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Review Of Evangelism: Learning From The Past, Authored By Green, Jeffrey Stevenson Jun 2026

Review Of Evangelism: Learning From The Past, Authored By Green, Jeffrey Stevenson

Witness

No abstract provided.

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Multi-Modal Cross-Platform Recommendation System With Aggregated Social Context Signals, Anonymous Jun 2026

Multi-Modal Cross-Platform Recommendation System With Aggregated Social Context Signals, Anonymous

Defensive Publications Series

Systems and methods are described for cross-platform, social-context-aware product recommendation. Interaction signals associated with a user are aggregated across multiple applications and normalized into features used to populate an inspiration graph representing entities and relationships reflecting user interests and context. A conversational shopping mode receives multi-turn requests and constraints and may accept multi-modal inputs such as room, wardrobe, or invitation images. Candidate products are retrieved from one or more catalogs and ranked using features derived from the inspiration graph and, when provided, the multi-modal inputs. In some embodiments, a trend momentum score is computed from velocity and recency of style …

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Protocol Bridge Architecture For Chat-Directed Cloud Ai Agent Access To Local Application Interfaces With Knowledge Base Integration, Anonymous Jun 2026

Protocol Bridge Architecture For Chat-Directed Cloud Ai Agent Access To Local Application Interfaces With Knowledge Base Integration, Anonymous

Defensive Publications Series

A cloud-enabled, chat-controlled architecture provides remote AI agent access to a local desktop design application through a protocol bridge. A plugin running inside the desktop application connects to a locally executed bridge service using WebSocket and executes commands via an internal plugin API with deep read/write support, including complex assets such as images and fonts. A cloud-hosted agent receives natural-language instructions from a chat platform, retrieves context from an external knowledge base and optionally a brand asset pipeline, generates structured tool commands subject to design-system constraints, and sends the commands as HTTP requests to the local bridge. The bridge translates …

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Dual-Vocabulary Llm Recommendations, Anonymous Jun 2026

Dual-Vocabulary Llm Recommendations, Anonymous

Defensive Publications Series

A unified lifecycle system supports dual-vocabulary LLM-enhanced recommendations using natural language tokens and semantic identifier (SID) tokens. Cross-architecture migration preserves accumulated SID knowledge by learning an embedding projection that minimizes pairwise similarity distortion and enforces neighborhood contraction for K-nearest SID neighbors, followed by staged initialization, embedding warmup, continued pretraining with synthetic domain replay, and validation. Modality-aware distillation applies dual temperatures, using higher temperature for natural language and lower temperature for SIDs to avoid catastrophic SID substitutions, with long-tail SID importance weighting, SID embedding-alignment, and a closed-loop controller that adjusts temperatures and loss weights when SID quality degrades. Serving uses staleness-tiered …

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Automated Insights Generator, Anonymous Jun 2026

Automated Insights Generator, Anonymous

Defensive Publications Series

An automated insights generator coordinates multiple specialized AI agents to conduct autonomous, iterative exploratory analysis from a single prompt. A central orchestrator executes outside a large language model (LLM) and manages persistent state, tool invocation, and repeated looping by rotating LLM sessions to avoid context exhaustion. A topic discovery agent monitors leadership communications to populate and prioritize a backlog of unaddressed analysis topics. An exploratory analysis agent executes a codified multi-phase methodology using organizational data tools such as SQL engines, experimentation platforms, metric systems, and visualization services. Outputs are cross-checked by a data validation agent against approved dashboards and canonical …

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Dynamic Image Conversion, Anonymous Jun 2026

Dynamic Image Conversion, Anonymous

Defensive Publications Series

Systems and methods are described for converting still images into short video clips at scale. A computing system receives a still image, determines an image pattern using extracted features, and selects one or more motion context files that map the pattern to standardized minimal-motion templates. The system generates a plurality of frames by applying the selected template(s) and encodes a short video clip that begins and/or ends with a frame identical to the original still image. In some implementations, a purpose-built image-to-video conversion model generates or refines frames, optionally conditioned on motion context files and template outputs that may also …

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Standard Model Template, Anonymous Jun 2026

Standard Model Template, Anonymous

Defensive Publications Series

A template-driven framework supports development and deployment of large ecosystems of machine learning models. A representative subset of models is selected from a model fleet by clustering model descriptors across multiple ecosystem dimensions. In a template iteration phase, candidate techniques are evaluated on the representative subset and a multi-model optimization process identifies template-level hyperparameters that satisfy an aggregate performance criterion while constraining regressions. Qualified techniques and hyperparameters are encoded into a versioned modular standard model template having standardized interfaces for architecture and, in some embodiments, feature, data, and training/serving components. In a model iteration phase, many individual production models are …

