Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/harbor/harbor.py", line 171, in _split_generators
raise DataFilesNotFoundError("No task.toml or instruction.md files found")
datasets.exceptions.DataFilesNotFoundError: No task.toml or instruction.md files found
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
binary-reasoning-v1
Verified reverse-engineering tasks over real production binaries — an RL / eval environment pack where every answer is derived from the artifact itself and machine-checked.
- 10,251 items · 10 families · 7 ISAs (x86-64, i686, AArch64, ARM32, RISC-V, MIPS o32/n64, PPC64LE)
- Sources: 649 distinct third-party file names referenced in shipped provenance (system libs incl. libcrypto/zstd/sqlite3/libxml2, Mesa DRI drivers, QEMU device models, systemd internals), Debian production cross-toolchain glibc, Android/Termux production aarch64 libs, curated Windows PEs, labeled cross-compiles
- Provenance per item: binary name and sha256_16 on every item; function address/size and architecture where applicable
- Verification: automated re-verification through our in-house analysis pipeline (answers re-verified against the binaries); 10,172
deterministic items score 1.0 on gold / 0.0 on abstention; automated answer-leak scan found 0/10,251 hits; all tasks load
against the real
verifiersv1 framework; 29 agentic challenges ship Harbor-format task packages, built + scored in real Docker containers with reward-chain gold and wrong-answer tests passing; each binary was also checked with 24 single-character mutations that scored zero - Baseline: a small local open-weight model mini-eval scored
5/23(22%) on selected static deterministic items; seeEVAL_RESULTS.mdfor conditions. Frontier reference: Claude Opus 5.5 with shell and file-read tools solved all 29 public agentic environments (145/145 attempts, 2026-10-29; non-isolated upper bound, see BENCHMARK-REPORT.md), so the public tier is warm-up level. Private task families are calibrated across several models on fresh, never-published instances; results are shared privately with prospective buyers.
Contents of this repo (free sample)
| file | what |
|---|---|
DATASHEET.md |
full composition table, guarantees, known limits, positioning vs existing work |
sample_free.jsonl |
9 items — one per family |
EVAL_RESULTS.md |
baseline eval methodology + results (incl. a frontier reference: Opus 5.5 single-shot ~58% on ID items) |
EVAL_RESULTS-passk.md |
full 29-env agentic pass@5 result for Claude Opus 5.5 with conditions and caveats |
BENCHMARK-REPORT.md |
benchmark report for the public agentic environments, including intervals, method notes, and known limits |
VERIFICATION-DOSSIER-PUBLIC.md |
public proof summary with measured checks and known caveats |
verification_kit/ |
sample-level grader, wrong-answer, key-sensitivity, and leak-check scripts; see verification_kit/README.md for limitations |
environment/src/binary_reasoning_v1/grading.py |
minimal grader module used by the verification kit. The HF free sample here is 9 items; the Prime Intellect environment package exposes a separate 100-item open sample. |
harbor_pilot_29.zip |
all 29 agentic Harbor task packages (task.toml + instruction + Dockerfile + verifier + solution scripts and solution explanations), ready for harbor run or a free HUD import (direct download) |
Also live on the Prime Intellect Environments Hub: s3rl4/binary-reasoning-v1
(prime env install s3rl4/binary-reasoning-v1).
The full pack (10,251 items + runnable verifiers v1 environment + Harbor packages + agentic binaries & sources) lives in the gated companion repo: S3RL4/binary-reasoning-v1-full — request access; access is reviewed on request. Commercial licensing and custom taskset builds: samueljanttila@gmail.com. Individual researchers: a personal, non-commercial licence is available for $199 on request. Companies and labs: see the DataVendor listings or email us. Privacy: PRIVACY.md
License
Task annotations, graders and packaging © RE-Lab, all rights reserved pending a commercial licence; third-party binaries remain under their own licences (provenance per item). Research evaluation use is granted for the free sample.
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