Search: “papers”

Using Non-Lipschitz Signum-based Functions for Distributed Optimization and Machine Learning: Trade-off Between Con-vergence Rate and Optimality Gap

arXiv:2608.01220v1 Announce Type: cross Abstract: In recent years, the prevalence of large-scale data-sets and the demand for sophisti-cated learning models have necessitated the development of effici

4 Aug 2026

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Agents

When Prompts Control Robots: Prompt Injection Attacks in Multi-Agent Robotic Systems

DGX agent

arXiv:2608.00747v1 Announce Type: new Abstract: Large language models are increasingly integrated into autonomous robotic systems for task planning and control, but this integration exposes them to pr

agentsarxiv-cs-ro

4 Aug 2026

A Machine Learning Surrogate for Component Criticality Ranking in Interdependent Power-Communication Networks

arXiv:2607.08918v2 Announce Type: replace Abstract: Cyber-physical power systems are vulnerable to cascading failures caused by interdependencies between power and communication infrastructures. Becau

A Model-Driven Approach for Developing Families of Reinforcement Learning Environments

arXiv:2606.20324v2 Announce Type: replace-cross Abstract: Virtual training environments are software-intensive systems in which reinforcement learning (RL) agents learn, adapt, and demonstrate meaning

local-aiarxiv-cs-lg

AgentHPOBench: A Benchmark For Evaluating LLM Agents as Sequential Hyperparameter Optimizers

arXiv:2607.29626v1 Announce Type: new Abstract: As LLMs evolve from code completion systems into autonomous scientific agents, evaluating their ability to conduct experiments has become increasingly i

An Ontology-Guided, Deduplication-Aware Extraction Layer for Knowledge Graph Construction from Heterogeneous Documents

arXiv:2607.28662v1 Announce Type: new Abstract: Large language models extract entities and relationships from unstructured documents fluently but inconsistently: type vocabularies fracture across docu

local-aiarxiv-cs-ai

Analysing User Reviews to Identify User Concerns Around Permissions in AI Apps

arXiv:2607.29343v1 Announce Type: new Abstract: Artificial intelligence is increasingly embedded in everyday software, making its integration into mobile apps inevitable. However, AI mobile app develo

Assessing the Generalization of Graph Neural Networks for Fault Location Across Increasing Distributed Energy Resource Penetration Levels

arXiv:2607.29293v1 Announce Type: new Abstract: Accurate fault location is critical for distribution network reliability. However, increasing distributed energy resource (DER) penetration complicates

Beyond Retrieval: Analytic Memory for Multimodal Agents

arXiv:2607.29440v1 Announce Type: new Abstract: Long-term multimodal memory must support not only retrieving relevant information but also computing over observations accumulated across interactions.

BWM: A Low-Cost High-Fidelity World Simulator for Robot Learning

model-releasesarxiv-cs-cv

arXiv:2607.29302v1 Announce Type: cross Abstract: Reliable robot learning requires a world simulator that can predict action consequences before execution on physical hardware, including risky and fai

Can Large Language Models Derive New Knowledge? A Dynamic Benchmark for Biological Knowledge Discovery

arXiv:2603.03322v2 Announce Type: replace-cross Abstract: Recent advancements in Large Language Model (LLM) agents have demonstrated remarkable potential in automatic knowledge discovery. However, rig

Combining Large Language Models and Symbolic Reasoning for Multi-Robot Temporal Planning through Explainable Knowledge Bases

arXiv:2502.19135v2 Announce Type: replace Abstract: We present PLANTOR, a framework for generating and executing multi-robot task plans from natural-language task descriptions through LLM-assisted kno

Communication-Efficient Secure Aggregation in Decentralized Learning

arXiv:2405.07708v3 Announce Type: replace Abstract: Decentralized learning (DL) enables participants to collaboratively train models without a central server, yet it faces significant scalability chal

CorrelationFlow: A Training-Free Geometric Approach for LiDAR Scene Flow Estimation

arXiv:2607.29237v1 Announce Type: new Abstract: LiDAR scene flow estimation has settled into a monoculture: nearly all recent methods share the same feed-forward architecture and the same family of se

researcharxiv-cs-cv

DASH-OPD: Discrepancy-Aware Switching with Hysteresis for On-Policy Distillation

arXiv:2607.29078v1 Announce Type: new Abstract: On-policy distillation (OPD) trains student models on their own rollouts to reduce exposure bias. However, in multi-turn agent scenarios, early student

Development of FDD-ON: an Ontology for VAV HVAC System Fault Detection and Diagnostics

arXiv:2607.29657v1 Announce Type: new Abstract: Fault detection and diagnosis (FDD) technology is essential for improving HVAC system reliability, energy efficiency, and maintenance effectiveness. How

