Karti Tripathi commited on
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Clarify text detectors and reproducibility in dataset card

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  1. README.md +6 -5
README.md CHANGED
@@ -98,8 +98,9 @@ Each row in `data/*.jsonl` is one episode:
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  - **Model input:** `context` and `turns`. Agent turns carry a `decision_point` and no text;
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  that is where the model answers.
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  - **Answer key:** `family`, `difficulty` and `decisions`. **Never put these in the prompt.**
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- - **Customer follow-ups are scripted.** They do not react to the model, so rollouts are
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- deterministic and evaluation is reproducible.
 
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  `raw/` holds the original two-file layout (`*.tickets.jsonl` = model input,
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  `*.targets.jsonl` = answer key, joined by `id`). `policies/policies.md` is the policy pack,
@@ -123,7 +124,7 @@ The reward is computed in three stages, in this order:
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  Over-escalation is penalised as hard as under-escalation. Escalating everything is the easy
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  local optimum when a reward is sloppy.
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- The full design, including the honest limits of the two text detectors, is in
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  `docs/EVALUATOR.md`. The reference scorer is open source in
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  [support-rl](https://github.com/karti-ai/support-rl); `docs/EVALUATOR.md` is its specification. Three worked episodes set the
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  quality bar in `docs/GOLD-EXAMPLES.md`.
@@ -177,8 +178,8 @@ to match it. Every change is listed in `docs/REVIEW-LOG.md`.
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  amendments that the SEC approved in April 2026 (Regulatory Notice 26-10, effective
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  2026-06-04). The pack is fictional house policy. Do not treat it as current regulation.
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  - **English only, text only, one fictional firm.**
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- - **Two detectors are heuristic.** Investment advice and unstated timelines are caught by
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- text detectors with known limits (see `docs/EVALUATOR.md`). The advice detector misses
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  indirect recommendations ("it's probably wise to…"). The timeline detector cannot tell
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  CMP-04's acknowledgement window from an invented resolution time of the same length.
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  - **Model input:** `context` and `turns`. Agent turns carry a `decision_point` and no text;
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  that is where the model answers.
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  - **Answer key:** `family`, `difficulty` and `decisions`. **Never put these in the prompt.**
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+ - **Customer follow-ups are scripted.** They do not react to the model, so the customer
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+ path is fixed. Model serving can still vary at temperature 0; the published results can
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+ be reproduced offline by re-scoring the saved outputs in [support-rl](https://github.com/karti-ai/support-rl).
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  `raw/` holds the original two-file layout (`*.tickets.jsonl` = model input,
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  `*.targets.jsonl` = answer key, joined by `id`). `policies/policies.md` is the policy pack,
 
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  Over-escalation is penalised as hard as under-escalation. Escalating everything is the easy
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  local optimum when a reward is sloppy.
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+ The full design, including the honest limits of the three text detectors, is in
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  `docs/EVALUATOR.md`. The reference scorer is open source in
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  [support-rl](https://github.com/karti-ai/support-rl); `docs/EVALUATOR.md` is its specification. Three worked episodes set the
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  quality bar in `docs/GOLD-EXAMPLES.md`.
 
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  amendments that the SEC approved in April 2026 (Regulatory Notice 26-10, effective
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  2026-06-04). The pack is fictional house policy. Do not treat it as current regulation.
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  - **English only, text only, one fictional firm.**
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+ - **Three checks use text detectors.** Disclosure before verification, investment advice,
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+ and unstated timelines are caught by text detectors with known limits (see `docs/EVALUATOR.md`). The advice detector misses
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  indirect recommendations ("it's probably wise to…"). The timeline detector cannot tell
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  CMP-04's acknowledgement window from an invented resolution time of the same length.
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