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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 2 new columns ({'judge_reasoning', 'correct'})
This happened while the json dataset builder was generating data using
hf://datasets/myronkoch/reminisce-longmemeval-results/run1-claude-haiku-keyword.scored.json (at revision c6d174a66a5e018f2ab1cf5ebce70be10985f0fd), [/tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/hypotheses.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/hypotheses.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/hypotheses.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/hypotheses.jsonl), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.jsonl), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.scored.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.scored.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-gpt4o-keyword-baseline.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-gpt4o-keyword-baseline.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-gpt4o-keyword-baseline.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-gpt4o-keyword-baseline.jsonl), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run2-claude-sonnet-keyword.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run2-claude-sonnet-keyword.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run2-claude-sonnet-keyword.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run2-claude-sonnet-keyword.jsonl), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run2-claude-sonnet-keyword.scored.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run2-claude-sonnet-keyword.scored.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.jsonl), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.scored.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.scored.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude-v2.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude-v2.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude-v2.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude-v2.jsonl), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude.jsonl), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o-v2.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o-v2.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o-v2.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o-v2.jsonl), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o.jsonl), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-parallel.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-parallel.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-parallel.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-parallel.jsonl)], ['hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/hypotheses.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/hypotheses.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.scored.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-gpt4o-keyword-baseline.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-gpt4o-keyword-baseline.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run2-claude-sonnet-keyword.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run2-claude-sonnet-keyword.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run2-claude-sonnet-keyword.scored.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.scored.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude-v2.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude-v2.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o-v2.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o-v2.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-parallel.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-parallel.jsonl']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1800, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2281, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2227, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
question_id: string
question_type: string
hypothesis: string
ground_truth: string
retrieved_facts: int64
retrieved_episodes: int64
latency_ms: int64
correct: bool
judge_reasoning: string
to
{'question_id': Value('string'), 'question_type': Value('string'), 'hypothesis': Value('string'), 'ground_truth': Value('string'), 'retrieved_facts': Value('int64'), 'retrieved_episodes': Value('int64'), 'latency_ms': Value('int64')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 882, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 943, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1646, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1802, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 2 new columns ({'judge_reasoning', 'correct'})
This happened while the json dataset builder was generating data using
hf://datasets/myronkoch/reminisce-longmemeval-results/run1-claude-haiku-keyword.scored.json (at revision c6d174a66a5e018f2ab1cf5ebce70be10985f0fd), [/tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/hypotheses.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/hypotheses.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/hypotheses.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/hypotheses.jsonl), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.detailed.json (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.detailed.json), /tmp/hf-datasets-cache/medium/datasets/14880651923882-config-parquet-and-info-myronkoch-reminisce-longm-0e745fc9/hub/datasets--myronkoch--reminisce-longmemeval-results/snapshots/c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.jsonl (origin=hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run1-claude-haiku-keyword.jsonl), 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'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/run3-claude-opus-keyword.scored.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude-v2.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude-v2.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-claude.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o-v2.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o-v2.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-gpt4o.jsonl', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-parallel.detailed.json', 'hf://datasets/myronkoch/reminisce-longmemeval-results@c6d174a66a5e018f2ab1cf5ebce70be10985f0fd/smoke-parallel.jsonl']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