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Dynamic K-Anonymity, Anonymous Jun 2026

Dynamic K-Anonymity, Anonymous

Defensive Publications Series

Techniques are disclosed for privacy enforcement in streaming data aggregation. Contextual signals for an aggregation breakdown are obtained, including signals such as breakdown cardinality, traffic volume, targeting specificity, data age, regulatory tier, and cross-breakdown overlap. A risk score in a bounded range is computed and mapped to a dynamic k-anonymity threshold between configured minimum and maximum values, optionally adjusted for composition risk based on how many breakdowns a user contributes to. An existing k-anonymity check uses the dynamic threshold to gate release. Separately or in a closed loop, probabilistic cardinality sketches are monitored over time to forecast whether cohorts will …

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Hypernetwork Cross-Attention, Anonymous Jun 2026

Hypernetwork Cross-Attention, Anonymous

Defensive Publications Series

Techniques are described for conditioning beam-search decoding on encoder outputs without constructing cross-attention matrices over encoder positions. An encoder output is compressed once into a fixed-size summary vector using learned query vectors. For each beam, a decoder query is mapped to a low-dimensional latent code by a code generator. A hypernetwork generates parameters for a per-beam primary network as a function of the latent code, including affine weight generation. The primary network is applied to the shared summary to produce a beam-specific output vector, with per-beam computation independent of encoder sequence length. A continuous latent code space supports interpolation, extrapolation, …

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Pareto Beam Search, Anonymous Jun 2026

Pareto Beam Search, Anonymous

Defensive Publications Series

Techniques are described for multi-objective beam search in generative retrieval systems that autoregressively generate semantic identifiers across multiple codebook steps. Each beam carries a vector of objective scores, such as relevance, diversity, freshness, and business value. At each decoding step, candidate beam extensions are evaluated and pruned by Pareto dominance using non-dominated sorting to form fronts. Beam selection proceeds by taking fronts in order until a beam budget is reached, and crowding distance is used to select among candidates within a front to promote spread across objective space. In some implementations, each beam also carries a preference vector used to …

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Composed Ot Beam Search, Anonymous Jun 2026

Composed Ot Beam Search, Anonymous

Defensive Publications Series

Multi-codebook generative retrieval produces semantic identifiers by autoregressively generating K codebook tokens. The disclosure describes globally coordinated decoding by formulating the K-step process as a sequentially composed optimal transport problem with K transport plans linked by marginal consistency constraints. A retrieval transport cost is defined per step from decoder conditional probabilities and may include a learned future value term and a diversity penalty. An entropically regularized objective is solved using composed Sinkhorn iterations that perform forward and backward scaling passes across steps to satisfy source, intermediate, and target marginals. A global beam computation budget is adaptively allocated across steps based …

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Automatic Discovery Of User Intent Categories In Conversion Rate Prediction Using Differentiable Discrete Routing, Anonymous Jun 2026

Automatic Discovery Of User Intent Categories In Conversion Rate Prediction Using Differentiable Discrete Routing, Anonymous

Defensive Publications Series

Systems and methods are described for automatically discovering user intent categories in conversion rate prediction using differentiable discrete routing. A routing network produces logits over K expert prediction heads based on interaction features such as click type, page type, and position. During training, a Gumbel-Softmax reparameterization generates differentiable approximations of discrete expert assignments, optionally with temperature annealing to transition from soft sharing to near-discrete specialization. A load balancing loss, such as a KL-divergence between an average routing distribution and a uniform distribution, discourages expert collapse. During inference, routing may collapse to a hard argmax such that exactly one expert head …

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Sram-Packed Multi-Leaky-Bucket Rate Limiter With Timer-Tick Scrubbing, Pipelined Read-Modify-Write Forwarding, And Csr Priority Escalation, Anonymous Jun 2026

Sram-Packed Multi-Leaky-Bucket Rate Limiter With Timer-Tick Scrubbing, Pipelined Read-Modify-Write Forwarding, And Csr Priority Escalation, Anonymous

Defensive Publications Series

A hardware leaky-bucket rate limiter stores multiple bucket entries per SRAM row and accesses the SRAM using a unified pipeline that selects per cycle exactly one of a posted traffic request, a timer-driven scrub operation, or a CSR access. Request metadata is pipelined for SRAM read latency and updates are performed using read-modify-write. A conflict detector with forwarding supplies a most-recent-value view when a row is accessed again before a prior update is observable, avoiding lost updates. Scrub is driven by a programmable timer tick and supports per-bucket refill rates using a scrub frequency counter; an error indication asserts when …

