Search: “papers”

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

researcharxiv-cs-cv

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Decentralized Granular Access Control for Agentic AI Systems in Critical Infrastructure

DGX agent

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

model-releasesarxiv-cs-ai

28 Jul 2026

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

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

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

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

Extending Desbordante with Probabilistic Functional Dependency Discovery Support

arXiv:2607.23636v1 Announce Type: cross Abstract: Data profiling aims to extract complex patterns from data for further analysis and use that data in domains such as data cleaning, data deduplication,

tutorialsarxiv-cs-ai

False Prophets: On the Security of World Models in Agentic Systems

arXiv:2607.23147v1 Announce Type: cross Abstract: Large language models now power autonomous agents capable of complex, multi-step tasks in different environments. Accurate and reliable execution of t

Fast Cross-Scenario Adaptation of CSI Models via Channel Conditional Parameter Generation

arXiv:2607.22637v1 Announce Type: new Abstract: Deep learning has shown strong potential for massive multiple-input multiple-output (Massive MIMO) physical-layer tasks, including channel state informa

Finite-Time Analysis of the Natural Policy Gradient in Finite-Horizon Markov Decision Processes

arXiv:2607.22982v1 Announce Type: new Abstract: Natural Policy Gradient (NPG) is a well-established Reinforcement Learning algorithm that underlies widely used methods such as Trust Region Policy Opti

safetyarxiv-cs-lg

FMOPF: Latent Flow Matching with Constraint-Aware Interaction Priors for AC Optimal Power Flow

arXiv:2607.22788v1 Announce Type: cross Abstract: AC optimal power flow determines the minimum-cost generation dispatch under nonlinear power balance constraints and is solved thousands of times daily

Formalizing Flag Algebras in Lean

arXiv:2607.23500v1 Announce Type: cross Abstract: Razborov's flag algebra method is a powerful tool for proving asymptotic inequalities in extremal graph theory, often reducing the task to finding a f

From Camera-Based Sensing to Reasoning: A Comprehensive Review Toward Proactive Vulnerable Road User Safety

arXiv:2510.03314v2 Announce Type: replace-cross Abstract: Ensuring the safety of vulnerable road users (VRUs), such as pedestrians and cyclists, remains a critical challenge, as conventional infrastru

FutureRTC: Real-Time Robot Execution with Anticipatory-Conditioned Action Chunking

arXiv:2607.24008v1 Announce Type: new Abstract: Real-time deployment of Vision-Language-Action (VLA) policies necessitates asynchronous execution, wherein subsequent action chunks are computed concurr

safetyarxiv-cs-ro

GaitFace: A Multimodal Dataset for Long-Range Person Identification

model-releasesarxiv-cs-cv

arXiv:2607.23542v1 Announce Type: new Abstract: Efficient border control is becoming a significant global challenge, mainly due to severe congestion and extended passenger waiting times. To mitigate t

Generalization bounds and sample complexity for remaining useful life prediction from complete degradation trajectories

arXiv:2607.23454v1 Announce Type: new Abstract: Data-driven remaining useful life (RUL) prediction requires complete degradation trajectories for training, yet such run-to-failure data are scarce and

safetyarxiv-cs-lg

Geometry Meets Semantics: Fractional Gradient Stabilization for Semantic-Driven Bounding Box Optimization in Visual Detection Tasks

arXiv:2607.23530v1 Announce Type: new Abstract: Bounding boxes are fundamental for object localization in visual detection tasks. Among them, oriented bounding boxes are widely used in visual detectio

tutorialsarxiv-cs-cv

GFLAN: Generative Functional Layouts

arXiv:2512.16275v2 Announce Type: replace-cross Abstract: Automated floor plan generation lies at the intersection of combinatorial search, geometric constraint satisfaction, and functional design req

GNN-based Multi-Agent Control of Traffic Shockwaves in Sparse Vehicular Ad-hoc Networks

arXiv:2607.23792v1 Announce Type: cross Abstract: Traffic shockwaves are stop-and-go waves that propagate upstream through the streams of vehicles and are one of the major causes of traffic congestion

agentsarxiv-cs-lg

Hallucination Rates in Language Generation

model-releasesarxiv-cs-cl

arXiv:2607.23361v1 Announce Type: cross Abstract: Language generation in the limit is an elegant model introduced by Kleinberg and Mullainathan [KM24] to formally study language generation by an algor

HELIOS: An LLM-Driven Autonomous Indirect Trajectory Optimization Agent

arXiv:2607.24051v1 Announce Type: cross Abstract: Low-thrust trajectory optimization is a core technology in deep-space mission design. Indirect methods based on Pontryagin's Minimum Principle (PMP) o

HeraSys: Collaborative Serving of Multiple LLM Workflows via Fine-Grained End-to-End Optimization

arXiv:2607.22578v1 Announce Type: new Abstract: The proliferation of Large Language Models (LLMs) has shifted serving systems from processing isolated requests to orchestrating high-concurrency, multi

