Search: “papers”

arXiv:2607.22598v1 Announce Type: cross Abstract: Educational chatbots powered by large language models (LLMs) show promising effects on learning outcomes, yet most systems delegate pedagogical decisi

hardwarearxiv-cs-ai

A General Deep Learning Framework for Wireless Resource Allocation under Discrete Constraints

DGX agent

arXiv:2603.19322v2 Announce Type: replace-cross Abstract: While deep learning (DL)-based methods have achieved remarkable success in continuous wireless resource allocation, efficient solutions for pr

model-releasesarxiv-cs-ai

28 Jul 2026

Hardware

A Motion-Aware Vector Quantization Framework with Centroid Reuse for Efficient VLA Inference

arXiv:2607.24148v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated strong potential for embodied AI, yet their high inference latency on GPUs limits real-time deploy

hardwarearxiv-cs-ai

A note on the motion representation and configuration update in time stepping schemes for the constrained rigid body

arXiv:2607.24317v1 Announce Type: new Abstract: The dynamics of a holonomically constrained rigid body can be modeled by Newton-Euler equations subjected to geometric constraints. This is frequently f

researcharxiv-cs-ro

A Reconstruction-Based Framework for Caption Evaluation Beyond Reference Captions

arXiv:2607.23235v1 Announce Type: new Abstract: Image captioning is a primary task in vision--language research, yet assessing how faithfully a caption preserves image semantics without relying on ref

A scalable online machine learning approach for Stock Recommendation

arXiv:2607.23120v1 Announce Type: cross Abstract: Stock recommendation systems face the dual challenge of adapting to rapidly changing market conditions while maintaining low-latency predictions for e

applicationsarxiv-cs-ai

A Simple, Optimal and Efficient Algorithm for Online Exp-Concave Optimization

arXiv:2512.23190v3 Announce Type: replace Abstract: Online eXp-concave Optimization (OXO) is a fundamental problem in online learning, where the goal is to minimize regret when loss functions are expo

A Statistical Difference between Single-Layer Learning and Hierarchical Learning in Wide Neural Networks

arXiv:2607.23397v1 Announce Type: new Abstract: Hierarchical neural networks are widely used in artificial intelligence, yet their mathematical properties remain incompletely understood. In the infini

A Unified Stereo Geometry Estimation Framework for Disparity and Surface Normal

arXiv:2607.24024v1 Announce Type: new Abstract: Stereo matching and surface normal estimation are fundamental tasks in 3D vision. However, existing feed-forward stereo methods still struggle to produc

AdaKAN: A dual-branch adaptive Kolmogorov-Arnold network for medical image segmentation

arXiv:2607.22891v1 Announce Type: new Abstract: Medical image segmentation is a fundamental task in computer-aided diagnosis, yet it remains challenging due to the complexity of anatomical structures

AIFL: A Global Daily Streamflow Forecasting Model Using a Deterministic LSTM Pre-trained on ERA5-Land and Fine-tuned on IFS

arXiv:2602.16579v2 Announce Type: replace-cross Abstract: Reliable global streamflow forecasting is essential for flood preparedness and water resource management, yet data-driven models often suffer

An Interactive Vision Language Platform for Cognitive Remediation in Schizophrenia

arXiv:2607.22721v1 Announce Type: cross Abstract: Cognitive remediation tasks often require patients to perform structured actions involving object manipulation and sequential reasoning. For patients

An MLIR-Based Compilation Method for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2607.15865v2 Announce Type: replace Abstract: Large Language Models (LLMs) have become the dominant workload on modern AI accelerators, yet deploying them on specialized hardware still faces two

ANSR-DT: A Neuro-Symbolic Framework for Adaptive and Explainable Digital Twins

arXiv:2501.08561v5 Announce Type: replace Abstract: Digital twins are increasingly used to monitor and optimize industrial systems, yet many existing frameworks remain difficult to interpret, slow to

Answering Path Queries under Linear and Guarded Existential Rules

arXiv:2607.22636v1 Announce Type: new Abstract: Ontology-mediated query answering is concerned with the problem of answering queries over knowledge bases consisting of a database instance and an ontol

safetyarxiv-cs-ai

ARdena: Scenario-driven control of real-time LLM agents

arXiv:2607.22651v1 Announce Type: new Abstract: Large language models (LLMs) have enabled increasingly capable conversational agents, but reliably controlling their behavior in real-time interactive e

safetyarxiv-cs-ai

AutoCluster, AutoTopicModeling, AutoTrendAnalysis: A Complete AutoML Pipeline for Predicting Emerging Trends

arXiv:2607.22641v1 Announce Type: cross Abstract: Predicting emerging trends is vital for businesses, researchers, and policymakers; yet traditional approaches often lack scalability and adaptability.

