SRC01 — Hallucination Taxonomy Survey — Scorecard¶
Source¶
| Field | Value |
|---|---|
| Title | A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions |
| Publisher | arXiv / ACM Transactions on Information Systems |
| Authors | Huang et al. |
| Date | 2023 (updated 2024) |
| URL | https://arxiv.org/abs/2311.05232 |
| Type | Academic survey paper |
Summary Ratings¶
| Dimension | Rating |
|---|---|
| Reliability | High |
| Relevance | High |
| Missing data | Low |
| Measurement bias | Low |
| Selective reporting | Low |
| Randomization | N/A |
| Protocol deviation | N/A |
| COI/Funding | Low |
Rationale¶
| Dimension | Rationale |
|---|---|
| Reliability | Published in ACM TOIS; comprehensive survey of the field |
| Relevance | Provides the taxonomy that training materials should but do not use |
| Bias | Academic survey; systematic coverage |
Evidence Extracts¶
| Evidence | Summary |
|---|---|
| SRC01-E01 | Taxonomy includes intrinsic/extrinsic, factuality/faithfulness; hallucination types range from easily detectable to almost undetectable |