The DOI matches its Crossref record.
Telling humans and computers apart automatically
Abstract
How lazy cryptographers do AI.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Designing human friendly human interaction proofs (HIPs)
Chellapilla, K., Larson, K., Simard, P., & Czerwinski, M. (2005) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1054972.1055070 · Cited by 261
Sybillimit: a near-optimal social network defense against sybil attacks
Yu, H., Gibbons, P. B., Kaminsky, M., & Xiao, F. (2010) · IEEE/ACM Transactions on Networking · doi:10.1109/tnet.2009.2034047 · Cited by 246
Working Together Apart: Collaboration over the Internet
Olson, J. S., & Olson, G. M. (2014) · Synthesis Lectures on Human-Centered Informatics · doi:10.2200/s00542ed1v01y201310hci020 · Cited by 95
Accessible privacy and security: a universally usable human-interaction proof tool
Sauer, G., Holman, J., Lazar, J., Hochheiser, H., & Feng, J. (2010) · Universal Access in the Information Society · doi:10.1007/s10209-009-0171-2 · Cited by 54
Patient-identified events implicated in the development of body dysmorphic disorder
Weingarden, H., Curley, E. E., Renshaw, K. D., & Wilhelm, S. (2017) · Body Image · doi:10.1016/j.bodyim.2017.02.003 · Cited by 48
Metadata
- Authors
- von Ahn, L., Blum, M., & Langford, J.
- Venue
- Communications of the ACM
- Published
- 2004-02
- Volume
- 47
- Issue
- 2
- Pages
- 56-60
- ISSN
- 0001-0782 (ISSN-L)
- 1557-7317
- OpenAlex
- W2072410439
- Cited by
- 895
- References
- 0
- FWCI
- 88.23
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Telling humans and computers apart automatically. https://app.cochat.ai/papers/10.1145/966389.966390
- The paper
- von Ahn, L., Blum, M., & Langford, J. (2004). Telling humans and computers apart automatically. Communications of the ACM. https://doi.org/10.1145/966389.966390
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
