Search: “papers”

Cross-Corpus Evaluation of Generalizable Vulnerability Detection in IoT Firmware

model-releasesarxiv-cs-lg

arXiv:2608.11492v1 Announce Type: cross Abstract: IoT firmware vulnerability detection remains challenging due to heterogeneous firmware ecosystems, resource-constrained platforms, and limitations in

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CTBench: Evaluating Troubleshooting Capabilities of AI Agents in Realistic Telecom Network Operations

DGX agent

arXiv:2608.12002v1 Announce Type: new Abstract: Agents are increasingly considered for automating network operations and maintenance, where engineers must diagnose network faults, optimize configurati

model-releasesarxiv-cs-ai

13 Aug 2026

Deep Learning Based Relative Transfer Matrix Estimation for Multiple Sources and Multiple Microphones

arXiv:2608.11627v1 Announce Type: cross Abstract: The Relative Transfer Matrix (ReTM), recently introduced as a generalization of the relative transfer function for multiple receivers and sources, sho

Detecting a Route Flip Is Easier Than Knowing Whether to Fix It: Causal Route-Mediated Damage in Quantized Mixture-of-Experts

arXiv:2608.11212v1 Announce Type: new Abstract: Top-k Mixture-of-Experts (MoE) routing is discontinuous, so a deployment-motivated numerical disturbance -- simulated 4-bit KV-cache quantization read b

local-aiarxiv-cs-ai

DexterSQL: Deep Schema Exploration and Rule-based Correction for Text-to-SQL Generation

arXiv:2608.11889v1 Announce Type: cross Abstract: Prompting-based (extit{i}.extit{e}., non-fine-tuning) Text-to-SQL methods, where underlying large language model parameters are not changed for the ta

Diagram-MMU: A Multi-Modal Benchmark for Scientific Diagrams

arXiv:2608.12262v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have been growing the capability for scientific writing and collaboration. For example, OpenAI Prism is a fre

Diffusion-Based Data-Driven Assortment Optimization

arXiv:2608.11419v1 Announce Type: new Abstract: Assortment optimization is a fundamental problem in revenue management, typically addressed using parametric choice models such as the multinomial logit

local-aiarxiv-cs-lg

Diffusion-Guided Cooperative Policy Learning for Target Tracking Based on Underwater Mobile Agent Networks

arXiv:2603.29426v2 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning (MARL) provides a promising solution for cooperative target tracking in networks of autonomous underwater v

safetyarxiv-cs-lg

Distribird: Literature-Informed Prior Distribution Design for Bayesian Model Calibration

arXiv:2608.11210v1 Announce Type: new Abstract: Bayesian calibration of process-based models requires a prior distribution for each model parameter. Despite decades of methodological work, researchers

Do LLMs Take Care of Their Own? Similarity Signals Can Induce Cooperation

arXiv:2608.12125v1 Announce Type: cross Abstract: As LLM-based agents with user-instructed goals are becoming widely deployed, they increasingly encounter each other in strategic interactions, and fac

Dynamic Governance of Multi-LLM Agent Systems for Collaborative Conversational Outcomes

arXiv:2608.11207v1 Announce Type: new Abstract: When two LLM agents with structurally opposed objectives interact across multiple turns, the absence of a shared goal function produces not competition

safetyarxiv-cs-ai

Dynamics Models for Offline Hyperparameter Selection in Real-World RL

arXiv:2608.11349v1 Announce Type: cross Abstract: A key obstacle to deploying reinforcement learning in real-world systems is hyperparameter selection, particularly when simulators are unavailable and

Energy-Aware Wind-Resilient Routing for Truck-Assisted Multi-UAV Delivery under Wind Uncertainty

arXiv:2608.11641v1 Announce Type: cross Abstract: Energy feasibility under wind uncertainty is a critical safety issue for low-altitude air-ground delivery. In truck-UAV systems, UAVs complete assigne

safetyarxiv-cs-ro

Epiplexity Guided Data Selection and Generation for Out-of-Distribution Generalization

arXiv:2608.11746v1 Announce Type: cross Abstract: Modern systems are increasingly expected to transfer across tasks not specified during training. What data facilitates generalization in these new, un

safetyarxiv-cs-cl

Ethics Practices in AI Development: An Empirical Study Across Roles and Regions

arXiv:2508.09219v3 Announce Type: replace-cross Abstract: Recent advances in AI applications have raised growing concerns about the need for ethical guidelines and regulations to mitigate the risks po

Every document extraction system has a perception blind spot. We mapped them. For ExtractBench, we tested 14 systems on documents that weren…

model-releasesjerry-liu--x

Every document extraction system has a perception blind spot. We mapped them. For ExtractBench, we tested 14 systems on documents that weren't born digital: 1950s regulatory filings, hand-filled tax f