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Recoverable Multimedia Export With Pre-Export Validation And Element-Level Automated Remediation, Anonymous Jun 2026

Recoverable Multimedia Export With Pre-Export Validation And Element-Level Automated Remediation, Anonymous

Defensive Publications Series

Techniques are disclosed for recoverable multimedia export using pre-export validation and element-level automated remediation. A validation engine traverses a composition graph before an export pipeline begins and checks referenced elements such as media assets, audio tracks, fonts, effects, filters, LUTs, and external resources for existence, decodability or integrity, permissions, compatibility, dependencies, and license validity. A structured validation report identifies each problematic element with a failure type and severity and provides remediation options. A user interface presents the report prior to export, including per-issue detail and a fix-all control, and accepts user overrides. A remediation engine applies selected actions such as …

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Ensemble Model Divergence Analysis For Adversarial Prompt Detection In Generative Ai Systems, Anonymous Jun 2026

Ensemble Model Divergence Analysis For Adversarial Prompt Detection In Generative Ai Systems, Anonymous

Defensive Publications Series

Techniques are disclosed for detecting adversarial, obfuscated, or harmful prompts in generative AI platforms by using model disagreement as a risk signal. A user prompt is routed to an ensemble of language models selected for diversity in architecture, size, generation, and safety tuning, optionally including smaller canary models. Each model generates a response, and the responses are embedded into a shared semantic vector space. Pairwise divergence values, such as cosine distances between response embeddings, are computed and aggregated into a divergence score for the prompt, with optional per-model divergence diagnostics. The divergence score is compared to a calibrated threshold to …

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Simpson's Paradox Detection And Granularity-Adaptive Behavioral Curve Estimation For Recommendation Systems, Anonymous Jun 2026

Simpson's Paradox Detection And Granularity-Adaptive Behavioral Curve Estimation For Recommendation Systems, Anonymous

Defensive Publications Series

Systems and methods are described for exposure-response behavioral curve estimation in recommendation systems with detection of aggregation artifacts consistent with Simpson’s paradox. Interaction logs are used to fit a behavioral curve model at multiple granularities, including individual and aggregate levels, and to compute peak locations. A distortion factor and severity score quantify divergence between aggregate and individual peak parameters and can trigger a paradox determination. A per-user peaked-behavior classifier is null-calibrated by generating synthetic sequences from a fitted monotonic model to estimate a null false-positive rate and adjust decision thresholds. A granularity-adaptive selector chooses among individual, cohort, and aggregate models …

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Computational Vertical Binocular Disparity Calibration Method For Augmented Reality Displays With Perceptual Tolerance-Based Statistical Assessment, Anonymous Jun 2026

Computational Vertical Binocular Disparity Calibration Method For Augmented Reality Displays With Perceptual Tolerance-Based Statistical Assessment, Anonymous

Defensive Publications Series

Techniques are described for calibrating vertical binocular disparity (VBD) in optical see-through augmented reality displays using two independent measurements rather than direct perceptual display-to-background alignment. A background VBD (bg_vbd) for the see-through optical path and a display-to-display VBD (display_vbd) between left and right display channels are measured, and a correction offset is computed as offset = bg_vbd - display_vbd. The offset is applied to one or both display channels to reduce relative VBD between displayed content and background toward approximately zero. A statistical framework assesses calibration quality by propagating measurement uncertainties (e.g., s_offset = sqrt(s_bg^2 + s_display^2)), optionally including display …

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Active-Feedback User Simulation Agent For Bidirectional Content Retrieval In Recommendation Systems, Anonymous Jun 2026

Active-Feedback User Simulation Agent For Bidirectional Content Retrieval In Recommendation Systems, Anonymous

Defensive Publications Series

Techniques are described for bidirectional candidate generation in a recommendation pipeline using an active-feedback user simulation agent. An initial candidate set is retrieved using one or more retrieval paths. A user digital twin consumes a live session state, including an emotional-state embedding, and evaluates the candidates by predicting a session trajectory. When the predicted trajectory indicates low engagement, disengagement risk, or a coverage gap between predicted preference and available candidates, the agent generates a structured, machine-readable retrieval query (e.g., topic, content-type, social, negative, emotional, or mixing requests). A query handler executes the query to obtain additional candidates, forming an expanded …

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Encoding-Aware Collusion Detection And Intervention System For Autonomous Pricing Markets, Anonymous Jun 2026

Encoding-Aware Collusion Detection And Intervention System For Autonomous Pricing Markets, Anonymous

