The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
query_id: string
question: string
qtype: string
day_asked: int64
seq: int64
hops: int64
fact_keys: list<item: string>
child 0, item: string
answer_display: string
accepted: list<item: string>
child 0, item: string
rejected: list<item: string>
child 0, item: string
heat: string
n_updates_before: int64
config: struct<preset: string, n_days: int64, n_persons: int64, n_projects: int64, events_min: int64, events (... 272 chars omitted)
child 0, preset: string
child 1, n_days: int64
child 2, n_persons: int64
child 3, n_projects: int64
child 4, events_min: int64
child 5, events_max: int64
child 6, hot_fraction: double
child 7, hot_pick_day: int64
child 8, multihop_min_gap: int64
child 9, quotas: struct<current_stable: int64, current_updated: int64, current_volatile: int64, point_in_time: int64, (... 69 chars omitted)
child 0, current_stable: int64
child 1, current_updated: int64
child 2, current_volatile: int64
child 3, point_in_time: int64
child 4, multihop_2: int64
child 5, multihop_3: int64
child 6, revoked: int64
child 7, absent: int64
child 10, seed: int64
hot_set: list<item: string>
child 0, item: string
est_tokens: int64
warnings: list<item: string>
child 0, item: string
counts: struct<episodes: int64, online_queries: int64, final_queries: int64, final_by_type: struct<current_s (... 168 chars omitted)
child 0, episodes: int64
child 1, online_queries: int64
child 2, final_queries: int64
child 3, final_by_type: struct<current_stable: int64, current_updated: int64, current_volatile: int64, point_in_time: int64, (... 69 chars omitted)
child 0, current_stable: int64
child 1, current_updated: int64
child 2, current_volatile: int64
child 3, point_in_time: int64
child 4, multihop_2: int64
child 5, multihop_3: int64
child 6, revoked: int64
child 7, absent: int64
child 4, facts: int64
to
{'config': {'preset': Value('string'), 'n_days': Value('int64'), 'n_persons': Value('int64'), 'n_projects': Value('int64'), 'events_min': Value('int64'), 'events_max': Value('int64'), 'hot_fraction': Value('float64'), 'hot_pick_day': Value('int64'), 'multihop_min_gap': Value('int64'), 'quotas': {'current_stable': Value('int64'), 'current_updated': Value('int64'), 'current_volatile': Value('int64'), 'point_in_time': Value('int64'), 'multihop_2': Value('int64'), 'multihop_3': Value('int64'), 'revoked': Value('int64'), 'absent': Value('int64')}, 'seed': Value('int64')}, 'counts': {'episodes': Value('int64'), 'online_queries': Value('int64'), 'final_queries': Value('int64'), 'final_by_type': {'current_stable': Value('int64'), 'current_updated': Value('int64'), 'current_volatile': Value('int64'), 'point_in_time': Value('int64'), 'multihop_2': Value('int64'), 'multihop_3': Value('int64'), 'revoked': Value('int64'), 'absent': Value('int64')}, 'facts': Value('int64')}, 'est_tokens': Value('int64'), 'hot_set': List(Value('string')), 'warnings': List(Value('string'))}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
query_id: string
question: string
qtype: string
day_asked: int64
seq: int64
hops: int64
fact_keys: list<item: string>
child 0, item: string
answer_display: string
accepted: list<item: string>
child 0, item: string
rejected: list<item: string>
child 0, item: string
heat: string
n_updates_before: int64
config: struct<preset: string, n_days: int64, n_persons: int64, n_projects: int64, events_min: int64, events (... 272 chars omitted)
child 0, preset: string
child 1, n_days: int64
child 2, n_persons: int64
child 3, n_projects: int64
child 4, events_min: int64
child 5, events_max: int64
child 6, hot_fraction: double
child 7, hot_pick_day: int64
child 8, multihop_min_gap: int64
child 9, quotas: struct<current_stable: int64, current_updated: int64, current_volatile: int64, point_in_time: int64, (... 69 chars omitted)
child 0, current_stable: int64
child 1, current_updated: int64
child 2, current_volatile: int64
child 3, point_in_time: int64
child 4, multihop_2: int64
child 5, multihop_3: int64
child 6, revoked: int64
child 7, absent: int64
child 10, seed: int64
hot_set: list<item: string>
child 0, item: string
est_tokens: int64
warnings: list<item: string>
child 0, item: string
counts: struct<episodes: int64, online_queries: int64, final_queries: int64, final_by_type: struct<current_s (... 168 chars omitted)
child 0, episodes: int64
child 1, online_queries: int64
child 2, final_queries: int64
child 3, final_by_type: struct<current_stable: int64, current_updated: int64, current_volatile: int64, point_in_time: int64, (... 69 chars omitted)
child 0, current_stable: int64
child 1, current_updated: int64
child 2, current_volatile: int64
child 3, point_in_time: int64
child 4, multihop_2: int64
child 5, multihop_3: int64
child 6, revoked: int64
child 7, absent: int64
child 4, facts: int64
to
