README.md

metadata

license: other
language:
  - en
task_categories:
  - text-generation
pretty_name: WildDelusion Benchmark
size_categories:
  - n<1K

WildDelusion Benchmark

WildDelusion Benchmark is the minimal, peer-facing release of the final Gemini-filtered WildDelusion cohort. It contains 493 verified user target turns from 303 naturally occurring, publicly shared human-chatbot conversations.

Each row includes the complete reconstructed conversation, including every available assistant turn. Roles are normalized to user and assistant, and target_message_index is a zero-based index into messages that points exactly to target_text.

Data

The dataset intentionally has only six columns:

Column	Description
example_id	Stable SHA-256 identifier for the verified target turn.
source	Source corpus/model-family route.
conversation_id	Source conversation identifier; use with source for clustering.
messages	Complete ordered conversation as {role, content} records.
target_message_index	Zero-based location of the verified user target in messages.
target_text	Exact text at messages[target_message_index].

For response evaluation, provide the conversation only through the target user turn. Later messages are retained for longitudinal research but must not be included in the model input:

from datasets import load_dataset

dataset = load_dataset("danielfein/WildDelusionBenchmark", split="train")
row = dataset[0]
model_input = row["messages"][: row["target_message_index"] + 1]

Selection

This release is an exact projection of the 493 targets retained in danielfein/WildDelusionCombined revision 4749e769261c6b068da4a42aa0f91ff4903c2985. Admission required a score of at least 7 under the exact Moore et al. user-endorses-delusion rubric using gemini-3-flash-preview in both target-only and three-preceding-turn views. Twenty-nine of 522 pre-filter targets were excluded.

The conversations were independently rehydrated from pinned ShareChat and WildChat revisions. The release contains 24,170 user turns and 24,141 assistant turns. All 493 transcripts contain assistant messages; 425 targets have at least one assistant turn before the target. One conversation includes four assistant image-generation outputs whose text was unavailable in the source export; their positions are preserved with explicit non-text placeholders.

See manifest.json for pinned revisions and integrity_report.json for the machine-readable audit.

Scope and limitations

• Inclusion is a rubric-based content annotation, not a clinical diagnosis of a user or a claim about the user's mental state.
• The dataset is retrieval-enriched and must not be used to estimate population prevalence.
• Multiple targets may come from the same source conversation. Split or bootstrap by (source, conversation_id), not by row.
• The material can contain sensitive mental-health, self-harm, conspiratorial, and personally revealing content. Use appropriate access and review practices.
• Exact source model versions are not consistently available, so source identifies the corpus/model family rather than a guaranteed model snapshot.

Licensing

This combined release is non-commercial. ShareChat-derived content is subject to CC BY-NC 4.0 terms; WildChat-derived content is subject to ODC-By. Users are responsible for complying with the upstream datasets' terms and privacy guidance.