Diagnosing Compositional Generalization in Sequential Robot Tasks

arXiv:2607.29687v1 Announce Type: new Abstract: Sequential robot manipulation requires policies to execute novel combinations of familiar instruction components. However, collecting demonstrations for

researcharxiv-cs-ro

Safety

Distance-aware Soft Prompt Guidance for Multimodal Valence-Arousal Estimation

arXiv:2603.13415v2 Announce Type: replace Abstract: Valence-arousal (VA) estimation is crucial for capturing the nuanced nature of human emotions in naturalistic environments. While pre-trained vision

safetyarxiv-cs-cv

DragonCrawl: A Generative, Intent-Based Framework for Scalable Mobile End-to-End Testing

arXiv:2607.28750v1 Announce Type: cross Abstract: As mobile applications grow in complexity, traditional End-to-End (E2E) testing frameworks struggle with UI volatility, maintenance overhead, and cros

applicationsarxiv-cs-ai

Explore Beyond the Boundary Using Entropic Information

arXiv:2607.29419v1 Announce Type: cross Abstract: In reinforcement learning, exploration with sparse and delayed rewards presents a significant challenge due to the limited feedback available for guid

Exploring Block Anomaly Detection In HDFS Log Data Analysis

arXiv:2607.29383v1 Announce Type: new Abstract: In recent years, with the development of big data technology, increasingly more companies use HDFS for data processing and storage. As a result, the mai

FibVLA: An Efficient Temporal Vision-Language-Action Model with Fibonacci Sampling

arXiv:2607.29596v1 Announce Type: cross Abstract: Vision-language-action models (VLAs), which leverage the cognition of multimodal information to infer physical-world actions, provide a generalized so

applicationsarxiv-cs-cv

Safety

Fragility of Value under Imperfect Alignment

arXiv:2607.28881v1 Announce Type: new Abstract: As more responsibility is placed upon AI systems, it becomes increasingly important to guarantee that these systems are aligned with humanity. A common

safetyarxiv-cs-ai

From Inline Notes to Collected Commentaries: Toward Context-Preserving Organization of Exegetical Knowledge in Classical Chinese Texts

arXiv:2607.29044v1 Announce Type: new Abstract: Inline notes and collected commentaries are important forms of scholarly communication that evolved within the Confucian exegetical tradition, yet have

applicationsarxiv-cs-cl

GoldenRetriever: Non-Interactive Homomorphic Encrypted Retrieval for Privacy-Preserving RAG

arXiv:2607.29019v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances large language models by incorporating external knowledge, but existing pipelines typically operate on p

researcharxiv-cs-cl

Information Processing by Neuron Populations in the Central Nervous System: A Theory of the Mathematical Structure of Data and Operations

arXiv:2309.02332v3 Announce Type: replace-cross Abstract: In the mammalian central nervous system, neurons are organized into populations communicating by spike trains propagating along axonal bundles

LegoQ: Density-Matrix Representation Learning with Spectral-Spatial State Transitions for Hyperspectral Classification

arXiv:2607.28970v1 Announce Type: new Abstract: Hyperspectral image classification is complicated by mixed pixels, spectral ambiguity, class imbalance, and limited annotations. Most current classifier

researcharxiv-cs-cv

Leveraging Image Generators to Address Data Scarcity: The Gen4Regen Dataset for Forest Regeneration Mapping

arXiv:2605.05627v2 Announce Type: replace-cross Abstract: Sustainable forest management relies on precise species composition mapping, yet traditional ground surveys are labour-intensive and geographi

applicationsarxiv-cs-ai

Library Reachability in LSR-Synth: How Anti-Memorization Design Changes the Measurement of Symbolic Discovery

arXiv:2607.28684v1 Announce Type: new Abstract: Existing benchmarks for scientific equation discovery are largely composed of well-known equations available in the public domain, making it difficult t

Lightweight Neural Networks for Affordance Segmentation: Enhancement of the Decoder Module

arXiv:2607.29473v1 Announce Type: new Abstract: The deployment of deep neural networks for visual affordance segmentation on wearable robots poses may prove critical, due to some conflicting aspects o

applicationsarxiv-cs-cv

Linear Proposal Operators and Stochastic Search Geometry in SOMA and Differential Evolution

arXiv:2607.29228v1 Announce Type: cross Abstract: Swarm and evolutionary algorithms are usually analyzed as complete procedural systems in which nonlinear selection, replacement, and adaptation obscur

Metaphor-Induced Algorithmic Steering: Cross-Domain Procedural Transfer in LLM Code Generation

arXiv:2607.28683v1 Announce Type: cross Abstract: Large language models benefit from elements in natural language, such as metaphors and analogies in training data and inference input to achieve gener

