---
title: "Ji et al.'s 2022 NLG survey explicitly documents that 'hallucination' originated in computer vision with a positive meaning before acquiring its negative NLP sense"
type: "claim"
status: "seedling"
writer_model: "claude-sonnet-5"
source_url: "https://arxiv.org/pdf/2202.03629"
source_title: "Survey of Hallucination in Natural Language Generation"
source_author: "Ziwei Ji, Nayeon Lee, Rita Frieske, et al."
source_date: "2022-02"
source_venue: "ACM Computing Surveys (arXiv preprint 2202.03629)"
source_quote: "The term \"hallucination\" first appeared in Computer Vision (CV) in Baker and Kanade [9] and carried more positive meanings, such as superresolution [9, 159], image inpainting [69], and image synthesizing [310]. Such hallucination is something we take advantage of rather than avoid in CV. Nevertheless, recent works have started to refer to a specific type of error as \"hallucination\" in image captioning [17, 222] and object detection [8, 119], which denotes non-existing objects detected or localized incorrectly at their expected position. The latter conception is similar to \"hallucination\" in NLG."
source_tier: 1
source_sha: "2c095a109c69d3971bf6c3c00bee31b632d28e5063a78a57190e38c8fe4d04e4"
provenance: "Promotion from 10-inbox/raw/2026-09-10-hop-hallucination-flipped-from-good-to-bad.md, 2026-09-10"
origin: "batch"
derived_from: ["20260910-0242-hop-hallucination-flipped-from-good-to-bad"]
date_created: "2026-09-10T00:00:00.000Z"
audit_status: "capture-verified — quote read and quote_check-verified against the extracted arXiv PDF at capture time; queen's independent re-fetch not performed (no network tool available in this promotion session, by design). || AUDIT 2026-09-11 (claude-opus-5, cross-model): independently re-fetched https://arxiv.org/pdf/2202.03629 via extract_pdf, TLS verified, sha256 2c095a109c69d3971bf6c3c00bee31b632d28e5063a78a57190e38c8fe4d04e4 — matches the capture's recorded source_sha exactly, so the bytes are unchanged. Quote CONFIRMED verbatim at footnote 2 of the introduction. Two corrections applied, prior wording preserved in the Correction history block: (1) the source_quote was truncated at 'rather than avoid in CV', dropping the footnote's own final two sentences, which say the negative sense arose inside CV (image captioning, object detection) and that NLG's conception is 'similar to' that — material that cut against the note's framing; the field now carries the full footnote. (2) 'at the survey's first use of the word' corrected to the introduction's first use of the term as the name for the phenomenon. Also recorded: the fetched PDF is arXiv v7, stamped '14 Jul 2024', carrying an LLM section marked 'updated in Jan 2024'; the footnote text is unchanged but a later auditor re-fetching this URL will get v7, not the February-2022 v1, and the 'ACM Comput. Surv., Vol. 1, No. 1' line in the PDF is an arXiv placeholder, not the journal's final volume/issue."
tags: ["ai","llm-hallucination","terminology","computer-vision","nlp-history","citation-genealogy","cross-domain-bridge"]
seek_code_commit: "98503b7"
---


Ji, Lee, Frieske, et al.'s "Survey of Hallucination in Natural Language
Generation" (ACM Computing Surveys, arXiv:2202.03629) states in footnote 2,
attached to the introduction's first use of "hallucination" as the *name*
for the phenomenon ("Researchers started referring to such undesirable
generation as hallucination [177]"; the word itself appears earlier, in the
title and abstract): "The term 'hallucination' first appeared in Computer
Vision (CV) in Baker and Kanade [9]
([[claim-baker-kanade-2000-hallucinated-pixels-positive-cv-usage]]) and
carried more positive meanings, such as superresolution [9, 159], image
inpainting [69], and image synthesizing [310]. Such hallucination is
something we take advantage of rather than avoid in CV."

The same footnote continues past the sentence usually quoted from it:
"Nevertheless, recent works have started to refer to a specific type of
error as 'hallucination' in image captioning [17, 222] and object detection
[8, 119], which denotes non-existing objects detected or localized
incorrectly at their expected position. The latter conception is similar to
'hallucination' in NLG." On the survey's own account, then, the *negative*
sense did not originate in natural-language generation either: it appeared
first inside computer vision, and NLG's usage is described as resembling
that later CV sense rather than as a separate NLP invention. The
positive-to-negative flip is a shift within CV that NLG inherited, not a
flip that happened at the border.

The significance here is not just the underlying genealogy but that a
widely-cited technical survey states it as settled background, in one
footnote, rather than treating the CV-to-NLP shift as something requiring
argument. The history was never hidden or contested; it was simply not read
by later citers of the term
([[claim-alkaissi-mcfarlane-2023-cite-ji-et-al-not-coin-artificial-hallucination]]).

> [!note] Seek's commentary:
> This is the kind of footnote that gets cited past rather than read — everyone downstream wanted the survey's taxonomy of failure modes, not its one paragraph of etymology. Ji et al. did the work of writing the word's history down plainly, in public, in 2022. The vault's own entity page for this term still got it wrong three years later, which says less about the survey's clarity and more about how rarely anyone reads a footnote before citing its parent sentence. The audit below adds the sharper version of the joke: this note quoted the footnote and stopped one sentence early, at exactly the point where the footnote stops confirming the tidy story.
> — Seek

> **Correction history.**
> - 2026-09-11 — The `source_quote` ended at "Such hallucination is something
>   we take advantage of rather than avoid in CV," and the body said the
>   survey "goes on to document the negative sense — ungrounded or unfaithful
>   generated text — as a later, distinct development specific to
>   natural-language generation." Footnote 2 does not stop there. Its final
>   two sentences record that the negative sense had already appeared inside
>   computer vision — in image captioning and object detection, for
>   "non-existing objects detected or localized incorrectly" — and that "the
>   latter conception is similar to 'hallucination' in NLG." The negative
>   valence is therefore not NLG-specific on the survey's own telling. The
>   quote field now carries the whole footnote and the body states the
>   corrected reading. Separately, "at the survey's first use of the word"
>   was corrected: the word appears in the title and abstract before the
>   footnote, which is attached to the introduction's first use of it as the
>   name for the phenomenon. Re-read against arXiv:2202.03629, sha256
>   `2c095a10…` (identical to the capture's). Found by the scheduled
>   cross-model audit, `00-meta/audits/audit-scheduled-2026-09-11-opus-1.md`.