Every paper checked — nothing hidden

All papers

Every paper checked in the week of 12–18 Oct 2026 · AI safety and reliability in deployment — nothing is hidden. Brief papers first.

All3,579 In brief3 More (on-topic)755 Not relevant2,801 Not assessed3 Older63 Could not confirm4 Blogs with no paper8 All blogs8

Paper	Topic	Relevance
Simplifying and Improving On-Policy Distillation for Few-Step Diffusion Proposes Simplified Matching Distillation, a regression-based on-policy method that enables four-step generation for diffusion models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on generation efficiency, not AI safety, jailbreaks, or deployment guardrails.
Beyond the Encoder: Object-Centric Representations Emerging from Segmentation Foundation Models This paper evaluates whether object pointers from the Segment Anything Model can transfer to downstream clinical tumor prediction tasks. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Studies medical downstream transfer, not safety guardrails or reliability.
Unbalanced W-Flow: Unbalanced Wasserstein Drifting under Finite-Batch Marginal Fluctuations The paper proposes an unbalanced optimal transport method to reduce minibatch fluctuations in teacher-free one-step generative models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on mathematical divergence optimization, not AI safety guardrails.
MajorTOM:Elliot Pretrain, A Multi-Sensor, Multi-Temporal Pretraining Dataset for Earth Observation This paper introduces a multi-sensor, multi-temporal satellite imagery dataset designed for pretraining Earth observation foundation models. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on remote sensing pretraining data, not safety guardrails.
Grid or Nodes? Probing Object Memory in World Models Under Partial Observability The paper compares spatial feature grids and tracked node coordinates for maintaining object memory under partial robot observability. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Studies robot memory representations, not safety guardrails or reliability.
Texture Interpolation as Texton Matching This paper studies texture interpolation using appearance-aware texton matching instead of standard positional coordinate blending. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Addresses graphic texture interpolation, not safety or deployment reliability.
Registration is a Representation Problem: Solving Whole-Body PET/CT Registration This paper presents an anatomical representation approach driving iterative solvers for longitudinal whole-body PET and CT image registration. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Addresses medical image alignment algorithms, not AI safety or jailbreak prevention.
Scaling Online Optimal Transport Minibatches for Flow Matching This paper develops an online entropic optimal transport approximation to scale minibatch coupling for stable flow matching. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Deals with optimal transport training stability, not deployment safety or guardrails.
Cepheid: Decoupling Scale from Structure for Cross-Family Motion Completion This paper proposes a dimensionless prior to complete dense mesh motion from sparse observations across different geometry families. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Addresses geometric motion completion, not safety or deployment reliability guardrails.
TrustPaper for forged PDF with Issuer Fingerprints This paper presents an issuer-aware forensic method that uses learned reference fingerprints to detect unauthorized alterations in PDF documents. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on PDF metadata forensics for certificates, not AI system safety.
ARMOR: Adversary Cost Amplification via a Schema-Preserving Password-Hardening Retrofit for Resource-Constrained Systems This paper introduces a verifier-side transform to harden password databases against offline cracking in resource-constrained systems. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Covers IoT password hashing defenses, not AI or LLM safety.
DS and AMDS Symbol-Pair Codes from Three Families of Simple Root Cyclic Codes The paper constructs three families of cyclic error-correcting codes and calculates their symbol-pair distance metrics. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on mathematical error-correcting codes, not AI safety or reliability.
Declared but Unaccountable: Measuring the Seller-Identity Gap in Advertising Supply-Chain Transparency The paper measures gaps between publisher ads.txt declarations and seller registries across millions of online advertising transparency records. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Covers digital advertising transparency records, not AI safety or deployment reliability.
(Implicitly) Characterizing Probabilistic Polynomial Time as Used in Cryptography The paper formalizes probabilistic polynomial-time cryptographic computation and adversary reductions using an implicit lambda calculus framework. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on theoretical cryptographic complexity, not AI safety or deployment.
StateSync-GKR: Design and Evaluation of a Reusable Sparse GKR Engine The paper evaluates a reusable Rust-based cryptographic proof engine designed for efficient state transitions and parallel execution. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Zero-knowledge proof cryptographic engine, unrelated to AI deployment safety.
