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adult_content
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security(content-moderation): 🔒️ Add labeled examples for adult content, BDSM, and CSAM categories to improve harmful content classification accuracy
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2026-03-18 01:16:03 -07:00 |
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age_play
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perf(data): ⚡ Refine negative examples for age_play, consent_violation, and intoxication topics and update config.yaml for performance-optimized validation.
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2026-03-18 02:56:20 -07:00 |
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anti_trans
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docs(data): 📝 Add neutral and controversial content examples to innocuous.jsonl and anti_trans/ datasets for moderation training validation
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2026-03-18 15:33:59 -07:00 |
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bdsm
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security(content-moderation): 🔒️ Add labeled examples for adult content, BDSM, and CSAM categories to improve harmful content classification accuracy
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2026-03-18 01:16:03 -07:00 |
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bestiality
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chore(content-moderation): 🔧 Update and expand labeled datasets in data/generated/ with examples for solicitation, spam, trafficking, and harmful content (CSAM, bestiality) including hard negatives, positives, and innocuous samples
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2026-03-18 01:16:04 -07:00 |
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consent_violation
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perf(data): ⚡ Refine negative examples for age_play, consent_violation, and intoxication topics and update config.yaml for performance-optimized validation.
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2026-03-18 02:56:20 -07:00 |
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contact_info
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security(content-moderation): 🔒️ Add labeled examples for adult content, BDSM, and CSAM categories to improve harmful content classification accuracy
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2026-03-18 01:16:03 -07:00 |
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csam
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chore(content-moderation): 🔧 Update and expand labeled datasets in data/generated/ with examples for solicitation, spam, trafficking, and harmful content (CSAM, bestiality) including hard negatives, positives, and innocuous samples
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2026-03-18 01:16:04 -07:00 |
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doxxing
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security(content-moderation): 🔒️ Add labeled examples for adult content, BDSM, and CSAM categories to improve harmful content classification accuracy
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2026-03-18 01:16:03 -07:00 |
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edge_play
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feat(content-moderation): ✨ Add positive examples for edge cases and hate speech, update prompts in category_specs.py, and archive experiment exp31
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2026-03-18 14:10:50 -07:00 |
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extreme_gore
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docs(content-moderation): 📝 Add hard negative examples for extreme gore, harassment, and predatory behavior categories and update training/validation/test splits
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2026-03-18 18:06:48 -07:00 |
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financial_coercion
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chore(data): 🔧 Add/update labeled examples for 15 data categories (edge-play, extreme-gore, financial-coercion, furry, hate-speech, impersonation, intoxication, law-enforcement) with expanded positives/hard negatives
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2026-03-18 01:16:03 -07:00 |
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furry
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chore(data): 🔧 Add/update labeled examples for 15 data categories (edge-play, extreme-gore, financial-coercion, furry, hate-speech, impersonation, intoxication, law-enforcement) with expanded positives/hard negatives
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2026-03-18 01:16:03 -07:00 |
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harassment
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chore(content-moderation): 🔧 Update training examples and refine data merging logic in merge_data.py for improved harassment/predatory behavior detection
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2026-03-18 22:26:15 -07:00 |
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hate_speech
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feat(content-moderation): ✨ Add positive examples for edge cases and hate speech, update prompts in category_specs.py, and archive experiment exp31
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2026-03-18 14:10:50 -07:00 |
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impersonation
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chore(data): 🔧 Add/update labeled examples for 15 data categories (edge-play, extreme-gore, financial-coercion, furry, hate-speech, impersonation, intoxication, law-enforcement) with expanded positives/hard negatives
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2026-03-18 01:16:03 -07:00 |
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intoxication
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perf(data): ⚡ Refine negative examples for age_play, consent_violation, and intoxication topics and update config.yaml for performance-optimized validation.