Hiding in Plain Sight: An Effective Physical Adversarial Patch Attack against Visual-Infrared Fused Face Detection

arXiv:2607.23292v1 Announce Type: cross Abstract: Deep learning-based visual-infrared fused face detection models are increasingly deployed across a wide range of applications, yet they remain suscept

tutorialsarxiv-cs-cv

Hierarchical Reinforcement Learning with Optimal Level Synchronization Based on Flow-Based Deep Generative Model

arXiv:2107.08183v2 Announce Type: replace Abstract: High-dimensional state and action spaces combined with sparse reward structures in reinforcement learning (RL) environments typically require advanc

How Do Practitioners Build SE Agents? Insights from a Mixed-Methods Study

arXiv:2607.10856v2 Announce Type: replace-cross Abstract: The rise of Software Engineering (SE) agents, i.e., LLM-based agents that can understand large codebases and carry out engineering tasks with

IKS-Instruct: A 24,000-Example Multilingual Dataset for Teaching Language Models Indian Knowledge Systems

model-releasesarxiv-cs-cl

arXiv:2607.23322v1 Announce Type: new Abstract: Instruction tuning has become the standard method for adapting large language models to follow human intent, yet existing instruction datasets are domin

In-Context Learning as Implicit Policy Gradient

arXiv:2607.23153v1 Announce Type: cross Abstract: Recent work has shown that large language models (LLMs) can iteratively improve their outputs by incorporating generated samples and their correspondi

Intent-Governed Tool Authorization for AI Agents

arXiv:2606.22916v2 Announce Type: replace Abstract: AI agents increasingly act through external tools: they read private data, construct structured payloads, submit write requests, export records, and

Applications

Investigating the Visual Cues of CNNs for Vascular Segmentation: A Case Study in Microscopy and Fundus Imaging

arXiv:2607.23371v1 Announce Type: cross Abstract: Vascular segmentation is a standard procedure for clinical diagnosis, yet the specific visual features determining model decisions remain poorly under

applicationsarxiv-cs-cv

JPEG AIC2026: A large-scale dataset for fine-grained assessment of image coding

model-releasesarxiv-cs-cv

arXiv:2607.22783v1 Announce Type: cross Abstract: Recent advances in conventional and learning-based image coding have increased the demand for benchmark datasets that support fine-grained assessment

Hardware

Kalypso: Relational LLM Serving

arXiv:2607.23815v1 Announce Type: cross Abstract: Large language models are increasingly used as semantic operators for filtering, extracting, ranking, joining, and transforming unstructured data. Exi

hardwarearxiv-cs-ai

Key-Interval A*: Accelerating Grid Pathfinding via Structural Abstraction

arXiv:2607.23393v1 Announce Type: new Abstract: Existing exact methods for 4-connected grid pathfinding reduce online search, but often either retain fine-grained search states or require substantial

Local Ai

Keyword Matters: Unveiling the Energy Sensitivity of On-Device LLM Prompting

arXiv:2607.22568v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed on mobile and embedded devices to improve privacy and reduce network latency. Yet on-device infer

local-aiarxiv-cs-ai

KG2Code: Bridging Knowledge Graphs and Large Language Models via Executable Code for Question Answering

arXiv:2607.22652v1 Announce Type: new Abstract: Recent research has explored the integration of knowledge graphs (KGs) with large language models (LLMs) to enhance their performance on downstream know

LanteRn: Latent Visual Structured Reasoning

arXiv:2603.25629v2 Announce Type: replace Abstract: While language reasoning models excel in many tasks, visual reasoning remains challenging for current large multimodal models (LMMs). As a result, m

researcharxiv-cs-cv

Layering Virtual Try-On

model-releasesarxiv-cs-cv

arXiv:2607.22924v1 Announce Type: new Abstract: In the real world, fashion is about layering: adding a jacket over a shirt, or a sequence of adding and removing layers, rather than just a single-layer

LeapBot-WA: World-Anchor Action Models via Predictive Latent Alignments

arXiv:2607.23969v1 Announce Type: new Abstract: World Action Models (WAMs) have emerged as a powerful paradigm for embodied intelligence, yet the prevailing reliance on pixel-level video generation cr

safetyarxiv-cs-ro

Learning Asymptotics with Convergence-Rate Guarantees using Linear Least Squares

arXiv:2607.23287v1 Announce Type: cross Abstract: We introduce a new research area that is called Asymptotics Learning Theory (ALT) and combines optimization with asymptotic analysis. In particular, A

researcharxiv-cs-lg

Applications

Let Me Look at You: Advanced Facial Expression Modeling for Conversational Speech Synthesis

arXiv:2607.24430v1 Announce Type: cross Abstract: Conversational Speech Synthesis is a fundamental component of human-computer interaction, aiming to generate contextually appropriate, expressive, and

applicationsarxiv-cs-cl

LLM-Assisted Ontology Engineering and Construction of a French Legal Knowledge Graph

arXiv:2607.24551v1 Announce Type: new Abstract: Maintenance regulations are complex legal texts that are difficult to exploit when addressing a specific case and challenging to integrate into operatio

Looking for Affect in Spontaneous Finnish Speech through Linguistic Interpretability

model-releasesarxiv-cs-cl

arXiv:2607.24155v1 Announce Type: new Abstract: Existing research on affect in speech has shown how acoustic surface characteristics and content-related linguistic aspects of speech both relate to per