Defensive Publications Series

Systems and methods monitor autonomous pricing markets for tacit collusion using externally observable posted prices and market outcomes. Multiple indicators are computed, including a price elevation index with Newey-West HAC uncertainty, Granger causality using vector autoregression with heteroskedasticity-consistent errors, a constrained three-state hidden Markov model producing a collusive-state posterior probability, and conditional mutual information estimated by k-nearest neighbors and normalized against a permutation null. The indicators are combined into a composite collusion score. An encoding regime is inferred from observables including price dimensionality, correlation structure, and within-run dispersion, and regime-specific thresholds are applied for detection. The system may estimate latent …

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Temperature Selection For Knowledge Distillation In Mixed-Vocabulary Models, Anonymous Jun 2026

Temperature Selection For Knowledge Distillation In Mixed-Vocabulary Models, Anonymous

Defensive Publications Series

Plateau-aware temperature selection is described for knowledge distillation of mixed-vocabulary models that include natural-language tokens and structured identifiers (SIDs). Teacher logits for SIDs are obtained from a forward pass on calibration data and analyzed without training a student model. A cold-collapse temperature boundary is estimated as a minimum temperature at which perplexity of a temperature-scaled SID softmax exceeds a threshold, and a soft-collapse temperature boundary is estimated as a maximum temperature at which a discriminability measure based on probability ratios exceeds a threshold. A SID distillation temperature is selected from the plateau between the boundaries, including selecting a geometric mean …

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Multimodal Session Simulation With Sequential User State Evolution For Content Ranking, Anonymous Jun 2026

Multimodal Session Simulation With Sequential User State Evolution For Content Ranking, Anonymous

Defensive Publications Series

Techniques are described for multimodal simulation of a user browsing session through an ordered content feed. A feed is rendered into a visual representation, and recent engagement events are encoded into a live session state vector that includes an emotional state embedding inferred from behavior. A multimodal autoregressive model consumes the rendered feed and the session state to predict a trajectory across feed positions, including predicted interactions and predicted emotional-state shifts conditioned on prior positions. A planner and/or safety checker uses the predicted trajectory to select among candidate orderings or to block a slate and serve a fallback ordering when …

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Dual-Table Hardware Architecture For Frequency-Adaptive Memory Access Management In Accelerator Systems, Anonymous Jun 2026

Dual-Table Hardware Architecture For Frequency-Adaptive Memory Access Management In Accelerator Systems, Anonymous

Defensive Publications Series

A hardware trap positioned between processing elements and a memory router and/or last-level cache intercepts tagged embedding read requests. The trap includes a dual-table structure comprising a low-frequency table that tracks access frequency for addresses without storing full embedding data and a high-frequency table that stores embedding data for addresses promoted as high-frequency. When an address exceeds a configurable promotion threshold, the trap initiates a fill request and promotes the address for local servicing. During the fill window, a configurable blocking threshold stalls additional requests for the promoted address to limit backpressure, and stalled requests are serviced upon data arrival. …

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Language Model System For Account Compromise Detection Via Multi-Signal Business Graph Reasoning, Anonymous Jun 2026

Language Model System For Account Compromise Detection Via Multi-Signal Business Graph Reasoning, Anonymous

Defensive Publications Series

Systems and methods are described for pre-monetization detection of business account compromise using large language model reasoning over business-graph evidence. A pipeline selects candidate accounts based on novel behavior such as advertising on previously unseen pages or domains. For each candidate, signals are aggregated across categories including account structural metadata, creator indicators, candidate ad content attributes, historical baseline ad attributes, administrative access modification records, and business activity events. Heterogeneous signals are transformed into a structured natural-language representation organized by category and combined with embedded domain heuristics specifying compromise indicators, non-compromise indicators, and exclusion criteria. A large language model processes the …

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Neural Network-Based Feature Imputation For Privacy-Constrained Environments Using Cross-Population Training, Anonymous Jun 2026

Neural Network-Based Feature Imputation For Privacy-Constrained Environments Using Cross-Population Training, Anonymous

Defensive Publications Series

Techniques are described for privacy-preserving feature imputation in environments where a limited-personalization policy deterministically withholds a subset of user features. Complete feature vectors from consenting users are collected and normalized using automated statistical classification of features. A deterministic binary mask derived from a privacy policy configuration is applied during training to simulate restricted-feature conditions. A denoising autoencoder (or other encoder-decoder model) is trained by reconstructing full vectors from masked inputs while computing reconstruction loss only on masked positions, optionally adding noise to visible features. During inference, visible features for a privacy-restricted user are normalized, passed through the trained model to …