{'config': {'preset': Value('string'), 'n_days': Value('int64'), 'n_persons': Value('int64'), 'n_projects': Value('int64'), 'events_min': Value('int64'), 'events_max': Value('int64'), 'hot_fraction': Value('float64'), 'hot_pick_day': Value('int64'), 'multihop_min_gap': Value('int64'), 'quotas': {'current_stable': Value('int64'), 'current_updated': Value('int64'), 'current_volatile': Value('int64'), 'point_in_time': Value('int64'), 'multihop_2': Value('int64'), 'multihop_3': Value('int64'), 'revoked': Value('int64'), 'absent': Value('int64')}, 'seed': Value('int64')}, 'counts': {'episodes': Value('int64'), 'online_queries': Value('int64'), 'final_queries': Value('int64'), 'final_by_type': {'current_stable': Value('int64'), 'current_updated': Value('int64'), 'current_volatile': Value('int64'), 'point_in_time': Value('int64'), 'multihop_2': Value('int64'), 'multihop_3': Value('int64'), 'revoked': Value('int64'), 'absent': Value('int64')}, 'facts': Value('int64')}, 'est_tokens': Value('int64'), 'hot_set': List(Value('string')), 'warnings': List(Value('string'))}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
π§ AgentLife β a self-validating benchmark for long-lived agent memory
Paper: The Ledger Knows What the Weights Know: Entity-Level Parametric Memory with Provenance Guarantees for LLM Agents β doi:10.5281/zenodo.21375428 (concept DOI, resolves to latest; this mirror ships the exact datasets evaluated in v2.1: 10.5281/zenodo.21396695) Β· Code + generator: https://github.com/caiovicentino/cls-ledger
AgentLife generates synthetic "lives" of a personal-assistant agent β a stream of dated episodes where facts are stated, updated, revoked, and interleaved with noise β followed by a final exam. The answer key is correct by construction: every answer derives from a programmatic temporal world state, never hand-annotation.
π― Why another memory benchmark
Each design principle answers a documented failure of existing agent-memory benchmarks (e.g. the LoCoMo audit: 6.4% of the answer key wrong, an LLM judge accepting ~63% of deliberately wrong answers):
| principle | enforcement |
|---|---|
| Answer key correct by construction | a privileged oracle must score exactly 100% β CI test |
| Freshness is falsifiable | a deliberately stale oracle must score 0% on updated-fact probes β CI test |
| Exact, auditable scoring | every query ships accepted + rejected surface forms; word-boundary matching; no LLM judge |
| Typed errors | correct / stale / hallucination / wrong_value / ambiguous / abstain / miss |
| Instrumented usage | online queries mark facts hot/cold β consolidation-policy experiments |
| Deterministic | same preset+seed β byte-identical dataset across processes and hash seeds β CI test |
π Query types
current_stable Β· current_updated (old values rejected) Β·
current_volatile Β· point_in_time (value as of day D) Β·
multihop_2/3 Β· revoked Β· absent (hallucination/abstention probe) Β·
online β plus, in v2 datasets (*v5): quantitative induction
(count / weekday-habit / trend over fact histories) and behavioral
dispositions (rules declared once, scored at the final exam with no
reminder), and an adversarial paraphrase protocol
(final_queries_paraphrased.jsonl) that measures benchmarkβsystem
co-adaptation.
π Layout
13 datasets: S-1..S-5 (30-day lives), M-1..M-3 (90-day),
M-9v5..M-12v5 (90-day with induction+disposition cells), L-1
(365-day). Each contains:
manifest.json
public/ # all a system may see
stream.jsonl # dated episodes (facts + noise)
episodes.jsonl
final_queries.jsonl
final_queries_paraphrased.jsonl
private/ # scoring only β answer key, world state, usage stats
β οΈ private/ is for scoring only. A system under evaluation must
never read it; the split is the benchmark's contract, not a secrecy
mechanism.
π¬ Reference-system signature (M-1)
| system | final acc | what it validates |
|---|---|---|
| oracle | 100% | answer key + scorer, end to end |
| stale oracle | 64.6% | 0% on updated/volatile/revoked β rejected-sets catch staleness |
| null | 9.8% | abstention floor (100% on absent only) |
π Use
git clone https://github.com/caiovicentino/cls-ledger
# regenerate any dataset bit-for-bit (deterministic per seed):
PYTHONPATH=. python3 -m agentlife.generate --preset M --seed 1 --out data/M-1
# validate the mirror: the oracle must print 100%
PYTHONPATH=. python3 -m agentlife.harness.run_eval --data data/M-1 --system oracle
π Citation
@misc{vicentino2026ledger,
author = {Vicentino, Caio},
title = {The Ledger Knows What the Weights Know: Entity-Level
Parametric Memory with Provenance Guarantees for LLM Agents},
year = {2026},
publisher = {Zenodo},
doi = {10.5281/zenodo.21375428},
url = {https://doi.org/10.5281/zenodo.21375428}
}
π Links
- π Paper (v2.1): https://doi.org/10.5281/zenodo.21396695
- π» Code, generator, harness: https://github.com/caiovicentino/cls-ledger
- π¦
obsidian-ledger(the architecture on your own vault, any coding agent): https://github.com/caiovicentino/cls-ledger/releases/tag/v2.1 - π§ OpenInterpretability collection: https://huggingface.co/collections/caiovicentino1/openinterpretability
π Acknowledgements
Experiments, code, and drafting carried out with the assistance of
Claude (Anthropic). Every number in the paper maps to a JSON artifact in
the repository (paper/REPRODUCING.md).
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