On the Effectiveness of NetFlow-Based Deanonymization of Tor Onion Services (Extended Version) The paper demonstrates active traffic analysis attacks that deanonymize Tor onion services using coarse NetFlow packet statistics. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Studies Tor network traffic deanonymization, not AI safety.
Asymptotics of Random-Lattice Enumeration: Beyond HKZ via Dense Sublattices The paper analyzes the asymptotic tree sizes of random lattice enumeration algorithms to establish bounds beyond quasi-HKZ bases. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Theoretical lattice cryptography math paper, not AI deployment safety.
Fetch Me If You Can: A Comprehensive Analysis of Fetch Metadata The paper evaluates the real-world deployment and effectiveness of Fetch Metadata security headers across the top one million websites. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Analyzes standard web browser HTTP security headers, not AI systems.
Riemannian Suppression of Cross-Session Identity Leakage in Motor-Imagery EEG The paper introduces a Riemannian transformation to suppress cross-session subject identity leakage in EEG brain-computer interfaces without training a privacy model. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Covers EEG brain-computer interface privacy, not AI deployment safety.
LLM-based Code Auditing by Inferring and Evaluating Developer Assumptions The paper presents a code auditing method that uses language models to infer developer beliefs and flag contradictions as potential vulnerabilities. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on static code analysis rather than deployed AI safety.
Penetrating the Reality Wall: Long-Range and Through-Wall AR/VR Privacy Eavesdropping via Wireless Power Side Channel The paper presents an attack reconstructing AR and VR user behaviors through non-intrusive wireless power side-channel eavesdropping. Peer-reviewed	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on physical wireless side-channel eavesdropping on AR/VR devices, not AI safety.
The Role of Generative Artificial Intelligence in Testing and Automation of Open RAN Systems: GNG-OTA Framework The paper proposes a framework combining generative AI and graph neural networks for automated testing in Open Radio Access Networks. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on Open RAN telecommunications testing, not AI deployment safety risks.
Forensic Text Recovery from Document Thumbnails Using Text-Aware U-Net The paper develops a text-aware U-Net guided by optical character recognition loss to restore readable text from degraded document thumbnails. Peer-reviewed	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on forensic document image restoration, not AI safety or reliability.
HDKEM: Authentication Allocation for Deniable Hybrid Key Exchange The paper formalizes authentication allocation in deniable hybrid key exchange and presents a concrete protocol combining ML-KEM-768 and X25519. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on cryptographic key exchange protocols, not AI deployment safety.
Resource-constrained Remote Attestation of Smart Meters Using Merkle Trees in a Trusted Execution Environment The paper introduces a remote attestation method for smart meters that uses Merkle trees inside a trusted execution environment. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on smart meter hardware attestation and TEEs, not AI safety.
Risk-aware Road-network Trajectory Synthesis under Local Differential Privacy The paper presents a framework for road-network trajectory synthesis under local differential privacy to protect user mobility patterns and transition choices. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on road-network trajectory privacy, not AI system deployment safety.
Revisiting Fast Tendermint: An Agreement Violation and Two Repairs The paper identifies an agreement violation in Fast Tendermint's published round-change rule and proposes two protocol repairs. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Addresses distributed consensus protocol correctness, not AI deployment safety.
Digital-Twin-Referenced Belief-Guided Q-Learning for Jammer Identification and Beam-Power Control in a mmWave Model The paper introduces a digital-twin-referenced belief-guided Q-learning method for jammer identification and beam-power control in millimeter-wave networks. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Deals with RF wireless communications and jammer mitigation, not AI system deployment safety.
Security and robustness analysis of encrypted communications for local home automation: ESPHome Native API and MQTT over TLS 1.3 The paper reviews security and performance trade-offs between MQTT over TLS 1.3 and the ESPHome Native API for local home automation. Peer-reviewed	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant IoT communication security review, not related to AI safety or reliability.