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Multi-Root Trust Chain Management For Secure Boot Firmware Development And Signing Infrastructure, Anonymous Jun 2026

Multi-Root Trust Chain Management For Secure Boot Firmware Development And Signing Infrastructure, Anonymous

Defensive Publications Series

Techniques are described for managing multiple secure-boot trust chains for firmware development and release on devices that support multiple hardware roots of trust. A provisioning pipeline generates a device configuration image that activates a selected non-production root index and is cryptographically bound to a device identifier such as an SoC serial number. The configuration image is signed using a production root to bootstrap trust, and activation may be policy-gated and generated in an event-driven manner with storage for fast retrieval. A signing service, backed by hardware security modules, signs firmware artifacts via authenticated service-to-service RPC and supports build-time selection between …

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Multi-Resolution Image Segmentation With Selective Region-Based Detail Refinement, Anonymous Jun 2026

Multi-Resolution Image Segmentation With Selective Region-Based Detail Refinement, Anonymous

Defensive Publications Series

Techniques are disclosed for multi-stage image segmentation with selective high-resolution region refinement. A coarse segmentation neural network generates a full-frame mask while operating with a reduced internal resolution to meet real-time constraints. From coarse outputs, a region of interest (ROI), such as a head/hair region, is dynamically determined per image or per video frame. The ROI is cropped from a higher-resolution version of the original input image, optionally along with aligned coarse segmentation data, and provided to a second refinement neural network that produces refined alpha or mask values and confidence. A fusion stage combines refined ROI output with the …

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Multi-Modal Social Context Detection And Automated Environment Behavior Adaptation, Anonymous Jun 2026

Multi-Modal Social Context Detection And Automated Environment Behavior Adaptation, Anonymous

Defensive Publications Series

A smart environment controller receives multi-modal occupancy signals including combinations of Wi-Fi sensing, Bluetooth proximity, acoustic analysis, and entry/lock events. Sensor fusion produces occupant hypotheses indicating identities, classes, and/or counts of occupants. A social context classifier determines a current social context reflecting social composition, such as solo, with-partner, hosting, kids-home, or user-defined contexts. A behavior policy engine maps the social context to coordinated actions across environment dimensions including notification routing, shared-surface content visibility, ambient settings, device routing, and security. Privacy routing rules prevent sensitive information from appearing on shared surfaces when non-primary household members are detected and instead route such …

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Split-Trust Key Derivation For Passkey-Authenticated Encrypted Data Backup And Recovery, Anonymous Jun 2026

Split-Trust Key Derivation For Passkey-Authenticated Encrypted Data Backup And Recovery, Anonymous

Defensive Publications Series

Techniques are described for passkey-authenticated encrypted backup and recovery using split-trust key derivation. A client device performs passkey authentication via WebAuthn/FIDO2 and invokes a PRF extension to obtain a high-entropy pseudorandom output. The client derives a client-side key component (e.g., a BackupRootKey via HKDF) from the PRF output and obtains a server-side secret from a backup service only after successful passkey authentication. The client combines the client-side key component and the server-side secret using a key derivation function to produce a backup encryption key used to encrypt backup data for cloud storage and to decrypt the backup during restore. Passkey …

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Quorum-Certified Partial State Recovery In Replicated Distributed Systems, Anonymous Jun 2026

Quorum-Certified Partial State Recovery In Replicated Distributed Systems, Anonymous

Defensive Publications Series

A replicated state machine maintains a quorum-attested committed-state shadow in addition to a consensus-replicated durable log. The shadow is organized into serviceable units (e.g., ranges, shards, or object groups) and includes, per unit, a log term/index through which the unit is safe and a deterministic digest of unit state, optionally with predecessor linkage, coverage metadata, and replica attestations. After leader failover, a replacement leader exchanges shadow records or attestations with followers and computes certified recovery frontiers per unit. In partial-recovery mode, a request gate permits reads from the shadow for certified units and may admit writes for certified units into …

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Ai-Driven Contextual Terminology Definition Generation For User Interface Elements, Anonymous Jun 2026

Ai-Driven Contextual Terminology Definition Generation For User Interface Elements, Anonymous

Defensive Publications Series

Systems and methods generate contextual, in-product definitions for domain terminology displayed in user interfaces. A client renders an annotated term and, upon a user click, sends the term and UI context to a backend definition service. The service checks a cache keyed by the term and context; when available, a cached definition is returned. Otherwise, the service invokes a language model with references to authoritative knowledge sources and an output contract requiring a definition of 20 words or fewer and a learn hyperlink to a wiki page that defines the term. The definition and hyperlink are presented via a standardized …

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