-cs-ai

Agents

If you’re interested in checking out LlamaParse for document extraction, sign up here: https://login.llamaindex.ai/sign-up

A 36‑page ArXiv whitepaper titled **ExtractBench** was released by Jerry Liu (jerryjliu0), describing a large‑scale, schema‑guided benchmark for real‑world document extraction from complex enterprise

agentsjerry-liu--x

Implicit representations are dead. Long live explicit primitives!

model-releasesarxiv-cs-cv

arXiv:2608.10001v1 Announce Type: cross Abstract: Continuous parameterization of medical data has emerged as a powerful paradigm for resolution-independent image representation. While Implicit Neural

InterPruner: Interactive Structured Pruning via Taylor-Implicit Criterion and Language-Prior Modulator for Multimodal Object Detection

arXiv:2608.10724v1 Announce Type: new Abstract: Multimodal object detection proves effective in remote sensing, especially the RGB-Infrared paradigm. The parallel feature extractors provide rich multi

researcharxiv-cs-cv

Learning Gaussian Structure: Intervention-Guided Density Control for Feed-Forward Driving Reconstruction

arXiv:2608.11077v1 Announce Type: new Abstract: Feed-forward Gaussian reconstruction has recently emerged as an efficient approach for driving scene reconstruction. However, prevailing LiDAR-based met

local-aiarxiv-cs-cv

Tutorials

Link-adaptive digital twin for robust physical-layer modeling in hybrid-amplified ultra-wideband optical networks

arXiv:2608.10517v1 Announce Type: cross Abstract: Accurate physical-layer modeling is increasingly essential for reliable ultra-wideband operation and capacity optimization, especially under the inten

tutorialsarxiv-cs-lg

Logit-Boundary Geometric Belief Interfaces and Sparse Sheaf-Enclave Protocols: A Self-Contained Substrate for Secure Network Electronic Health Record (EHR) Interoperability

model-releasesarxiv-cs-ai

arXiv:2608.10300v1 Announce Type: new Abstract: Electronic health-record interoperability is a boundary problem: legacy systems, generative models, terminology services, identity systems, and human re

MarkNull: Model-Agnostic Watermark Removal in AI-Generated Images via On-Manifold Latent Manipulation

arXiv:2608.10166v1 Announce Type: cross Abstract: Digital watermarking has emerged as a critical technique for provenance and copyright attribution in AI-generated imagery, yet its robustness against

safetyarxiv-cs-ai

Mixture-of-Experts-based Entropy Model for Learned Image Compression

arXiv:2608.10947v1 Announce Type: new Abstract: Learned image compression has seen significant progress in recent years with the development of end-to-end learned models that achieve better compressio

researcharxiv-cs-cv

MoE Proxy Models for Low-Cost Failure Reproduction and Diagnosis in LLM RL Post-Training

arXiv:2608.10823v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training of large language models (LLMs) is computationally intensive and involves complex system pipelines with substa

OmniVTA: Visuo-Tactile World Modeling for Contact-Rich Robotic Manipulation

arXiv:2603.19201v3 Announce Type: replace Abstract: Contact-rich manipulation tasks, such as wiping and assembly, require accurate perception of contact forces, friction changes, and state transitions

safetyarxiv-cs-ro

OpenDPDv2: A Unified Learning and Optimization Framework for Neural Network Digital Predistortion

arXiv:2507.06849v3 Announce Type: replace-cross Abstract: Neural network (NN)-based Digital Predistortion (DPD) improves linearization for wideband radio frequency (RF) power amplifiers (PAs) but ofte

Optimized Sequential Testing for Binary Ensemble Classifiers

model-releasesarxiv-cs-lg

arXiv:2606.15237v1 Announce Type: cross Abstract: Ensemble classifiers are predictive models that combine the results of simpler base models, often by majority vote. A classic example is random forest

Pair-Centric Graph Rewiring for Over-Squashing via Optimal Transport-Guided Communication Alignment

arXiv:2608.10619v1 Announce Type: new Abstract: Message-passing neural networks (MPNNs) often struggle when task-relevant information is distributed across distant regions of a graph, since local prop

safetyarxiv-cs-lg

Partially Observable Learning for Multi-Platform Dispatch Optimization

arXiv:2608.10897v1 Announce Type: new Abstract: Instant delivery platforms have become a critical component of urban logistics, increasingly relying on crowdsourced couriers to fulfill highly dynamic

safetyarxiv-cs-lg

Policy Convergence and Divergence Across National and Within Regional AI Strategies: A Policy Design Element Analysis

arXiv:2608.11006v1 Announce Type: cross Abstract: Governments worldwide have responded to the rapid expansion of AI by publishing national and regional AI strategies. Comparing national and regional A

safetyarxiv-cs-ai

Agents

Recovering Wasted Compute in Autoresearch Agents

arXiv:2608.10424v1 Announce Type: new Abstract: A slew of recent works develop agents for solving research problems end-to-end, a paradigm increasingly referred to as autoresearch. Such agents have in

agentsarxiv-cs-ai

Reinforcement Learning-Based Laser Cutting Machine Parameter Optimization

model-releasesarxiv-cs-ai

arXiv:2608.10549v1 Announce Type: new Abstract: Achieving high accuracy in laser-based cutting of optical films requires careful tuning of parameters such as focal length and laser power beam, adjuste

