# Perplexity — Learning from Real-World Mistakes

- Company: Perplexity (perplexity.ai)
- Announced: 2026-09-21
- Category: capability-change
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://www.perplexity.ai/hub/blog/learning-from-real-world-mistakes
- Record: https://forck.live/items/12717-learning-from-real-world-mistakes
- Subject: Perplexity

Perplexity describes a training method combining rejection sampling fine-tuning with hint-guided self-distillation to learn from real-world user sessions. The approach distinguishes between successful and unsuccessful sessions, using user corrections and tool errors as training signals to reduce tool-call failures by 21.2% relative to an earlier checkpoint.

## Evidence

Verbatim from https://www.perplexity.ai/hub/blog/learning-from-real-world-mistakes:

> In live use, the later trained checkpoint reduced tool-call failures by 21.2% relative to an earlier trained checkpoint.

---

Record: https://forck.live/items/12717-learning-from-real-world-mistakes
Catalogue: https://forck.live/llms.txt
Current issue: https://forck.live/feed.md