Think Locally Before Computing Jointly: Efficient Secure Multi-Party Computation via Maximizing Local Processing The paper optimizes garbled-circuit secure multi-party computation by restructuring Boolean circuits to maximize local, non-cryptographic evaluations. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Cryptographic multi-party computation optimization, not related to AI systems.
The Right to Be Forgotten under Correlation: Privacy-Utility Tradeoffs This paper derives the optimal tradeoff between privacy leakage and utility when redacting information from correlated datasets. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Information-theoretic privacy for data redaction, not AI system safety/reliability.
SEAL-DT: An End-to-End Security Engineering and Assurance Framework for Cross-Domain Digital Twins This paper introduces an end-to-end security engineering framework for specifying, simulating, and assuring cross-domain digital twins. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Framework for digital twin security engineering, not AI safety or reliability.
Can Rényi Accountants Beat Lossless Accountants for DP-SGD? This paper demonstrates that Renyi differential privacy accountants can provide tighter privacy bounds for DP-SGD than lossless accountants. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Theoretical DP-SGD privacy bounds, outside deployed AI safety and reliability.
Tight End-to-End Accounting for Differentially Private Synthetic Data This paper develops accounting techniques to maintain tight differential privacy guarantees across complex synthetic data generation pipelines. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on differential privacy mathematics for synthetic data, not deployed AI safety/reliability.
SSM-Attack: Learning Where to Perturb for Black-Box Face Privacy This paper proposes using state space models to guide black-box image perturbations that disrupt facial recognition systems. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on adversarial attacks against computer vision face recognition, not deployed AI safety/reliability.
VulnBump: A Benchmark for Fixing Vulnerable Dependencies in Real Projects While Keeping the Build and Tests Green This paper introduces a benchmark testing whether coding agents can upgrade vulnerable dependencies while preserving project builds and test suites. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Main contribution is an SE benchmark for automated code repair agents.
Fast Forgiving Base64 Decoding with SIMD Instructions This paper introduces a block-oriented SIMD algorithm to accelerate forgiving Base64 decoding while removing whitespace characters. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant SIMD algorithms for Base64 decoding, not related to AI safety.
Extending Layered Attestation into ARM Application Run-Times This paper presents a runtime anchor architecture extending hardware root-of-trust attestation into active application execution on ARM. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on ARM hardware attestation and secure runtimes, not AI.
Local Leakage Resilience of Shamir Secret Sharing: Below Half Threshold Rate This paper provides mathematical bounds proving Shamir secret sharing resilience against local leakage under a lower reconstruction threshold. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Theoretical cryptography on Shamir secret sharing, not AI safety.
Beyond Model Scaling: Rethinking Sequence Construction for Transformer-based Network Intrusion Detection This paper proposes session-coherent sequence temporalization to improve transformer-based network intrusion detection over fixed-window approaches. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on network intrusion detection sequences, not AI safety/reliability.
The Maximum Nonlinearity of 8-variable Balanced Boolean Functions is 116 This paper resolves a mathematical open problem by proving the maximum nonlinearity of 8-variable balanced Boolean functions is 116. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Pure Boolean function mathematics, unrelated to AI safety or reliability.
Privacy-Preserving GNN Inference on Financial Transaction Graphs via Homomorphic Encryption This paper proposes an edge-centric graph neural network inference framework using homomorphic encryption for collaborative multi-bank transaction analysis. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Addresses cryptographic privacy for financial graph networks, not AI safety or guardrails.
BALLAST: Physics-Aware Moving Target Defense for Industrial Control Systems Using a Digital Twin Safety Oracle This paper develops a moving target network defense that uses digital twins to avoid disrupting industrial control physical processes. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Addresses industrial control system moving target defense, not AI safety or LLM deployment.
HULK: An Efficient Algorithm for Enabling Fast Bulk Bitwise Operations on Homomorphically Encrypted Data This paper introduces an algorithm to speed up bulk bitwise operations on homomorphically encrypted data without increasing ciphertext size. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on homomorphic encryption algorithms, not AI safety or LLM deployment reliability.
Tanchun: Robust Flow-Based HTTP(S) DDoS Detection via Behavioral Attribute Guidance This paper presents a drift-aware system for detecting HTTP DDoS attacks by grouping decryption-free traffic into behavioral sequences. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Covers network-level DDoS traffic detection, not AI safety or deployment reliability.
