Datasets:
active_needle_spans list | available_modes list | backbone_sha256 string | canonical_passage_tokens int64 | canonical_tokenizer string | canonical_tokenizer_revision string | dataset_protocol_version string | design dict | design_variant string | geometry_panel_id string | gold_count int64 | gold_pairs list | hard_negative_spans list | haystack dict | mode_views dict | num_needles int64 | pair_id string | passage string | passage_sha256 string | row_id string | schema_version string | seed int64 | slots list | source_protocol_version string | source_schema_version string | split string | stimulus_id string | target_passage_tokens int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[
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"canonical_token_length": 30,
"char_end": 3538,
"char_start": 3453,
"city": "Chicago",
"needle_id": "N1",
"score": 72,
"slot_index": 1,
"text": "
Excerpt:\nIn the 2024 city score audit, Chicago received a score of 72.\... | [
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"native_thinking"
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"city_score_content_fixed_across_seeds": false,
"city_score_order_fixed_across_seeds": false,
"content_permutation_zero_based": [
4,
9,
8,
0,
3,
7,
1,
5,
2,
6
],
"content_seed": 366927173,
"family_key": "v4.4_T10000_seed123... | v4.4 | v4_4_seed1234_1263_count1_10_shared_geometry_v1 | 1 | [
{
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"slot_index": 1
}
] | [
{
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"char_end": 3412,
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"slot_index": 1,
"text": ", and with no idea who painted it? If you walk around a museum trying this experiment, you'll find you get some truly startling results.... | {
"duplicate_source_files_skipped": [],
"expanded_token_count": 11308,
"original_token_count": 11308,
"seed": 1234,
"source_file": "__multi_file_no_repeat__",
"source_file_count": 3,
"source_files": [
"copy.txt",
"gap.txt",
"boss.txt"
],
"source_mode": "multi_file_no_repeat",
"source_rep... | {
"native_thinking": {
"contract_id": "v4_4_native_thinking_concise_v1",
"contract_sha256": "5e610d1535efed5b0adeab2a1869d0c63cc5aaa8167def3ff11e7f533b719059",
"expected_final_line": "Total: 1",
"user_text_sha256": "675b78a96d9ac4e265404ec77785c7cc2d2326fd21b6ba931cf88afe71894971"
},
"non_thinking... | 1 | V4_4_T10000_N1_seed1234 | July 2006 When I was in high school I spent a lot of time imitating bad writers. What we studied in English classes was mostly fiction, so I assumed that was the highest form of writing. Mistake number one. The stories that seemed to be most admired were ones in which people suffered in complicated ways. Anything funny... | 6612ae61e6c3686bd20b1e8712fa0dfb89cb9f34a6adea339adffbc3fced1d64 | V4_4_T10000_N1_seed1234 | realistic_niah_count_geometry_shared_v2 | 1,234 | [
{
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"char_end": 3538,
"char_start": 3453,
"city": "Chicago",
"content_kind": "needle",
"content_text": "
Excerpt:\nIn the 2024 city score audit, Chicago received a score of 72.\nEn... | realistic_niah_v4_nonthinking_v3 | realistic_niah_v4_stimulus_v1 | discovery | V4_4_T10000_N1_seed1234 | 10,000 |
[
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"city": "Chicago",
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"slot_index": 1,
"text": "
Excerpt:\nIn the 2024 city score audit, Chicago received a score of 72.\... | [
"non_thinking",
"native_thinking"
] | 29c2b65f089c6b20742f3f4dd2ad07e923bb5b643b8f3f2f1d7789ce8e17b075 | 10,000 | Qwen/Qwen3-8B | b968826d9c46dd6066d109eabc6255188de91218 | v4_4_shared_geometry_mode_contracts_v2 | {
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],
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"family_key": "v4.4_T10000_seed123... | v4.4 | v4_4_seed1234_1263_count1_10_shared_geometry_v1 | 2 | [
{
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"slot_index": 1
},
{
"city": "Baku",
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"slot_index": 2
}
] | [
{
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"text": ", and with no idea who painted it? If you walk around a museum trying this experiment, you'll find you get some truly startling results.... | {
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"source_files": [