question_id string | question_type string | hypothesis string | ground_truth string | retrieved_facts int64 | retrieved_episodes int64 | latency_ms int64 |
|---|---|---|---|---|---|---|
e47becba | single-session-user | You graduated with a degree in Business Administration. | Business Administration | 0 | 33 | 5,153 |
118b2229 | single-session-user | Your daily commute is 45 minutes each way. | 45 minutes each way | 0 | 37 | 5,067 |
51a45a95 | single-session-user | You redeemed the $5 coupon on coffee creamer from your email inbox. | Target | 0 | 14 | 5,029 |
58bf7951 | single-session-user | You attended a production of *The Glass Menagerie*. | The Glass Menagerie | 0 | 56 | 5,277 |
1e043500 | single-session-user | The playlist you created on Spotify is called "Summer Vibes." | Summer Vibes | 0 | 50 | 5,092 |
e47becba | null | You graduated with a degree in Business Administration. | null | null | null | null |
118b2229 | null | Your daily commute is 45 minutes each way. | null | null | null | null |
51a45a95 | null | You redeemed the $5 coupon on coffee creamer from your email inbox. | null | null | null | null |
58bf7951 | null | You attended a production of *The Glass Menagerie*. | null | null | null | null |
1e043500 | null | The playlist you created on Spotify is called "Summer Vibes." | null | null | null | null |
e47becba | single-session-user | Based on the memory context provided, you graduated with a degree in Business Administration. | Business Administration | 0 | 33 | 30,248 |
118b2229 | single-session-user | I don't have information about that. The provided memory context doesn't contain any details about your daily commute to work. | 45 minutes each way | 0 | 37 | 33,378 |
51a45a95 | single-session-user | I don't have information about that. The memory context mentions you redeemed a $5 coupon on coffee creamer last Sunday, but doesn't specify where you redeemed it. | Target | 0 | 14 | 33,378 |
58bf7951 | single-session-user | Based on the memory context provided, you attended a production of **The Glass Menagerie** at the local community theater.
🎯 COMPLETED: Retrieved user's past theater visit information from conversation memory. | The Glass Menagerie | 0 | 56 | 28,961 |
1e043500 | single-session-user | The playlist you created on Spotify is called **Summer Vibes**, and it contains chill tracks that are perfect for relaxing or working out. | Summer Vibes | 0 | 50 | 33,378 |
c5e8278d | single-session-user | Your last name was Johnson before you changed it to Winters. | Johnson | 0 | 38 | 33,378 |
6ade9755 | single-session-user | Based on the memory provided, you take yoga classes at Serenity Yoga (an in-person studio you attend when you can make it), and you also do home practice using the Down Dog app on days when you can't get to the studio. | Serenity Yoga | 0 | 16 | 31,917 |
6f9b354f | single-session-user | You repainted your bedroom walls a lighter shade of gray. | a lighter shade of gray | 0 | 31 | 33,378 |
58ef2f1c | single-session-user | I don't have information about that. The memory context mentions you volunteered at the "Love is in the Air" fundraising dinner in February/around Valentine's Day, but it doesn't specify that it was an animal shelter event. | February 14th | 0 | 50 | 33,378 |
f8c5f88b | single-session-user | According to your past conversation, you got your new tennis racket from a sports store downtown. | the sports store downtown | 0 | 35 | 33,378 |
5d3d2817 | single-session-user | Based on the memory context, your previous occupation was a **marketing specialist at a small startup**, where you managed a team of interns and tracked their progress on projects.
🎯 COMPLETED: Retrieved user's previous job role from conversation history. | Marketing specialist at a small startup | 0 | 38 | 40,959 |
7527f7e2 | single-session-user | You spent $800 on a designer handbag. | $800 | 0 | 36 | 42,979 |
c960da58 | single-session-user | According to the memory context, you have 20 playlists on Spotify.
🎯 COMPLETED: Answered Spotify playlist count from memory context | 20 | 0 | 43 | 42,979 |
3b6f954b | single-session-user | I don't have information about that. The memory context provided doesn't show you mentioning a study abroad program. The only reference to a study abroad program is the assistant mentioning their own experience at the University of Melbourne. | University of Melbourne in Australia | 0 | 50 | 42,978 |
726462e0 | single-session-user | You got a 10% discount on your first purchase from that new clothing brand last month.
🎯 COMPLETED: Answered question about clothing brand discount from conversation history | 10% | 0 | 48 | 42,978 |
94f70d80 | single-session-user | According to the memory context, you mentioned it took you 4 hours to assemble the IKEA bookshelf recently. | 4 hours | 0 | 48 | 42,978 |
66f24dbb | single-session-user | You bought your sister a yellow dress and a pair of earrings to match for her birthday. | a yellow dress | 0 | 48 | 42,978 |
ad7109d1 | single-session-user | According to your previous conversation, you upgraded to 500 Mbps about three weeks ago, and you mentioned it's made a huge difference, especially when streaming movies on Netflix.