Federated Learning for Distributed CNC Tool Wear Prediction

arXiv:2608.11281v1 Announce Type: cross Abstract: Tool wear prediction is an important task in CNC machining, where accurate monitoring of tool condition supports product quality and process reliabili

First-order friction models with bristle dynamics: lumped and distributed formulations

arXiv:2602.09429v3 Announce Type: replace-cross Abstract: Dynamic models, particularly rate-dependent models, have proven effective in capturing the key phenomenological features of frictional process

researcharxiv-cs-ro

From Safety Documentation to Safety Knowledge Support: An Evidence-Grounded LLM Framework for Medical Devices

arXiv:2608.12025v1 Announce Type: cross Abstract: Medical devices are becoming more software-intensive, connected, and AI-enabled. Their development requires risk-management evidence aligned with ISO

safetyarxiv-cs-ai

Generative Video Compression Based on Hierarchical Referencing

arXiv:2608.11618v1 Announce Type: new Abstract: Diffusion-based generative video compression has emerged as a promising paradigm to improve perceptual quality, where latent frames are required to be e

researcharxiv-cs-cv

Hierarchical Federated Transfer Learning in Digital Twin-Based Vehicular Networks

arXiv:2608.11532v1 Announce Type: cross Abstract: In recent research on the Digital Twin-based Vehicular Ad hoc Network(DT-VANET), Federated Learning (FL) has shown its ability to provide data privacy

High-dimensional Multi-objective Bayesian Optimization with Learned Variable Interactions

arXiv:2608.11713v1 Announce Type: cross Abstract: Multi-objective Bayesian optimization (MOBO) is effective in identifying the Pareto fronts for expensive black-box problems. However, most current MOB

local-aiarxiv-cs-ai

How Can Driving World Models Do Counterfactual Prediction?

model-releasesarxiv-cs-cv

arXiv:2608.11601v1 Announce Type: new Abstract: Driving world models are often interpreted as counterfactual simulators for observed driving episodes: given a factual driving log, they are asked what

HSTGFormer: Hyper Spatial-Temporal Graph Transformer for 3D Human Pose Estimation

arXiv:2608.12187v1 Announce Type: cross Abstract: Transformer-based methods have achieved strong performance in monocular 3D human pose estimation, but most existing approaches organise spatial and te

Inverse-dynamics observer design for a linear single-track vehicle model with distributed tire dynamics

arXiv:2603.07499v3 Announce Type: replace-cross Abstract: Accurate estimation of the vehicle's sideslip angle and tire forces is essential for enhancing safety and handling performances in unknown dri

safetyarxiv-cs-ro

IoT-Enabled Autonomous Maritime Navigation in Smart Ports: A Curriculum-Guided Shared Policy Learning Framework

arXiv:2608.11597v1 Announce Type: cross Abstract: As smart port infrastructures increasingly rely on autonomous maritime devices enabled by the Internet of Things (IoT), ensuring reliable onboard navi

safetyarxiv-cs-lg

Koopman Representation of Nonlinear Virtual Environments in Kinesthetic Haptic Systems

arXiv:2608.11461v1 Announce Type: new Abstract: Rendering haptic feedback with nonlinear virtual environments (VEs) is important in many applications that require highly accurate force feedback. This

researcharxiv-cs-ro

Latent variable models for simultaneous EOV identification and removal in population-based SHM

model-releasesarxiv-cs-lg

arXiv:2608.11995v1 Announce Type: cross Abstract: The robust treatment of environmental and operational variability (EOV) is an open challenge in population-based structural health monitoring (PBSHM).

Locomotion Variability and User Experience in Smart Wheelchair Human-Robot Interaction

arXiv:2608.11417v1 Announce Type: new Abstract: Human movement is inherently variable, with variability structured according to task relevance: movements are typically more consistent at task-critical

researcharxiv-cs-ro

Tutorials

Low-Interaction-Rank Learning: Unifying Multiplicative Dual-Encoder Heads

arXiv:2608.11661v1 Announce Type: cross Abstract: A multiplicative dual-encoder network computes a real-valued output for a pair of inputs as the inner product of their separate encodings. This archit

tutorialsarxiv-cs-ai

Machine Learning-Based Cyber Defense for Cloud Infrastructure: An Adaptive Deep Q-Network Architecture for Intelligent Intrusion Detection and Automated Threat Mitigation

arXiv:2608.12190v1 Announce Type: cross Abstract: With the increasing complexity of cyber assaults in cloud environments, adaptable security solutions are needed that can support real-time detection a

safetyarxiv-cs-ai

Market-Information-Aware Gated-LoRA of Foundation Models for Transferable Day-Ahead Electricity Price Forecasting

arXiv:2608.11359v1 Announce Type: new Abstract: Electricity price forecasting is crucial for market participants but remains difficult because prices are volatile, market-specific, and closely tied to

researcharxiv-cs-lg

MOON: Multi-Objective OrthoNormalized Updates for Multitask Learning

arXiv:2608.11749v1 Announce Type: cross Abstract: Multi-objective optimization (MOO) has demonstrated significant success in multi-task learning by mitigating task conflicts through gradient manipulat

