EditLens: Quantifying the Extent of AI Editing in Text
Paper • 2510.03154 • Published
Qwen3-0.6B SFT'd on text→text_type pairs from pangram/editlens_iclr to output one of three labels: human_written, ai_edited, or ai_generated.
No thinking mode, direct label output only.
This is a WIP and requires review. See the benchmark script for methodology. If you find any mistakes, please let me know. Refer the official EditLens Repo and their paper for more context.
| Parameter | Value |
|---|---|
| Base model | unsloth/qwen3-0.6b-unsloth-bnb-4bit |
| Epochs | 1 (1875 steps) |
| Learning rate | 5e-5 (linear schedule) |
| Warmup steps | 50 |
| Optimizer | AdamW 8-bit |
| Per-device batch size | 2 |
| Gradient accumulation | 16 |
| Effective batch size | 32 |
| Max sequence length | 2048 |
| LoRA rank / alpha | 16 / 16 |
| Seed | 3407 |
Trained with Unsloth and HuggingFace TRL.
Paper baselines from EditLens (ICLR 2026, Table 2). Dark-edged bars = local run(Open Source).
Paper baselines from Table 1, Section 4.2
Full benchmark pipeline and raw predictions: revalidate/