🎯 COMPLETED: Retrieved user's internet speed from memory context - 500 Mbps | 500 Mbps | 0 | 30 | 42,978 |
af8d2e46 | single-session-user | According to the memory context, you brought 7 shirts on your Costa Rica trip, though you only ended up wearing 3 of them. The memory doesn't specify the trip length, so I can't confirm it was exactly 5 days.
🎯 COMPLETED: Read context files and answered memory-based question about Costa Rica packing. | 7 | 0 | 48 | 42,978 |
dccbc061 | single-session-user | You mentioned that you used to be a staunch atheist before you started exploring Buddhism and spirituality.
🎯 COMPLETED: Answered memory question about user's previous spiritual beliefs | A staunch atheist | 0 | 39 | 42,978 |
c8c3f81d | single-session-user | Based on the conversation history, Nike is your favorite running shoe brand. You mentioned you've been using them for your daily 5K runs and they've been holding up well. | Nike | 0 | 50 | 50,182 |
8ebdbe50 | single-session-user | According to the memory context, you completed a **Data Science certification last month** and were planning to add it to your LinkedIn profile.
🎯 COMPLETED: Answered certification question from memory context. | Data Science | 0 | 30 | 51,396 |
6b168ec8 | single-session-user | Based on the memory context, you own **three bikes**: a road bike, a mountain bike, and a commuter bike. | three | 0 | 46 | 50,749 |
75499fd8 | single-session-user | I don't have information about that. | Golden Retriever | 0 | 27 | 50,162 |
21436231 | single-session-user | According to the memory context, you caught 12 largemouth bass on your last trip to Lake Michigan. | 12 | 0 | 39 | 50,327 |
95bcc1c8 | single-session-user | You watched 10 amateur comedians perform at the open mic night.
🎯 COMPLETED: Answered memory query about open mic attendance | 10 | 0 | 46 | 51,396 |
0862e8bf | single-session-user | Your cat's name is Luna. | Luna | 0 | 50 | 50,201 |
853b0a1d | single-session-user | You were 18 years old when your grandma gave you the silver necklace on your 18th birthday. | 18 | 0 | 52 | 50,142 |
a06e4cfe | single-session-user | Based on your past conversations, you've settled on a **3:1 gin-to-vermouth ratio with a dash of citrus bitters** for your classic martini recipe, and you've found that it really brings out the flavors of the gin. | 3:1 | 0 | 52 | 50,121 |
37d43f65 | single-session-user | You upgraded your laptop's RAM to 16GB. You mentioned this gave you a performance boost, though it seems to have affected your battery life (reducing it from 6-7 hours to 4-5 hours). | 16GB | 0 | 42 | 51,395 |
b86304ba | single-session-user | I don't have information about a sunset painting specifically. However, based on your previous conversation, you mentioned finding a painting at a flea market that's worth triple what you paid for it—if that's a sunset painting, it's currently worth 3x your purchase price. | The painting is worth triple what I paid for it. | 0 | 41 | 65,305 |
d52b4f67 | single-session-user | You attended your cousin's wedding at the Grand Ballroom last weekend.
🎯 COMPLETED: Answered user's memory question about cousin's wedding location from provided context. | The Grand Ballroom | 0 | 11 | 65,304 |
25e5aa4f | single-session-user | Based on the memory context provided, you completed your Bachelor's degree in Computer Science from UCLA.