ReLTEx: Reliable LLM-based Taxonomy Expansion

model-releasesarxiv-cs-ai

arXiv:2608.10970v1 Announce Type: cross Abstract: Recent advances in Large Language Models (LLMs) have demonstrated strong capabilities in generating semantically relevant concepts and relations, maki

ReRound: Reconstructive Rounding to Resolve Midpoint Ambiguity in Calibration-Free LLM Quantization

model-releasesarxiv-cs-cl

arXiv:2608.11045v1 Announce Type: cross Abstract: ReRound (Reconstructive Rounding) is a post-training quantization method that addresses the midpoint ambiguity inherent in standard round-to-nearest (

Retrieval-Corrected Conformal Prediction for Time Series

arXiv:2608.10553v1 Announce Type: cross Abstract: Conformal prediction (CP) provides distribution-free prediction intervals for fixed forecasters, but its standard calibration procedure is often ineff

local-aiarxiv-cs-ai

Risk-Averse Wasserstein Distributionally Robust Online Learning

arXiv:2602.20403v2 Announce Type: replace Abstract: We study distributionally robust online learning, where a risk-averse learner updates decisions sequentially to guard against worst-case distributio

Robust Sliding Mode and Admittance Control of Underactuated Aerial Manipulators for Contact-Based Inspection

arXiv:2608.10656v1 Announce Type: new Abstract: Contact-based industrial inspection requires aerial platforms to maintain stable interaction while rejecting disturbances. Underactuated aerial manipula

safetyarxiv-cs-ro

RTSKG: Building a Rail Transit Station Knowledge Graph Dataset

arXiv:2608.11080v1 Announce Type: new Abstract: Rail transit systems play a vital role in urban mobility and economic development. As key components of such systems, rail transit stations function as

Applications

Self-Knowledge Retrieval Augmented Generation Framework for Patent Matching

arXiv:2608.11030v1 Announce Type: cross Abstract: Patent retrieval and matching based on large language models (LLMs) play a vital role in intellectual property protection. However, due to the complex

applicationsarxiv-cs-cl

Sensor-Informed Per-Point Covariance for Structured-Light 3D Imaging

arXiv:2608.10888v1 Announce Type: new Abstract: Per-point uncertainty models are important in structured-light 3D reconstruction for probabilistic registration, fusion, and quality assessment. In prac

local-aiarxiv-cs-cv

SinD 2.0: A Multi-City UAV Dataset with Semantic Risk Annotations for SOTIF-Oriented Safety Validation at Signalized Intersections

model-releasesarxiv-cs-ro

arXiv:2607.16943v2 Announce Type: replace Abstract: Safety validation at signalized intersections remains a critical bottleneck for the deployment of autonomous driving systems (ADS), as these scenari

sLTN: Structural Logic Tensor Networks

arXiv:2608.11136v1 Announce Type: new Abstract: Logic Tensor Networks (LTN) provide a neurosymbolic framework in which first-order logic is interpreted through tensor operations, enabling logical cons

Smart Enough to Go Extinct? An Evolutionary Challenge to the Value of General Intelligence and Its Ethical Implications for AGI

arXiv:2608.10730v1 Announce Type: cross Abstract: The pursuit of artificial general intelligence (AGI) rests on a seemingly self-evident premise: that general intelligence, the kind of flexible, domai

safetyarxiv-cs-ai

TEAMMix: Taxonomy Enrichment Augmentation and Minority-augmented Mixing Strategy for LLM-enhanced Weak-Supervised Hierarchical Text Classification

arXiv:2608.11044v1 Announce Type: new Abstract: Hierarchical Text Classification (HTC), as a critical text mining task, faces challenges such as complex label hierarchies and class imbalance. Existing

researcharxiv-cs-cl

TEASR: Training-Efficient Any-Step Diffusion Transformer for Real-World Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2606.16188v2 Announce Type: replace Abstract: Diffusion models excel in Real-World Image Super-Resolution (Real-ISR) due to their powerful generative priors but suffer from slow iterative sampli

TemMed-Bench: Evaluating Temporal Medical Image Reasoning in Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2509.25143v2 Announce Type: replace-cross Abstract: Existing medical reasoning benchmarks for vision-language models primarily focus on analyzing a patient's condition based on an image from a s

The Evaluation Protocol Determines the Result: An Independent Reproduction of LeWorldModel on TwoRoom

model-releasesarxiv-cs-lg

arXiv:2608.10145v1 Announce Type: new Abstract: LeWorldModel trains a latent world model with a prediction loss and a single anti-collapse regulariser, and reports approximately 87% of goals reached o

The Illusion of Cross-Lingual Safety in Low-Resource Languages

arXiv:2608.11146v1 Announce Type: new Abstract: Safety alignment in large language models (LLMs) is largely developed in English, assuming these safeguards generalize across multilingual settings. How

local-aiarxiv-cs-cl