OEIS Open: How many conjectures can language models turn into theorems?

arXiv:2608.11941v1 Announce Type: new Abstract: We construct OEIS Open, a benchmark based on 492 open mathematical conjectures from the OEIS, formalized in Lean by Tsoukalas et al. Whereas these conje

OrderMoE: An expert similarity driven distributed edge MoE inference

arXiv:2607.17154v2 Announce Type: replace-cross Abstract: Although mixture-of-experts, MoE, models have been increasingly adopted to scale large language models with moderate computation cost, it rema

local-aiarxiv-cs-lg

Proportional Analogies on Probability Distributions via Bayesian Updating

arXiv:2608.11724v1 Announce Type: new Abstract: Analogies are quaternary relations of the form 'A is to B as C is to D'. Among the various formalizations of analogical reasoning, proportional analogie

ProtoHGF-Net: Prototype HyperGraph Fusion with Intra-modal Calibration for RGBT Object Detection

arXiv:2608.11595v1 Announce Type: new Abstract: RGB-Thermal (RGBT) object detection enables robust perception in complex scenes by leveraging the complementary strengths of visible textures and therma

researcharxiv-cs-cv

Quantifying the Relationship Between Clinical Safety and Environmental Impact in Therapeutic LLMs

arXiv:2608.11830v1 Announce Type: cross Abstract: The deployment of large language models (LLMs) in mental health contexts raises questions about the relationship between clinical safety and environme

safetyarxiv-cs-cl

Reducing Symmetry Increase in Equivariant Neural Networks

arXiv:2608.12010v1 Announce Type: new Abstract: Equivariant Neural Networks (ENNs) have empowered numerous applications in scientific fields. Despite their remarkable capacity for representing geometr

applicationsarxiv-cs-lg

RevCRN: Reversible Analog Computation using Chemical Reaction Networks

arXiv:2608.11362v1 Announce Type: cross Abstract: The computability of real numbers and functions using Turing Machines has been a central area of theoretical computer science since the mid-20th centu

researcharxiv-cs-cl

Self-Harness: Harnesses That Improve Themselves

model-releasesarxiv-cs-cl

arXiv:2606.09498v2 Announce Type: replace Abstract: The performance of LLM-based agents is jointly shaped by their base models and the harnesses that mediate their interaction with the environment. Be

Soft-Attention Improves Skin Cancer Classification Performance

arXiv:2105.03358v4 Announce Type: replace-cross Abstract: In clinical applications, neural networks must focus on and highlight the most important parts of an input image. Soft-Attention mechanism ena

researcharxiv-cs-cv

Sparse and robust geometric twin support vector machine via asymmetric RoBoSS loss function

arXiv:2608.11567v1 Announce Type: new Abstract: In real-world scenarios, the training data usually contains redundant features, label noise and feature noise, which provide severe challenges for the e

applicationsarxiv-cs-lg

Structural Silence: When AI Infrastructure Fails Speakers of Underrepresented Languages

arXiv:2608.12278v1 Announce Type: cross Abstract: Artificial intelligence tools for education and language support are increasingly framed as scalable responses to access gaps in under-resourced commu

Structuring the Space of Perspectives

arXiv:2608.12113v1 Announce Type: new Abstract: The same event can be reported from different perspectives depending on the experiences, background, and beliefs of the writer or speaker. A variety of

researcharxiv-cs-cl

Agents

Top-down Traffic Scenario Generation via Joint Initial-Goal Diffusion and Trajectory Infilling

arXiv:2608.11407v1 Announce Type: new Abstract: Robust traffic simulators are crucial for developing and testing autonomous vehicles to reduce the costly, labor-intensive real-world data collection pr

agentsarxiv-cs-ro

Towards Model-based Run-time Cybersecurity: On Control-Flow Anomaly Detection, Attack Identification, and Hardware Monitoring

arXiv:2608.11802v1 Announce Type: cross Abstract: Methods to increase the resilience of systems to cyber-attacks become increasingly important. Control-flow monitoring provides a principled basis to e

Towards Truly Unsupervised Evaluation of Feature Selection

arXiv:2608.12057v1 Announce Type: new Abstract: Feature selection is one of the most important and fundamental tasks in data mining, tackled by a family of methods with an established set of evaluatio

researcharxiv-cs-lg