Prompt-Segmentation Meets ROI Encryption: Fine-Grained Video Protection Based on Diffusion Isolation This paper presents a prompt-segmentation method to encrypt irregular video regions with less distortion in surrounding non-sensitive areas. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on video codec ROI encryption, not AI safety, alignment, or LLM guardrails.
X.js: A Live Benchmark for Node.js Taint-Style Vulnerabilities The paper presents X.js, a benchmark of real-world Node.js taint-style vulnerabilities paired with executable exploits and patches. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on web application taint vulnerabilities, not AI safety or deployment reliability.
Autonomous Cyber Operations Gym for Training and Evaluating AI Models for Defence The paper introduces a simulation gym for training and evaluating autonomous cyber defence models and network intrusion detectors. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Trains intrusion detection classifiers, not safety or reliability of LLM deployments.
ARACDE: Retrofitting Databases with ABAC using External Authorization Engines The paper presents ARCADE, an architecture decoupling relational database authorization logic into external attribute-based policy engines. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Addresses relational database access control, not AI safety or LLM deployment reliability.
Dynamic Attack Surfaces: A Queue of Branching Processes The paper models dynamic software attack surfaces and patching queues using branching processes under evolving attacker populations. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Models cybersecurity vulnerability patching dynamics, not AI deployment safety or guardrails.
$\mathsf{EFI}\Leftrightarrow\mathsf{1PRS}$ The paper proves an equivalence between EFI pairs and expanding single-copy pseudorandom state generators in quantum cryptography. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on theoretical quantum cryptography, not AI safety or deployment robustness.
AegisAsync: Symbolic Async-Event Simulation for Risks in Python Asynchronous Programs The paper introduces AegisAsync, a symbolic event simulation framework for detecting concurrency and cancellation bugs in asynchronous Python code. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on static analysis of Python async code, not AI safety or LLM deployment risks.
Fin_Agent at FinEval 2026: Task-Aware Methods for Multilingual Financial NLP The paper describes a system submission combining rules and language models for multilingual financial named-entity recognition and question answering. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Applies NLP models to financial tasks, not AI safety or deployment guardrails.
Does System One Transfer? Calibrated Typed-Decision Models, Label Budgets, and Translation for Indonesian Regional Languages The paper evaluates the cross-lingual transfer, calibration, and translation sensitivity of fast typed-decision models on regional Indonesian languages. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Deals with cost reduction and classification accuracy, not safety or guardrails.
OpenMobile-2: Building Versatile Mobile Agents with Scalable Environments and App-Native Tools The paper presents OpenMobile-2, combining open mobile environments, trajectory datasets, and hybrid GUI-tool actions for mobile agents. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on mobile agent capability and evaluation, not deployment safety or guardrails.
AutoEnvScaling: Automating the Data Flywheel with Terminal Agents The paper presents AutoEnvScaling, using terminal agents to automatically generate reinforcement learning environments from model rollouts. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Explores environment generation for RL training, not AI deployment safety or guardrails.
Simple Linear Corrections for Compression in Late Interaction The paper proposes a linear score correction method to recover retrieval quality in compressed late-interaction document representations. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Deals with retrieval scoring efficiency, not AI safety, hallucination, or alignment.
Modeling the Arrival Time of Information-Bearing Events in Natural Language The paper uses neural temporal point processes to model the timing of information-bearing events in human and model generated text. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Analyzes language generation patterns without addressing deployment safety.
ASSET: Adaptive Speech Segmentation via Reinforcement Learning The paper introduces ASSET, a reinforcement learning method that adaptively compresses speech encoder outputs into continuous audio tokens. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Focuses on audio token compression rather than safety risks.
Multimodal Co-Generation With Continuous Bitstream Diffusion The paper applies continuous bitstream diffusion to joint and conditional generation across multimodal data without learned tokenizers. Preprint	AI safety and reliability in deployment via arxiv · 15 Oct, 06:18	Not relevant Explores multimodal generation architectures without addressing safety.

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