BC-NMPC: Battery-Constrained NMPC with Propulsion Prediction and Replanning for High-Speed Flight

arXiv:2607.23867v1 Announce Type: new Abstract: Trajectory tracking performance of Uncrewed Aerial Vehicles (UAVs) degrades during high-speed and agile flight due to the depletion of the battery and s

applicationsarxiv-cs-ro

Benchmarking LLMs for Verilog Design Flows

arXiv:2607.22759v1 Announce Type: cross Abstract: Large language models (LLMs) show promise in code generation, but their capabilities to produce correct, synthesizable hardware description language (

Beyond Directed Acyclic Graphs: Causal Zeros and Causal Differential Equations

arXiv:2607.22910v1 Announce Type: new Abstract: Pearl's structural causal model (SCM) framework, built on directed acyclic graphs (DAGs) and the do-calculus, is the dominant formal language for causal

researcharxiv-cs-lg

Tutorials

BeyondFusion: Self-Aligned Latent Diffusion for Calibration-Free Infrared Super-Resolution and Infrared-Visible Fusion

arXiv:2607.24110v1 Announce Type: new Abstract: Mobile infrared-visible imaging typically pairs a compact infrared sensor with a high-resolution visible camera for complementary perception. While cros

tutorialsarxiv-cs-cv

BHARATI: Morphology-Aware Tokenizers for Classical Indian Languages with Subword Fertility Analysis

model-releasesarxiv-cs-cl

arXiv:2607.23319v1 Announce Type: new Abstract: Standard subword tokenization algorithms such as Byte-Pair Encoding (BPE) and SentencePiece are trained predominantly on modern language corpora and pro

Bitcoin Price Direction Prediction via Regime-Aware Multi-Modal Fusion of Social Sentiment and Technical Features

arXiv:2607.23370v1 Announce Type: new Abstract: Bitcoin price prediction on sub-daily timescales is a hard open problem in computational finance. Bitcoin exhibits fat-tailed returns, non-stationary dy

applicationsarxiv-cs-lg

Breaking the Total Variance Barrier: Sharp Sample Complexity for Linear Heteroscedastic Bandits with Fixed Action Set

arXiv:2607.23679v1 Announce Type: new Abstract: Recent years have witnessed increasing interests in tackling heteroscedastic noise in bandits and reinforcement learning. In these works, the cumulative

researcharxiv-cs-lg

Can an Actor-Critic Optimization Framework Improve Analog Design?

arXiv:2603.24714v2 Announce Type: replace Abstract: Analog design often slows down because even small changes to device sizes or biases require expensive simulation cycles, and high-quality solutions

researcharxiv-cs-lg

Cascade Forgery Mining Network for Fingerprint Presentation Attack Detection

arXiv:2607.24090v1 Announce Type: new Abstract: Fingerprint Presentation Attack Detection (PAD) is a critical component of fingerprint identification systems, serving as a protective measure against u

CausAdv: A Causal-based Framework for Detecting Adversarial Examples

arXiv:2411.00839v4 Announce Type: replace-cross Abstract: Deep learning has led to tremendous success in computer vision, largely due to Convolutional Neural Networks (CNNs). However, CNNs have been s

Characterisation of Density-based FM generation methods in the context of Information Fusion

arXiv:2607.23243v1 Announce Type: new Abstract: Fuzzy Integral (FI) based aggregation provides a powerful mechanism for nuanced aggregation, for example, in ensemble approaches or decision-level fusio

ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding

arXiv:2607.24743v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundam

Closing the Loop in Humanoid VLA: Persistent 3D Object Tokens for Verifiable Loco-Manipulation

arXiv:2607.18016v2 Announce Type: replace Abstract: Vision-language-action policies are a promising foundation for general robot control, but long-horizon humanoid loco-manipulation requires the robot

applicationsarxiv-cs-ro

Co-planning of Flight Corridors and Communication Infrastructure for Urban Drone Logistics Networks

arXiv:2607.23989v1 Announce Type: new Abstract: Reliable wireless connectivity is essential for urban air mobility (UAM) networks in dense urban environments. It is therefore imperative to carefully p

applicationsarxiv-cs-ro

Continual Knowledge Consolidation LORA for Domain Incremental Learning

arXiv:2510.16077v2 Announce Type: replace-cross Abstract: Domain Incremental Learning (DIL) is a sub-branch of continual learning that aims to address the never-ending arrival of new domains without c

Covariance-Boosted Gaussian Processes for Spatiotemporal Irregularities

arXiv:2607.23018v1 Announce Type: cross Abstract: Nonstationary Gaussian process (GP) models are powerful tools for capturing input-dependent variability by adapting to observed data. However, with li

safetyarxiv-cs-lg

DAP-Pose: Deep Temporal Alignment and Physics-aware Cross-modal Sensor Fusion for Robust Pose Estimation

model-releasesarxiv-cs-cv

arXiv:2607.23755v1 Announce Type: new Abstract: Robust and accurate pose estimation with multi-modal sensors is fundamental for autonomous vehicles and mobile robotic systems in complex environments.

