Search: “papers”

Beyond Correctness: Toward Automated Novelty Verification with Lean 4

arXiv:2608.14669v1 Announce Type: new Abstract: Artificial intelligence systems applied to mathematics verify correctness but not novelty: an automatically generated theorem can compile in Lean withou

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Beyond Independence: Learning Correlated Views for Variational Incomplete Multi-View Clustering

DGX agent

arXiv:2608.15757v1 Announce Type: new Abstract: Incomplete multi-view clustering (IMVC) aims to uncover shared cluster structures from data with partially observed views. Although recent imputation-fr

tutorialsarxiv-cs-cv

18 Aug 2026

Beyond Tokens: A Survey on Decoding Methods for Large Language and Vision-Language Models

arXiv:2608.14797v1 Announce Type: new Abstract: Large language models (LLMs) and large vision-language models (LVLMs) have demonstrated impressive generative capabilities, yet ensuring their outputs a

researcharxiv-cs-cl

Binarized High-Efficiency RAW Video Restoration and Beyond

arXiv:2608.16756v1 Announce Type: new Abstract: RAW video restoration is fundamental to high-quality low-level perception and serves as the basis for a wide range of downstream vision applications. Wh

Bit-Level Triangular Content-Aware Permutation for Fragile Image Watermarking: Zero False Positive Rate, Single-Bit Sensitivity, and Arbitrary Dimension Support

arXiv:2608.14800v1 Announce Type: cross Abstract: With the growth of digital document exchange, protecting image integrity against attacks such as Vector Quantization (VQ) and collage has become criti

applicationsarxiv-cs-cv

Bitstream Action Recognition is Byte Modeling

model-releasesarxiv-cs-cv

arXiv:2608.15695v1 Announce Type: new Abstract: Conventional action recognition typically relies on successful pixel decoding of the bitstream. However, bitstream corruption during storage or transmis

Braided Vision Transformer for Stroke Detection in Multi-view Retinal Fundus Imaging

arXiv:2608.14722v1 Announce Type: new Abstract: Stroke remains a leading cause of mortality and morbidity worldwide, emphasizing the importance of its accurate and immediate assessment. Retinal fundus

Camera-Agnostic Pruning of 3D Gaussian Splats via Descriptor-Based Beta Evidence

arXiv:2603.21933v2 Announce Type: replace-cross Abstract: The pruning of 3D Gaussian splats is essential for reducing their complexity to enable efficient storage, transmission, and downstream process

Certifying Compressed Language Models: An Audit and a Statistical Toolkit

model-releasesarxiv-cs-lg

arXiv:2608.15046v1 Announce Type: new Abstract: A fraction of a point of benchmark accuracy is the usual evidence that a compressed model is equivalent to its original. That quantity is least informat

CETalk: Continuous Valence-Arousal Control for Audio-Driven 3D Talking Head Generation

arXiv:2608.15110v1 Announce Type: cross Abstract: Emotional 3D talking head generation aims to synthesize expressive facial animations with accurate lip synchronization. However, existing methods ofte

Clause Encounters of the Third Kind: Can LLMs Replace Language Teachers?

arXiv:2608.16286v1 Announce Type: new Abstract: While various organizations now actively encourage LLM use in classrooms, we still lack rigorous, systematic evaluations of how well these models actual

researcharxiv-cs-cl

Local Ai

Closing the Loop: A Control-Theoretic Framework for Provably Stable Time Series Forecasting with LLMs

arXiv:2602.12756v2 Announce Type: replace Abstract: Large Language Models (LLMs) have recently shown exceptional potential in time series forecasting (TSF), leveraging their inherent sequential reason

local-aiarxiv-cs-lg

Local Ai

CM-MAE: A Physics-Guided Cross-Modal Self-Supervised Learning Framework for Vision-Wireless Applications

arXiv:2608.15972v1 Announce Type: cross Abstract: Synchronized camera and wireless measurements observe the same scene through different physical channels. The central difficulty is that a representat

local-aiarxiv-cs-ai

Agents

Competing at Every Price Point with Agentic Evolution over a Menu of LLMs

arXiv:2608.16207v1 Announce Type: new Abstract: Consider a firm that surveys its competition for a particular agentic task and seeks to offer superior accuracy at every competitor price point. A firm

agentsarxiv-cs-ai

Comprehensive language-image pre-training for 3D medical image understanding

arXiv:2510.15042v3 Announce Type: replace Abstract: In the 3D medical image domain, vision-language pre-training is used to create vision-language encoders (VLEs) that can support radiologists by retr