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2026-03-18 02:56:20 -07:00 |
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law_enforcement
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chore(data): 🔧 Add/update labeled examples for 15 data categories (edge-play, extreme-gore, financial-coercion, furry, hate-speech, impersonation, intoxication, law-enforcement) with expanded positives/hard negatives
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2026-03-18 01:16:03 -07:00 |
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ncii
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security(moderation-data): 🔒️ Update training examples for harmful content detection to improve moderation accuracy
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2026-03-18 01:16:03 -07:00 |
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necrophilia
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chore(content-moderation): 🔧 Update and expand labeled datasets in data/generated/ with examples for solicitation, spam, trafficking, and harmful content (CSAM, bestiality) including hard negatives, positives, and innocuous samples
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2026-03-18 01:16:04 -07:00 |
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predatory_behavior
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chore(content-moderation): 🔧 Update training examples and refine data merging logic in merge_data.py for improved harassment/predatory behavior detection
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2026-03-18 22:26:15 -07:00 |
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profanity
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security(moderation-data): 🔒️ Update training examples for harmful content detection to improve moderation accuracy
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2026-03-18 01:16:03 -07:00 |
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roleplay
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security(moderation-data): 🔒️ Update training examples for harmful content detection to improve moderation accuracy
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2026-03-18 01:16:03 -07:00 |
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scam_patterns
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security(moderation-data): 🔒️ Update training examples for harmful content detection to improve moderation accuracy
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2026-03-18 01:16:03 -07:00 |
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scat
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chore(content-moderation): 🔧 Update and expand labeled datasets in data/generated/ with examples for solicitation, spam, trafficking, and harmful content (CSAM, bestiality) including hard negatives, positives, and innocuous samples
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2026-03-18 01:16:04 -07:00 |
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self_harm
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security(moderation-data): 🔒️ Update training examples for harmful content detection to improve moderation accuracy
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2026-03-18 01:16:03 -07:00 |
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sextortion
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security(moderation-data): 🔒️ Update training examples for harmful content detection to improve moderation accuracy
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2026-03-18 01:16:03 -07:00 |
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snuff
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chore(generated-data): 🔧 Update adversarial training data with negative examples and threat datasets
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2026-03-18 01:16:04 -07:00 |
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solicitation
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chore(content-moderation): 🔧 Update and expand labeled datasets in data/generated/ with examples for solicitation, spam, trafficking, and harmful content (CSAM, bestiality) including hard negatives, positives, and innocuous samples
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2026-03-18 01:16:04 -07:00 |
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spam
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chore(content-moderation): 🔧 Update and expand labeled datasets in data/generated/ with examples for solicitation, spam, trafficking, and harmful content (CSAM, bestiality) including hard negatives, positives, and innocuous samples
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2026-03-18 01:16:04 -07:00 |
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threats
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chore(generated-data): 🔧 Update adversarial training data with negative examples and threat datasets
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2026-03-18 01:16:04 -07:00 |
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trafficking
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chore(content-moderation): 🔧 Update and expand labeled datasets in data/generated/ with examples for solicitation, spam, trafficking, and harmful content (CSAM, bestiality) including hard negatives, positives, and innocuous samples
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2026-03-18 01:16:04 -07:00 |
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watersports
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chore(content-moderation): 🔧 Update and expand labeled datasets in data/generated/ with examples for solicitation, spam, trafficking, and harmful content (CSAM, bestiality) including hard negatives, positives, and innocuous samples
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2026-03-18 01:16:04 -07:00 |
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innocuous.jsonl
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docs(data): 📝 Add neutral and controversial content examples to innocuous.jsonl and anti_trans/ datasets for moderation training validation
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2026-03-18 15:33:59 -07:00 |
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perturbation_negatives.jsonl
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chore(data): 🔧 Update dataset splits and negative samples for improved model robustness
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2026-03-18 22:55:39 -07:00 |
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targeted_hard_negatives.jsonl.19d
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feat(content-moderation): ✨ Update pipeline logic to handle phased training data splits, add hard/positive examples, and improve classification documentation
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2026-03-10 14:43:12 -07:00 |
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targeted_positives.jsonl.19d
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feat(content-moderation): ✨ Update pipeline logic to handle phased training data splits, add hard/positive examples, and improve classification documentation
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2026-03-10 14:43:12 -07:00 |