DDVT: Dynamic Dual-level Vision Transformer Fusion Network for Answer Grounding in Visual Question Answering

arXiv:2607.23921v1 Announce Type: new Abstract: Answer grounding in visual question answering aims to locate the region from a given natural language question associated with the visual content of an

Decentralized Granular Access Control for Agentic AI Systems in Critical Infrastructure

arXiv:2607.22611v1 Announce Type: new Abstract: The deployment of autonomous AI agents in production infrastructure introduces fundamental security challenges that traditional role-based access contro

Agents

DeepFaith: Evidence-Grounded LLMs for Faithful Incident Reporting in Multi-Stage APT Defense

arXiv:2607.24348v1 Announce Type: cross Abstract: Advanced Persistent Threats (APTs) are difficult to detect and interpret due to their multi-stage and stealthy nature. While recent autonomous defense

agentsarxiv-cs-ai

Local Ai

Development of Vision-Language Model-based GNSS Spoofing Detection for Autonomous Vehicle Navigation

arXiv:2607.23962v1 Announce Type: new Abstract: Autonomous vehicles (AVs) depend on Global Navigation Satellite Systems (GNSS) for localization and navigation, making them vulnerable to spoofing attac

local-aiarxiv-cs-cv

Diffusion-Guided Search via Exponential Tilting (DiffTilt): An Application to Falsification of Safety-Critical Systems

arXiv:2607.23134v1 Announce Type: new Abstract: Discovering rare safety-critical failures in autonomous and cyber-physical systems is a fundamental challenge in verification and validation. Existing f

Discovering cryptographic weaknesses with Claude

model-releasessimon-willison

Discovering cryptographic weaknesses with Claude The best part of this article (here's the repo) about how Anthropic researchers used Claude Mythos to find mathematical flaws in both HAWK and a weaker

Tutorials

Do Coverage and Mutation Scores of LLM-Generated Test Suites Correlate with Their Effectiveness? (Replicability Study)

arXiv:2607.22880v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have driven growing interest in using LLMs to automate test generation. Prior work commonly evaluates

tutorialsarxiv-cs-ai

Do Diagrams Help Large Language Models Reason? Evidence from Syllogistic Reasoning

arXiv:2607.23513v1 Announce Type: cross Abstract: Diagrams are widely used to support logical reasoning, and prior studies suggest that representations such as Euler diagrams can improve human reasoni

Do Visual Features Improve Other-Initiated Repair Detection? A Dyadic Multimodal Approach

arXiv:2607.23845v1 Announce Type: new Abstract: Other-initiated Self-repair, or in short Other-initiated Repair (OIR), is an essential mechanism in conversational interaction, whereby a recipient sign

DynaCalKV: Key-Value Cache Compression via Head Grouping and Adaptive Rank Allocation

arXiv:2607.24331v1 Announce Type: new Abstract: As the inference phase of Large Language Models (LLMs) requires handling long context windows, the Key-Value (KV) cache initially appears to address thi

Efficiency Matters in Autonomous Research

arXiv:2607.24647v1 Announce Type: new Abstract: AI-driven autonomous research (AR) systems are becoming increasingly effective across a broad range of tasks. Their performance, however, is still evalu

safetyarxiv-cs-ai

Hardware

Energy Constrained Hierarchical Underwater Monitoring via Local Multi-Agent RAG

arXiv:2607.24313v1 Announce Type: cross Abstract: Marine life monitoring is limited by strict energy constraints, poor underwater connectivity, and the high cost of transmitting raw multimodal data fr

hardwarearxiv-cs-cv

Evaluating and Mitigating the Misguidance Effect of Buggy Code in LLM-Generated Unit Tests

arXiv:2607.22883v1 Announce Type: cross Abstract: While Large Language Models (LLMs) show great promise for automating unit test generation, recent studies suggest that the quality of generated tests

Explainable Reinforcement Learning via Physics-Aware Policy Distillation

arXiv:2607.24672v1 Announce Type: new Abstract: In safety-critical sectors such as robotics and automotive engineering, the deployment of Deep Reinforcement Learning (DRL) is often hindered by the bla