CUBICS: Situation-aware performance estimation for safety-relevant ML components

arXiv:2608.16564v1 Announce Type: new Abstract: Machine learning (ML) is a key technology driving innovation today, but ensuring ML safety remains a major challenge for safety-related applications. A

safetyarxiv-cs-ai

Cyclops: LiDAR as a Camera That Dreams in Color

arXiv:2608.16264v1 Announce Type: new Abstract: Conventionally, robotic perception relies heavily on cameras due to the rich semantic texture they provide. However, their performance degrades signific

safetyarxiv-cs-ro

Decentralized Federated Learning for Heterogeneous Multi-Task Semantic Communication

arXiv:2608.15256v1 Announce Type: new Abstract: Collaborative training in distributed semantic communication (DSC) networks typically relies on decentralized federated learning (DFL). However, pushing

Decision-Driven Regularization: A Blended Model for Learning and Optimization

arXiv:2608.15124v1 Announce Type: new Abstract: In contextual optimization, the decision-maker seeks optimal decisions to minimize a cost function, that varies based on observed features. This context

Decorrelation Is Not Complementarity: Skill, Not Lineage, Governs Trusted-Monitor Ensembles

arXiv:2608.16190v1 Announce Type: cross Abstract: Trusted monitoring has a cheap, trusted model score a stronger untrusted model's actions, and a diverse ensemble of them beats a single stronger monit

DeltaLog: Deferred Materialization of Recurrent States for Linear Attention Decoding

arXiv:2608.15533v1 Announce Type: cross Abstract: Linear attention models eliminate the quadratic prefix computation and context-growing KV cache of softmax attention by replacing pairwise token inter

Depth-Dominant Skeleton Detection for Natural Scenes

arXiv:2608.16367v1 Announce Type: new Abstract: To date, all natural scene skeleton detection follows the paradigm of taking RGB images as the sole input; despite notable progress, methods under this

Detachable Wire Drive : Reconfigurable Robot Architecture with Shared Actuators

arXiv:2608.15461v1 Announce Type: new Abstract: Reconfigurable robots offer significant potential for adapting to diverse tasks; however, conventional centralized architectures often require dedicated

researcharxiv-cs-ro

Detecting Money Laundering in Rwandan Mobile Money: A Machine Learning Framework

model-releasesarxiv-cs-lg

arXiv:2608.15447v1 Announce Type: new Abstract: Mobile money has widened financial access across Sub-Saharan Africa and enlarged the surface for money-laundering and terrorism-financing (ML/TF) activi

Digital Twin Degradation: Detecting Cyber Physical Attacks via Temporal Inconsistencies

arXiv:2608.16159v1 Announce Type: cross Abstract: Digital Twins (DTs) are increasingly used to monitor and analyze Cyber Physical Systems (CPS). However, in adversarial environments, the fidelity of a

Tutorials

Domain Agnostic Text Redaction from Natural Language Rules using Instruction Tuning

arXiv:2608.14693v1 Announce Type: cross Abstract: With the increasing digitization of personal and corporate communication, the automatic sanitization of textual data has become a crucial component of

tutorialsarxiv-cs-ai

Domain-Specific Text Embedding Models for Entity Resolution

arXiv:2608.16161v1 Announce Type: cross Abstract: General-purpose text embedding models are designed to capture semantic similarity but are not optimised for distinguishing entity records that represe

applicationsarxiv-cs-ai

DPNet: Efficient Dead-End Prediction and Avoidance for Vision-Based UAV Navigation

arXiv:2608.16640v1 Announce Type: new Abstract: Vision-based Unmanned Aerial Vehicles (UAVs) often suffer from navigation failures in dead ends due to limited sensing accuracy and range. To address th

applicationsarxiv-cs-ro

Drive, Pack, Fly: The Travelling Thief Problem with Drone

arXiv:2608.16435v1 Announce Type: new Abstract: In collection operations, accumulating payload progressively slows the vehicle, imposing a cumulative penalty on routing efficiency. An onboard drone ca

Agents

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

arXiv:2412.19505v3 Announce Type: replace Abstract: Recent successes in autoregressive (AR) generation models, such as the GPT series in natural language processing, have motivated efforts to replicat

agentsarxiv-cs-cv

DYNASHIELD: A Black-Box Moving Target Defense for LLMs via Dynamic Decoding Customization

arXiv:2412.07672v2 Announce Type: replace-cross Abstract: Large language models (LLMs) remain vulnerable to jailbreak attacks in which adversarial prompts induce harmful outputs. Existing defenses oft

safetyarxiv-cs-cl

Efficient Coreset Selection via K-Nearest Neighbor Graphs

arXiv:2608.16270v1 Announce Type: new Abstract: Coreset selection reduces the cost of model training by replacing a large training set with a small representative subset. Existing gradient-approximati

applicationsarxiv-cs-lg

Enhancing Differentially Private Linear Regression via Public Second-Moment

arXiv:2508.18037v2 Announce Type: replace Abstract: Leveraging information from public data has become increasingly crucial in enhancing the utility of differentially private (DP) methods. Traditional

applicationsarxiv-cs-lg

ER-KANs: Efficient and Robust Kolmogorov-Arnold Networks for Data-Scarce Scientific Machine Learning

arXiv:2608.14773v1 Announce Type: cross Abstract: The efficient-KAN literature---covering Chebyshev, wavelet, and radial-basis-function variants of the original Kolmogorov-Arnold Network---has been be