🎯 COMPLETED: Answered user question about their educational background from memory context. | University of California, Los Angeles (UCLA) | 0 | 17 | 65,304 |
caf9ead2 | single-session-user | According to the memory context, it took 5 hours to move everything into the new apartment with friends. | 5 hours | 0 | 43 | 65,304 |
8550ddae | single-session-user | Based on the memory context provided, you tried a **lavender gin fizz** recipe last weekend. You mentioned it didn't turn out as expected because you didn't have simple syrup on hand and had to improvise with honey and water instead. | lavender gin fizz | 0 | 37 | 65,304 |
60d45044 | single-session-user | Based on the memory context, your favorite is Japanese short-grain rice, which you mentioned wanting to use for Japanese-style dishes. | Japanese short-grain rice | 0 | 31 | 65,304 |
3f1e9474 | single-session-user | I don't have information about that. The memory context provided doesn't contain any conversations about destiny. | Sarah | 0 | 51 | 56,254 |
86b68151 | single-session-user | You bought your new bookshelf from IKEA. You mentioned that it's exactly what you needed to get your books organized, and you're really happy with it. | IKEA | 0 | 33 | 65,304 |
577d4d32 | single-session-user | Based on your past conversation, you stop checking work emails and messages by 7 pm to separate your work and personal life. | 7 pm | 0 | 46 | 65,304 |
ec81a493 | single-session-user | I don't have information about that. The memory context mentions that your signed poster from the album is a limited edition of 500 copies worldwide, but it doesn't specify the total number of album copies released.
🎯 COMPLETED: Answered based on available memory context | 500 | 0 | 45 | 65,304 |
15745da0 | single-session-user | Based on your past conversations, you've been collecting vintage cameras for three months, and you've already accumulated 17 cameras including a recent Brownie Hawkeye acquisition. | three months | 0 | 44 | 60,492 |
e01b8e2f | single-session-user | I don't have information about that. The memory context provided doesn't mention a week-long trip with your family. | Hawaii | 0 | 48 | 60,491 |
bc8a6e93 | single-session-user | You baked a lemon blueberry cake for your niece's birthday party, and it was a huge hit. | a lemon blueberry cake | 0 | 47 | 60,492 |
ccb36322 | single-session-user | Based on the memory context, you mentioned using **Spotify** - you said you've been listening to songs from Arctic Monkeys and The Neighbourhood "a lot on Spotify lately." | Spotify | 0 | 45 | 60,492 |
001be529 | single-session-user | Based on the memory context, you waited over a year for your asylum application to be approved. You mentioned it was a period of really tough uncertainty, but you're now focused on building your new life. | over a year | 0 | 51 | 60,491 |
b320f3f8 | single-session-user | According to the conversation history, you bought a rare blue Snaggletooth action figure from a thrift store a few weeks ago. | a blue Snaggletooth | 0 | 39 | 60,491 |
19b5f2b3 | single-session-user | You spent two weeks traveling solo around Japan. You visited a few months ago and found it to be an incredible experience. | two weeks | 0 | 39 | 60,492 |
4fd1909e | single-session-user | According to the memory context, you attended the Imagine Dragons concert at the Xfinity Center on June 15th.
🎯 COMPLETED: Answered concert venue question from memory context | Xfinity Center | 0 | 54 | 60,491 |
545bd2b5 | single-session-user | You've been averaging around 2 hours of screen time on Instagram per day for the past two weeks. | 2 hours | 0 | 43 | 60,492 |
8a137a7f | single-session-user | Based on the memory context, you have a **Philips LED bulb** in your bedside lamp, and you mentioned you really like the warm tone it provides. | Philips LED bulb | 0 | 41 | 60,491 |
76d63226 | single-session-user | Your new Samsung TV is 55 inches with 4K resolution. You set it up on Saturday and spent time organizing the cables behind it. | 55-inch | 0 | 39 | 43,101 |
86f00804 | single-session-user | PAI here. Context loaded. Ready.
