ReadOnce: I wanted less rereading, so I kept the model's mistake visible

说明与用途

ReadOnce 是一个网页应用，使用句子嵌入和词汇过滤器比较旧笔记与新笔记，标记可能的重复，并输出审计 JSON，同时保留所有原始文本。

问题

Users need to detect repeated or paraphrased content in new notes without losing the original text or relying on external APIs.

结果

In 4/4 calibration and 12/12 held‑out synthetic cases, ReadOnce matched expectations, outperforming an exact‑only baseline (0/4 and 10/12). One role‑swap miss was documented and retained for transparency.

工作流

• Load current and earlier notes into the two input boxes
• The app tokenizes each note and generates 384‑dimensional vectors via Xenova/all-MiniLM-L6-v2
• Compute cosine similarity between each current note and all earlier notes
• Apply lexical guards (quantity, date, negation, status words, uppercase identifiers) to filter false positives
• Flag notes with cosine ≥0.82, runner‑up gap ≥0.06, and equal protected lexical facts as "possible repeat"
• Render all current notes with reference links and reasons
• Export audit JSON containing original text, references, scores, reasons, settings and timings

证据

ReadOnce takes a smaller job: compare an earlier set of notes with a current one and suggest which lines might repeat earlier meaning. It keeps every current line, its earlier reference, the actual model score and a reason. Nothing is deleted or rewritten.

来源

The final actual browser-model run matched the authored expectations in 4/4 calibration cases and 12/12 held-out cases.

来源

The matching rule is deliberately visible: cosine at least 0.82, a best-versus-runner-up gap of at least 0.06, and equal protected lexical facts.

来源