Evaluating Multimodal LLMs across Text and Audio Modalities for Accessible Disaster Assistance

arXiv:2608.14651v1 Announce Type: new Abstract: Effective disaster risk communication is a foundational humanitarian challenge, yet current emergency infrastructure fails to meet the needs of individu

Evaluating the impact of adversarial traffic patterns on vanet communication using veins simulation

arXiv:2608.14583v1 Announce Type: cross Abstract: Vehicular Ad Hoc Networks (VANETs) are a key component of intelligent transportation systems, enabling real-time communication between vehicles. Howev

Exclusivity-Guided Mask Learning for Semi-Supervised Crowd Instance Segmentation and Counting

arXiv:2603.16241v2 Announce Type: replace Abstract: Semi-supervised crowd analysis is a prominent area of research, as unlabeled data are typically abundant and inexpensive to obtain. However, traditi

Agents

Explaining Reinforcement Learning Decisions in Self-adaptive Systems

arXiv:2608.14620v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has been extensively used in autonomous and self-* systems, but RL policies, especially deep RL ones relying on neural net

agentsarxiv-cs-ai

Extend the Safety Horizon for Intelligent Transportation Systems through Semantic-Aware Cooperative Perception

arXiv:2608.14603v1 Announce Type: cross Abstract: Cooperative perception enables vehicles and infrastructure to exchange sensor data via Vehicle-to-Everything (V2X) communication, extending sensing co

safetyarxiv-cs-ai

Faster, Cheaper, More Accurate: Specialised Knowledge Tracing Models Outperform LLMs

arXiv:2603.02830v2 Announce Type: replace-cross Abstract: Predicting future student responses to questions is particularly valuable for educational learning platforms where it enables effective interv

applicationsarxiv-cs-ai

Tutorials

Feasible and Novel Synthetic Population Generation with Tabular and Sequential Travel Attributes

arXiv:2608.15867v1 Announce Type: cross Abstract: Synthetic populations are critical inputs for activity-based travel demand models, yet generating realistic populations from limited survey data remai

tutorialsarxiv-cs-ai

FETERS: Few-Shot Early Time-Series Classification via Effective Ratio Selection

arXiv:2608.16385v1 Announce Type: new Abstract: Early time-series classification (ETSC) aims to make accurate predictions from partially observed time series as early as possible. Although various sto

FirstDiff: One-Step Diffusion-Based Anomaly Detection for Multivariate Time Series via Initial Noise Prediction

arXiv:2608.15727v1 Announce Type: cross Abstract: Diffusion models have recently shown strong potential for multivariate time-series anomaly detection by learning the distribution of normal data throu

FLOPs vs Real Work: The Importance of Replication in AI Efficiency Assessment

arXiv:2608.14550v1 Announce Type: new Abstract: AI efficiency has recently taken the spotlight in both academy and industry due to massive model scales, high energy demands, and environmental costs. W

FollowUpBot: An LLM-Based Conversational Robot for Automatic Postoperative Follow-up

arXiv:2507.15502v1 Announce Type: cross Abstract: Postoperative follow-up plays a crucial role in monitoring recovery and identifying complications. However, traditional approaches, typically involvin

applicationsarxiv-cs-cl

Formalisms for Robotic Mission Specification and Execution: A Comparative Analysis

arXiv:2603.15427v2 Announce Type: replace-cross Abstract: Robots are increasingly deployed across diverse domains and designed for multi-purpose operation. As robotic systems grow in complexity and op

applicationsarxiv-cs-ro

From Continuous Design to Delay-Aware Discrete Synthesis: Guaranteed High-Bandwidth Joint Control for PMSM Drives

arXiv:2608.14937v1 Announce Type: new Abstract: The increasing dynamic demands of modern robotic joints require current controllers to achieve high bandwidth over wide operating ranges of speed, accel

researcharxiv-cs-ro

From Positionwise Confidence to Prefix Scheduling: Verifier Skipping in Speculative Decoding

arXiv:2608.14787v1 Announce Type: cross Abstract: Speculative decoding is a leading technique to reduce the cost of autoregressive generation by using a small drafter to propose several tokens, which

safetyarxiv-cs-cl