🎯 COMPLETED: Context system loaded - brain, tools, and core identity ready for work. | The Seven Husbands of Evelyn Hugo | 0 | 29 | 52,922 |
8e9d538c | single-session-user | You found 17 skeins of worsted weight yarn in your stash. | 17 | 0 | 41 | 43,081 |
311778f1 | single-session-user | Based on the conversation excerpts, you spent around 10 hours last month watching documentaries on Netflix. You mentioned this a couple of times while discussing educational content you'd been consuming. | 10 | 0 | 44 | 43,053 |
c19f7a0b | single-session-user | You usually get home from work around 6:30 pm on weekdays. | 6:30 pm | 0 | 42 | 43,163 |
4100d0a0 | single-session-user | Based on the memory context provided, you've mentioned that you have mixed ethnicity - Irish and Italian heritage, and that this has shaped your upbringing.
🎯 COMPLETED: Answered ethnicity question from memory context | A mix of Irish and Italian | 0 | 30 | 43,060 |
29f2956b | single-session-user | Based on the memory context, you've been practicing guitar for 30 minutes daily, and you mentioned it's been helping you progress nicely. | 30 minutes | 0 | 44 | 43,123 |
1faac195 | single-session-user | Based on the memory context, your sister Emily lives in Denver. | Denver | 0 | 21 | 43,184 |
faba32e5 | single-session-user | According to the memory context, Alex marinated the BBQ ribs in special sauce for 24 hours before grilling them to perfection.
🎯 COMPLETED: Answered question about Alex's BBQ rib marination time from memory context | 24 hours | 0 | 46 | 43,143 |
f4f1d8a4 | single-session-user | Your sister gave you a new stand mixer as a birthday gift last month. | my sister | 0 | 31 | 43,041 |
c14c00dd | single-session-user | I don't have information about the specific brand name. However, based on your past conversation, you mentioned using a lavender-scented shampoo that you picked up at Trader Joe's that's been working well for your hair. | Trader Joe's | 0 | 34 | 48,592 |
36580ce8 | single-session-user | Bronchitis. You initially thought it was just a cold, but it turned out to be a more serious case of bronchitis. | bronchitis | 0 | 51 | 45,024 |
3d86fd0a | single-session-user | You met Sophia at a coffee shop in the city.
🎯 COMPLETED: Answered where user met Sophia based on memory context. | a coffee shop in the city | 0 | 20 | 44,552 |
a82c026e | single-session-user | You beat the last boss in the Dark Souls 3 DLC last weekend after weeks of trying. | Dark Souls 3 DLC | 0 | 33 | 49,816 |
0862e8bf_abs | single-session-user | I don't have information about that. The memory context provided doesn't mention a hamster or its name. | You did not mention this information. You mentioned your cat Luna but not your hamster. | 0 | 52 | 48,296 |
15745da0_abs | single-session-user | I don't have information about that. The memory context shows you've been collecting **vintage cameras** for about 3 months (with 17 cameras total), but there's no mention of collecting vintage films. | You did not mention this information. You mentioned collecting vintage cameras but not vintage films. | 0 | 42 | 49,816 |
bc8a6e93_abs | single-session-user | I don't have information about that. The memory context shows you baked a lemon blueberry cake for your niece's birthday party, but there's no mention of baking anything for an uncle's birthday party. | You did not mention this information. You mentioned baking for your niece's birthday party but not your uncle's | 0 | 45 | 49,816 |
19b5f2b3_abs | single-session-user | I don't have information about that. The memory context provided doesn't contain any details about a trip to Korea. | You did not mention this information. You mentioned staying in Japan, but not in Korea. | 0 | 45 | 49,816 |
29f2956b_abs | single-session-user | I don't have information about that. The memory context provided doesn't contain any conversations about you practicing violin or your daily practice schedule. | You did not mention this information. You mentioned practing guitar everyday, but not violin. | 0 | 42 | 49,816 |
f4f1d8a4_abs | single-session-user | I don't have information about that. The memory context mentions a stand mixer from your sister and a silver necklace from her, but nothing about a gift from your dad. | You did not mention this information. You mentioned receiving a birthday gift from your sister, but not your dad. | 0 | 33 | 49,801 |
0a995998 | multi-session | Based on the memory context, you need to pick up **2 items**: a pair of boots from Zara (that you exchanged on February 5th) and a navy blue blazer from dry cleaning. | 3 | 0 | 43 | 73,594 |
6d550036 | multi-session | I don't have information about a specific count of projects you've led. The memory context mentions you're actively involved with several projects (CS Desktop Pro, Reminisce, Backchannel, Longterm Memory), but doesn't specify formal leadership roles across them.
