datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
causal-internalization-physical-law
IOO — Conservation-Slip Signatures on Hyper-Graph Fiber Bundles
Verified results bundle for the working manuscript "Machine Intelligence
for Physical Systems: Conservation-Slip Signatures on Hyper-Graph Fiber
Bundles — From Simulated Aircraft to Satellite and Robot Telemetry"
(Sehaj Randhir Singh, NYU ECE).
This dataset hosts the machine-readable verification artifacts of the IOO
(Index of Operators / Index of Operations) framework: one JSON per
experiment, each produced and… See the full description on the dataset page: https://huggingface.co/datasets/Sejibeji/causal-internalization-physical-law.internalization
Internalization as an Operation — Spine-Extraction Campaign
Complete, reproducible campaign data for a pre-registered validation that
failed at its first gate. Two machine operators from different model families
independently extracted typed dependency graphs from five argumentative
documents under agreement thresholds fixed before any data collection.
Edge-level agreement fell below the declared threshold on every document, and
the operators diverged on which nodes exist before… See the full description on the dataset page: https://huggingface.co/datasets/spectralbranding/internalization.eh-pstruct-internalization-seed-robustness
pstruct-internalization-seed-robustness -- aggregate exhaust
Aggregate-only: every file committed under this experiment's analysis-committed/ tree (dose-response tables, direction fits, gate AUROCs, manifests, and any other analysis artifact), copied byte-for-byte. No source question text, aliases, or per-row generation text -- analysis-committed/ never carries those.
HF repo: professorsynapse/eh-pstruct-internalization-seed-robustness
Provenance
Experiment:… See the full description on the dataset page: https://huggingface.co/datasets/professorsynapse/eh-pstruct-internalization-seed-robustness.benchmark
continual-internalization/benchmark
Aggregated benchmark across three continual-internalization settings:
world-news — Polymarket-spike-anchored news articles (Feb–Mar 2026), post-cutoff.
code-changelogs — new public Python APIs introduced in stable releases of NumPy / pandas / Polars / PyTorch / SciPy.
personalization — PersonaMem-v2 (static, K=1) + HorizonBench (streaming, K=4) persona conversations.
Splits
evaluation
Eval questions only. Schema:… See the full description on the dataset page: https://huggingface.co/datasets/continual-internalization/benchmark.changelogs-agentic-rag-3docs-generationscontinual-internalization
continual-internalization/benchmark
Aggregated benchmark across three continual-internalization settings:
world-news — Polymarket-spike-anchored news articles (Feb–Mar 2026), post-cutoff.
code-changelogs — new public Python APIs introduced in stable releases of NumPy / pandas / Polars / PyTorch / SciPy.
personalization — PersonaMem-v2 (static, K=1) + HorizonBench (streaming, K=4) persona conversations.
Splits
evaluation
Eval questions only. Schema:… See the full description on the dataset page: https://huggingface.co/datasets/anon-neurips-2026-v100/continual-internalization.changelogs-agentic-rag-10docs-generationspersonalization-agentic-rag-10docs-generationsclog-eval-generations
clog-eval-generations
Unified eval generations from the continual-internalization / code-changelog benchmark suite. Every row is one model trial on one (mode, library, question) cell.
390,800 rows • 83 eval models • 4 modes (DA, CR, RR, IR)
8 trials per cell • sampling: T=0.7, top_p=0.95, top_k=20
Reconstructed prompts (prompt_system / prompt_user) are included so you can see the chat template used. Code snippets and library corpora are stubbed (e.g. <<CODE SNIPPET MASKED>>) to… See the full description on the dataset page: https://huggingface.co/datasets/continual-internalization/clog-eval-generations.personalization-agentic-rag-5docs-generationschangelogs-agentic-rag-5docs-generationsllm_internalizationpersonalization-agentic-rag-3docs-generations