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"gap.txt",
"boss.txt"
],
"source_mode": "multi_file_no_repeat",
"source_rep... | {
"native_thinking": {
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"contract_sha256": "5e610d1535efed5b0adeab2a1869d0c63cc5aaa8167def3ff11e7f533b719059",
"expected_final_line": "Total: 2",
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},
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{
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Excerpt:\nIn the 2024 city score audit, Chicago received a score of 72.\nEn... | realistic_niah_v4_nonthinking_v3 | realistic_niah_v4_stimulus_v1 | discovery | V4_4_T10000_N2_seed1234 | 10,000 |
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[{"canonical_span_end":744,"canonical_span_start":714,"canonical_token_length":30,"char_end":3538,"c(...TRUNCATED) | [
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End of preview. Expand in Data Studio
Realistic NIAH count mechanism analysis
Version 2 stores the paired geometry panel once. The default
geometry_shared configuration contains 300 unique V4.4 stimulus rows: 200
discovery rows (seeds 1234-1253) and 100 held-out confirmation rows (seeds
1254-1263), with counts 1-10 balanced within every seed. Each pair_id is now
one row rather than two duplicated mode rows.
The common row contains the passage, gold records, slots, active needle spans,
hard negatives, design metadata, and a byte-canonical backbone_sha256.
mode_views stores only per-row prompt hashes and expected final lines for the
registered non_thinking and native_thinking contracts. Full prompt/runtime
contracts are stored once in contracts/MODE_CONTRACTS.json.
Frozen source
- Source protocol:
realistic_niah_v4_nonthinking_v3 - Design variant:
v4.4 - Canonical passage length: 10,000 Qwen3-8B tokenizer tokens
- Full source
stimuli.jsonlSHA-256:da4dd86142eb8a07f9a7e53497efd3375184c8e68367d4db994370fcb331f090 - Original full-grid audit: passed (1,200 rows across V4.1-V4.4)
The uploaded geometry config contains only the 300 V4.4 rows. source/
retains the original audit and a V4.4-only excerpt of the source manifest.
This repository contains inputs only: no model generations, parsed traces, hidden states, attention tables, representation outputs, causal results, or mechanism result schemas are included.
Prompt/runtime contract
To render a mode prompt, select its entry in contracts/MODE_CONTRACTS.json
and replace the single {{passage}} placeholder in user_text_template
with the row's passage. The resulting SHA-256 must equal
mode_views[mode].user_text_sha256.
non_thinking: disable native thinking, use the registered direct numeric prompt, and append the contract'sassistant_prefix(Total:) before scoring or generation.native_thinking: enable native thinking, use the registered concise reasoning prompt, and do not inject a synthetic reasoning scaffold.
The comparison treatment jointly includes the registered prompt contract and the chat-template thinking control. It is not a flag-only contrast.
Mode-specific causal extensions
Future causal inputs or result tables must not modify geometry_shared.
Register them in causal/REGISTRY.json and store files under
data/causal/<mode>/<experiment_id>/<split>.jsonl. Each registry entry records
its own row schema, seeds, counts, controls, hashes, and discovery/confirmation
policy. Non-thinking and native-thinking extensions may therefore add seeds
independently while retaining an immutable shared geometry panel.
When an extension is published through Dataset Viewer, expose it as a distinct
config named causal_<mode>_<experiment_id>; do not combine heterogeneous
experiment schemas into the default geometry config.
Migration from version 1
The previous non_thinking and native_thinking configs duplicated all 300
backbones. Their exact mode prompts remain reproducible from the v2 contracts
and per-row hashes. Pin the previous Hub revision if the legacy two-config row
shape is required.
Rendered token IDs are intentionally not stored because they depend on the model family and pinned tokenizer revision. Exact prompt-token needle spans must be reconstructed from each row's half-open passage character spans after applying the registered model chat template.
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