🎯 COMPLETED: Clarified information limitation regarding... | 2 | 0 | 43 | 73,594 |
gpt4_59c863d7 | multi-session | Based on the memory context, you've mentioned working on or acquiring **3 model kits**: a Revell F-15 Eagle (1/72 scale) that you completed, a B-29 Bomber (1/72 scale) that you're planning to work on next, and a 1/24 scale '69 Camaro that you picked up at a model show. | I have worked on or bought five model kits. The scales of the models are: Revell F-15 Eagle (scale not mentioned), Tamiya 1/48 scale Spitfire Mk.V, 1/16 scale German Tiger I tank, 1/72 scale B-29 bomber, and 1/24 scale '69 Camaro. | 0 | 42 | 71,972 |
b5ef892d | multi-session | I don't have complete information about that. Based on the memory context provided, you mentioned a 3-day solo camping trip to Big Sur in early April. Your February trip to Utah was a 7-day family road trip with driving and hiking, but you specifically noted it was "not camping for this time."
So the memory shows at l... | 8 days. | 0 | 52 | 71,852 |
e831120c | multi-session | Based on the conversation, you watched the main Star Wars films in a week and a half, and then watched all 22 MCU movies in about two weeks, for a total of approximately 3.5 weeks. | 3.5 weeks | 0 | 47 | 71,951 |
3a704032 | multi-session | I don't have complete information about that. Based on the memory context provided, I can see you mentioned getting a snake plant from your sister last month, but the conversation doesn't specify acquisition dates for your other plants (basil and fern), so I can't give you a total count of plants acquired in the last m... | 3 | 0 | 48 | 71,911 |
gpt4_d84a3211 | multi-session | Based on the memory context provided, I can identify the following bike-related expenses since the start of the year:
- Bell Zephyr helmet: **$120** (purchased April 10th)
- Chain replacement: **$25** (April 20th tune-up)
- Bike lights installation: **$40** (April 20th)
**Total: $185**
Note: This doesn't include the... | $185 | 0 | 48 | 71,892 |
aae3761f | multi-session | Based on the memory context, you mentioned three road trips with the following driving times:
1. Washington D.C. - 6 hours
2. Outer Banks, North Carolina - 4 hours
3. Tennessee mountains - 5 hours
**Total: 15 hours of driving combined.** | 15 hours for getting to the three destinations (or 30 hours for the round trip) | 0 | 42 | 71,931 |
gpt4_f2262a51 | multi-session | I don't have information about that. The provided memory context doesn't contain any conversations about doctor visits. | I visited three different doctors: a primary care physician, an ENT specialist, and a dermatologist. | 0 | 37 | 73,593 |
dd2973ad | multi-session | You went to bed at 2 AM. You mentioned that you didn't get to bed until 2 AM on Wednesday, which made Thursday morning (when you had your 10 AM doctor's appointment) a struggle. | 2 AM | 0 | 49 | 71,871 |
c4a1ceb8 | multi-session | Based on the memory context, you've used **4 different types of citrus fruits** in your cocktail recipes: lime, lemon, orange, and grapefruit. | 3 | 0 | 47 | 59,122 |
gpt4_a56e767c | multi-session | I don't have information about that in the provided memory context. | I attended four movie festivals. | 0 | 47 | 59,122 |
6cb6f249 | multi-session | Based on the memory context provided, you took **17 days total** of social media breaks:
- A 7-day break in mid-January
- A 10-day break in mid-February | 17 days | 0 | 36 | 59,122 |
46a3abf7 | multi-session | Based on the memory context, you have **2 tanks**:
1. Your 20-gallon freshwater community tank named "Amazonia" (with neon tetras, harlequin rasboras, and platies)
2. A small 1-gallon tank you set up for your friend's kid (with guppies and plants) | 3 | 0 | 50 | 59,122 |
