An intelligent framework for auto-filling web forms from different web applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
End-users compose ad-hoc business processes by integrating web applications to conduct online tasks. Generally, end-users have to enter information into web forms of web applications, and often repetitively type the same information into applications. It could be a tedious job for end-users to fill in web forms with identical information. To save end-users from repetitive typing and increase composition productivity, it is critical to propagate and pre-fill user inputs to web applications. In this paper, we propose an intelligent auto-filling framework collecting and propagating user inputs across web applications, identifying user usage patterns and contexts. The empirical results show that our framework, on average, achieves a precision of 74.5% and a recall of 58% on pre-filling web forms, and a precision of 82.25% and a recall of 68.4% on suggesting values to end-users if the end-users edit the initial pre-filled values.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it