MemoryTax
Collection
7 items • Updated
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
question_id: string
sample_id: string
category: string
verdict: int64
raw: string
gold_used: list<item: string>
child 0, item: string
prompt: string
judge_prompt_version: string
cost_by_operations: struct<retrieval: struct<llm_calls: int64, prompt_tokens: int64, completion_tokens: int64, embed_cal (... 474 chars omitted)
child 0, retrieval: struct<llm_calls: int64, prompt_tokens: int64, completion_tokens: int64, embed_calls: int64, embed_c (... 86 chars omitted)
child 0, llm_calls: int64
child 1, prompt_tokens: int64
child 2, completion_tokens: int64
child 3, embed_calls: int64
child 4, embed_chars: int64
child 5, rerank_calls: int64
child 6, rerank_pairs: int64
child 7, wall_s: double
child 8, reason: string
child 1, qa_answer: struct<llm_calls: int64, prompt_tokens: int64, completion_tokens: int64, embed_calls: int64, embed_c (... 70 chars omitted)
child 0, llm_calls: int64
child 1, prompt_tokens: int64
child 2, completion_tokens: int64
child 3, embed_calls: int64
child 4, embed_chars: int64
child 5, rerank_calls: int64
child 6, rerank_pairs: int64
child 7, wall_s: double
child 2, construction: struct<llm_calls: int64, prompt_tokens: int64, completion_tokens: int64, embed_calls: int64, embed_c (... 70 chars omitted)
child 0, llm_calls: int64
child 1, prompt_tokens: int64
child 2, completion_tokens: int64
child 3, embed_calls: int64
child 4, embed_chars: int64
child 5, rerank_calls: int64
child 6, rerank_pairs: int64
child 7, wall_s: double
system: string
n_questions: int64
bench: string
n_chunks: int64
sample_idx: int64
to
{'sample_id': Value('string'), 'sample_idx': Value('int64'), 'system': Value('string'), 'bench': Value('string'), 'n_questions': Value('int64'), 'n_chunks': Value('int64'), 'cost_by_operations': {'retrieval': {'llm_calls': Value('int64'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'embed_calls': Value('int64'), 'embed_chars': Value('int64'), 'rerank_calls': Value('int64'), 'rerank_pairs': Value('int64'), 'wall_s': Value('float64'), 'reason': Value('string')}, 'qa_answer': {'llm_calls': Value('int64'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'embed_calls': Value('int64'), 'embed_chars': Value('int64'), 'rerank_calls': Value('int64'), 'rerank_pairs': Value('int64'), 'wall_s': Value('float64')}, 'construction': {'llm_calls': Value('int64'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'embed_calls': Value('int64'), 'embed_chars': Value('int64'), 'rerank_calls': Value('int64'), 'rerank_pairs': Value('int64'), 'wall_s': Value('float64')}}}
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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
question_id: string
sample_id: string
category: string
verdict: int64
raw: string
gold_used: list<item: string>
child 0, item: string
prompt: string
judge_prompt_version: string
cost_by_operations: struct<retrieval: struct<llm_calls: int64, prompt_tokens: int64, completion_tokens: int64, embed_cal (... 474 chars omitted)
child 0, retrieval: struct<llm_calls: int64, prompt_tokens: int64, completion_tokens: int64, embed_calls: int64, embed_c (... 86 chars omitted)
child 0, llm_calls: int64
child 1, prompt_tokens: int64
child 2, completion_tokens: int64
child 3, embed_calls: int64
child 4, embed_chars: int64
child 5, rerank_calls: int64
child 6, rerank_pairs: int64
child 7, wall_s: double
child 8, reason: string
child 1, qa_answer: struct<llm_calls: int64, prompt_tokens: int64, completion_tokens: int64, embed_calls: int64, embed_c (... 70 chars omitted)
child 0, llm_calls: int64
child 1, prompt_tokens: int64
child 2, completion_tokens: int64
child 3, embed_calls: int64
child 4, embed_chars: int64
child 5, rerank_calls: int64
child 6, rerank_pairs: int64
child 7, wall_s: double
child 2, construction: struct<llm_calls: int64, prompt_tokens: int64, completion_tokens: int64, embed_calls: int64, embed_c (... 70 chars omitted)
child 0, llm_calls: int64
child 1, prompt_tokens: int64
child 2, completion_tokens: int64
child 3, embed_calls: int64
child 4, embed_chars: int64
child 5, rerank_calls: int64
child 6, rerank_pairs: int64
child 7, wall_s: double
system: string
n_questions: int64
bench: string
n_chunks: int64
sample_idx: int64
to
{'sample_id': Value('string'), 'sample_idx': Value('int64'), 'system': Value('string'), 'bench': Value('string'), 'n_questions': Value('int64'), 'n_chunks': Value('int64'), 'cost_by_operations': {'retrieval': {'llm_calls': Value('int64'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'embed_calls': Value('int64'), 'embed_chars': Value('int64'), 'rerank_calls': Value('int64'), 'rerank_pairs': Value('int64'), 'wall_s': Value('float64'), 'reason': Value('string')}, 'qa_answer': {'llm_calls': Value('int64'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'embed_calls': Value('int64'), 'embed_chars': Value('int64'), 'rerank_calls': Value('int64'), 'rerank_pairs': Value('int64'), 'wall_s': Value('float64')}, 'construction': {'llm_calls': Value('int64'), 'prompt_tokens': Value('int64'), 'completion_tokens': Value('int64'), 'embed_calls': Value('int64'), 'embed_chars': Value('int64'), 'rerank_calls': Value('int64'), 'rerank_pairs': Value('int64'), 'wall_s': Value('float64')}}}
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.
MemoryTax-Res-Qwen3-5-4B
Structure
MemoryTax-Res-Qwen3-5-4B/
├── res_{system}_{bench}_4b/ # one memory system on one benchmark
│ ├── qa_res/ # per-question answers (with retrieved memory ids)
│ ├── judge_res/judge.jsonl # per-question judge verdicts
│ ├── cost/ # per-corpus token / call cost, by memory operation
│ └── memories.tar.gz # memory store built by the system
└── naive_baselines/
└── res_{baseline}_{bench}_4b/ # same layout
{system} amem, memoryos, simplemem, etc.
{baseline} no_context, long_ctx, oracle, rag_hybrid_1rd, rag_hybrid_2rd
{bench} longmemeval_s, persona_mem_v2_128k, mint_eval
Citation
@misc{he2026memorytaxdissectingnet,
title={Memory Tax: Dissecting the Net Value of Agent Memory},
author={Xuan He and Sining Zhoubian and Ruozhen Yang and Yuhao Wen and Zhineng Wang and Yuyang Hu and Ke Yang and Yuyu Zhang and Ping Nie and Jiawei Han and ChengXiang Zhai},
year={2026},
eprint={2610.34073},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2610.34073},
}
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