Back to corpus
research noteexperiment writeup candidatescore 40

Trust Translator System Documentation

1. [System Overview](#system-overview) 2. [Architecture](#architecture) 3. [Trust Scoring System](#trust-scoring-system) 4. [Intent Preservation Engine](#intent-preservation-engine) 5. [Style Translation](#style-translation) 6. [Cross-Domain Translation](#cross-domain-translation) 7. [API Reference](#api-reference) 8. [Evolution History](#evolution-history)

Full HTML reader

Read the full artifact

Open in new tab

Extracted abstract or opening context

**Version:** 2.5.0-gen13 **Evolution:** Generation 13 (Cross-Platform Intelligence) **Last Updated:** February 2025 1. [System Overview](#system-overview) 2. [Architecture](#architecture) 3. [Trust Scoring System](#trust-scoring-system) 4. [Intent Preservation Engine](#intent-preservation-engine) 5. [Style Translation](#style-translation) 6. [Cross-Domain Translation](#cross-domain-translation) 7. [API Reference](#api-reference) 8. [Evolution History](#evolution-history) Trust Translator is a sophisticated communication transformation system that converts text between communication styles while preserving semantic intent. Built on linguistic theory (Politeness Theory, Hofstede's Cultural Dimensions, Speech Act Theory), it enables contextually appropriate communication across different relationships, platforms, and cultures. | Capability | Description | |------------|-------------| | **Style Translation** | Transform casual ↔ formal, direct ↔ diplomatic | | **Intent Preservation** | Maintain semantic meaning through transformations | | **Trust Calibration** | Relationship-aware communication recommendations | | **Cultural Bridging** | Cross-cultural adaptation (Gen 10) | | **Platform Intelligence** | Platform-specific optimization (Gen 13) | | **Multi-party Facilitation** | Group conversation dynamics (Gen 9) | | **Streaming Translation** | Real-time token-by-token output (Gen 11) | | **Translation Memory** | Adaptive learning from feedback (Gen 12) | | Module | File | Purpose | |--------|------|---------| | **Styles** | `src/styles.ts` | Communication style definitions, markers, analysis | | **Intent** | `src/intent.ts` | Semantic extraction, SAO parsing, face threats | | **Trust** | `src/trust.ts` | Relationship tracking, style recommendations | | **Translator** | `src/translator.ts` | Core transformation engine | | **LLM Semantic** | `src/llm-semantic.ts` | Deep semantic understanding via LLM | | **Conversation Flow** | `src/conversation-flow.ts` | Multi-turn conversation tracking | | **Multi-Party** | `src/multiparty-engine.ts` | Group dynamics, facilitation | | **Cultural Bridge** | `src/cultural-bridge.ts` | Hofstede dimensions, cultural adaptation | | **Streaming** | `src/streaming-engine.ts` | Token-by-token translation | | **Translation Memory** | `src/translation-memory.ts` | Learning, feedback, preferences | | **Platform Intelligence** | `src/platform-intelligence.ts` | Platform detection and optimization |

Promotion decision

What has to happen next

Attach run IDs, datasets, metrics, and reproduction commands.

Why this is not always a full paper yet

Corpus pages are public-safe readers for discovered workspace artifacts. They are not automatically final papers. A corpus item becomes a polished paper only after the editable source, evidence checkpoints, references, figures, render path, and release status are attached through the paper schema.