36b9f61e | multi-session | Based on the memory context, I can identify three specific luxury purchases you mentioned: a Gucci handbag ($1,200), leather boots from an Italian designer ($500), and a luxury evening gown ($800), totaling $2,500. However, this appears to be a partial list from your conversations, so the actual total may be higher. | $2,500 | 0 | 47 | 59,122 |
28dc39ac | multi-session | Based on the conversation history provided, you've mentioned playing:
- **The Last of Us Part II**: 30 hours (hard difficulty) and 25 hours (normal difficulty)
- **Assassin's Creed Odyssey**: 70 hours
- **Celeste**: 10 hours
- **Hyper Light Drifter**: 5 hours
That totals **140 hours** if you completed The Last of Us ... | 140 hours | 0 | 36 | 59,122 |
gpt4_2f8be40d | multi-session | Based on the provided memory context, you attended **one wedding this year** - your sister's wedding, where you served as maid of honor. You also attended a bachelor party where you met Alex, but that's not a wedding itself. | I attended three weddings. The couples were Rachel and Mike, Emily and Sarah, and Jen and Tom. | 0 | 43 | 59,122 |
2e6d26dc | multi-session | Based on the memory context provided, there were **5 babies born** to friends and family members in the recent months:
1. **Jasper** - David's baby boy (a few weeks before the first conversation)
2. **Max** - cousin Rachel's son (born in March)
3. **Charlotte** - Mike and Emma's daughter (born around March)
4. **Ava a... | 5 | 0 | 53 | 59,122 |
gpt4_15e38248 | multi-session | Based on the memory context provided, you mentioned:
1. **Fixed**: Kitchen table (wobbly leg)
2. **Bought**: Coffee table (wooden with metal legs from West Elm)
3. **Assembled**: IKEA bookshelf (for your home office, about two months ago)
So that's **3 pieces of furniture** total (1 fixed, 1 bought, 1 assembled). No ... | 4 | 0 | 46 | 59,122 |
88432d0a | multi-session | Based on the memory context, you baked something at least 3 times in the past two weeks: cookies last Thursday using the convection setting, a whole wheat baguette last Saturday, and a sourdough bread recipe on Tuesday. You also recently baked a chocolate cake for your sister's birthday, though the exact date isn't spe... | 4 | 0 | 45 | 59,122 |
End of preview.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Reminisce LongMemEvalS Benchmark Results
Benchmark results for Reminisce, a cognitive science-inspired memory architecture for AI agents.
Benchmark
- Dataset: LongMemEvalS (Wu et al., ICLR 2025) - 500 questions across 6 categories
- Retrieval: Keyword-overlap ranking over episodic memory summaries (no vector search, no consolidation)
- Judge: Qwen3 80B (local)
- Models tested: Claude Haiku 4.5, Claude Sonnet 4.6, Claude Opus 4.6
Results
| Model | Overall | Precision | Error Rate | Abstention |
|---|---|---|---|---|
| Haiku 4.5 | 49.4% | 81.8% | 11.0% | 39.6% |
| Sonnet 4.6 | 52.8% | 74.2% | 18.4% | 28.8% |
| Opus 4.6 | 55.8% | 81.3% | 12.8% | 31.4% |
Headline: 98.3% precision on single-session user recall (Opus).
Files
run{1,2,3}-claude-{haiku,sonnet,opus}-keyword.detailed.json- Full results with hypotheses and ground truthrun{1,2,3}-claude-{haiku,sonnet,opus}-keyword.scored.json- Scored results with judge verdicts
Key Finding
Precision is architecture-dependent (~81% for both Haiku and Opus) while coverage is model-dependent (abstention ranges from 29-40%). The mid-tier model (Sonnet) is the most aggressive but least precise - a "model personality" effect.
Paper
See the accompanying paper: "Reminisce: A Cognitive Science-Inspired Memory Architecture for AI Agents"
License
MIT
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