MirrorCraft: Paired Evaluation under Hidden Rule Changes in Minecraft

arXiv:2607.29218v1 Announce Type: new Abstract: With the prosperity of the large language models (LLMs), it has become an interesting topic: how do LLM-based agents work in Minecraft? Unfortunately, m

Multi-Agent Planning with Spatio-Temporal and Topological Constraints using STL-GO

arXiv:2607.28679v1 Announce Type: new Abstract: Multi-agent planning problems arise in a variety of engineering applications, such as multi-robot wildfire fighting and unmanned aerial inspection in fa

Multimodal Reinforcement Learning with Adaptive Verifier for AI Agents

arXiv:2512.03438v3 Announce Type: replace Abstract: Agentic reasoning models trained with multimodal reinforcement learning (MMRL) have become increasingly capable, yet they are almost universally opt

local-aiarxiv-cs-ai

On the Expressive Power of Sparse Geometric MPNNs

arXiv:2407.02025v5 Announce Type: replace-cross Abstract: Motivated by applications in chemistry and other sciences, we study the expressive power of message-passing neural networks for geometric grap

OnlineCache: Learning Dynamic Caching Policies with Error Correction for Efficient Diffusion Inference

arXiv:2607.29398v1 Announce Type: new Abstract: Diffusion models have revolutionized generative tasks but incur high latency due to iterative denoising. While cache-based strategies accelerate inferen

local-aiarxiv-cs-lg

Open-Source LLM-Driven Formal Verification: A Multi-Agent Pipeline for RTL Repair

arXiv:2607.28877v1 Announce Type: cross Abstract: Verification consumes the majority of modern chip design effort, yet the formal verification tools that provide mathematical guarantees of correctness

OpenClaw and Ollama in Agentic AI: Toward Fully Autonomous and Scalable AI Agent Systems

arXiv:2607.28629v1 Announce Type: new Abstract: The rapid transition from reactive large language models (LLMs) to persistent, action-capable systems has exposed critical gaps in the architectural und

Physics-Embedded Neural ODEs for Learning Antagonistic Pneumatic Artificial Muscle Dynamics

arXiv:2602.23670v2 Announce Type: replace Abstract: Pneumatic artificial muscles (PAMs) enable compliant actuation for soft wearable, assistive, and interactive robots. When arranged antagonistically,

researcharxiv-cs-ro

Progressive Decision-Making for Localizing Open-Ended AI-Generated Image Forgeries

arXiv:2607.29156v1 Announce Type: new Abstract: AI-generated image forgeries are becoming increasingly realistic and difficult to characterize with fixed manipulation patterns. As generative models co

local-aiarxiv-cs-cv

Pyramidal Width Can Increase Under Vertex Insertion

arXiv:2607.29555v1 Announce Type: new Abstract: Lacoste-Julien and Jaggi conjectured in 2015 that the pyramidal width of a polytope cannot increase when a vertex is added, provided that every old poin

Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation

arXiv:2607.28776v1 Announce Type: new Abstract: Generative machine learning is increasingly used for inorganic crystal structure generation. Most models and the corresponding evaluation approaches rel

SAM+D: Parameter-Efficient Dimensional Lifting of SAM-Family Models via Depth-Routed LoRA and Depth Shifting

model-releasesarxiv-cs-cv

arXiv:2607.29033v1 Announce Type: new Abstract: Existing methods for adapting 2D foundation models such as SAM to 3D volumes either process slices independently---ignoring inter-slice context---or req

SATViz: Real-Time Visualization of Clausal Proofs

arXiv:2209.05838v2 Announce Type: replace Abstract: Visual layouts of graphs representing SAT instances can highlight the community structure of SAT instances. The community structure of SAT instances

Agents

Scaling Scientific Discovery Environments for Turn-Level Agentic RL

arXiv:2607.28990v1 Announce Type: new Abstract: Large language model agents have shown promising capabilities in data-driven scientific discovery tasks, where an agent interacts with an execution envi

agentsarxiv-cs-ai

Seeing Differently: Modeling Interpretive Perspectives in Computational Creativity using a Four-World Framework

arXiv:2607.28644v1 Announce Type: cross Abstract: Creativity in computational systems is often evaluated as an objective property of artifacts, with existing Computational Creativity (CC) frameworks a

SeekBrain: An Autonomous Multi-Agent System for Accelerating Neuroscience Discovery

arXiv:2607.29347v1 Announce Type: cross Abstract: Modern neuroscience relies on integrating multi-scale, multimodal datasets to uncover the neural principles underlying intelligence. However, analytic