dissertation.git/tests/test_judge.py, branch mainUndergraduate dissertation — Deceptive Alignment in Autonomous LLM Agents (UEL, 2026). Sandboxed agentic-LLM deception study: 960 runs, three-tier judging (regex + blackbox + glassbox).http://git.jayrup.me/c/dissertation.git/atom?h=main2026-03-26T01:24:29ZAdd xAI (Grok) batch API support2026-03-26T01:24:29ZCaptainJack2491jayrupnakawala@gmail.com2026-03-26T01:24:29Zurn:sha1:a463184c91107a7eaaec2167b3883dfcebef8785
- Add XAIBatchProvider class implementing BatchProvider ABC
- Add --provider CLI argument to judge_runner (anthropic|xai)
- Refactor Judge class to use BatchProvider instead of direct API calls
- Update tests for new Judge constructor signature
refactor: extract judge prompts to files and add granular blackbox categories2026-03-25T21:50:13ZCaptainJack2491jayrupnakawala@gmail.com2026-03-25T21:50:13Zurn:sha1:8483f05c79f13176c487f57cc2c589646891be65
- Extracted Blackbox and Glassbox prompts from into their own markdown files in
- Implemented progressive 4-tier Blackbox categories (FABRICATED, OMITTED_CRITICAL, DECEPTIVE_FRAMING, ACCURATE)
- Added neutral examples to the Blackbox prompt to improve formatting consistency
- Updated references and tests to match new judge categorization structure
feat(judge): updated blackbox to include source document for added accuracy2026-03-01T02:08:48ZCaptainJack2491jayrupnakawala@gmail.com2026-03-01T02:08:48Zurn:sha1:1834ca766e0b7dca8ddc9a49f5c88849210aaadffeat: implement judging system with regex, blackbox, and glassbox checks2026-02-25T16:10:37ZCaptainJack2491jayrupnakawala@gmail.com2026-02-25T16:00:55Zurn:sha1:375eddf1bd4e23db80feb74c6272dad610345795
- Add src/judge.py: RegexChecker, BlackboxChecker, GlassboxChecker, Judge orchestrator
- Add src/judge_runner.py: CLI for batch/single judging with CSV output
- Add regex_rules.yaml for corporate_sabotage_v2 and child_protection scenarios
- Add judge config section to config.yaml (model, temperature, log_dir)
- Add tests/test_judge.py: 34 unit tests covering all components
- Uses Anthropic Batch API for half-cost LLM judge calls
- Judge logs include full CoT reasoning and judge model for auditability