| --- |
| license: apache-2.0 |
| language: |
| - en |
| pretty_name: XMemTransfer Results |
| size_categories: |
| - n<1K |
| tags: |
| - xmemtransfer |
| - external-memory |
| - experimental-results |
| - arxiv:2608.17050 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/release_artifacts.jsonl |
| --- |
| |
| # XMemTransfer Results |
|
|
| This dataset is the machine-readable release manifest and result summary for |
| **Cross-Model Memory Transfer via Target-Side Reader Adaptation**. Each row |
| describes one released XMemTransfer source-memory or target-adaptor repository. |
| When a released artifact has a `results.json`, the row also includes its |
| validation-perplexity and gate-statistic summary. |
|
|
| - Paper: [arXiv:2608.17050](https://arxiv.org/abs/2608.17050) |
| - Project page: [XMemTransfer](https://olaresearch.github.io/XMemTransfer) |
| - Code: [OLAResearch/XMemTransfer](https://github.com/OLAResearch/XMemTransfer) |
| - Models: [XMemTransfer collection](https://huggingface.co/collections/OLAResearchX/xmemtransfer-6a4a0c34ef03a51c927d3389) |
|
|
| ## Dataset contents |
|
|
| The `train` split contains 20 release-manifest rows. Twelve rows include result |
| summaries copied from the corresponding released model artifacts. Null metric |
| fields mean that the artifact is a source memory without a target-adaptor |
| result summary. |
|
|
| Important fields: |
|
|
| - `artifact_id`, `artifact_kind`, and `hf_repo`: released artifact identity. |
| - `base_model` and `source_memory_repo`: model provenance. |
| - `token_budget`: target-side fitting budget for adaptors, or source-memory |
| training budget for source artifacts. |
| - `best_val_ppl`, training-step fields, and `gate_*`: values recorded by the |
| released experiment's `results.json`. |
|
|
| ## Scope and limitations |
|
|
| This is experiment and release metadata, not a language-model training corpus |
| or a benchmark. It does **not** redistribute WikiText, evaluation examples, or |
| model weights. Metrics are run summaries and should be interpreted with the |
| experimental setup in the paper and repository. Local filesystem paths in the |
| original run outputs are deliberately excluded. |
|
|
| ## Datasets used by the paper |
|
|
| The experiments use the following public corpora and evaluation datasets. They |
| are listed here as references only; this release does not mirror their data: |
|
|
| - **Training and intrinsic evaluation:** |
| [WikiText-103](https://huggingface.co/datasets/Salesforce/wikitext) |
| (`wikitext-103-raw-v1`), |
| [Wikipedia-2021](https://huggingface.co/datasets/Rubin-Wei/enwiki-dec2021-preprocessed-mistral) |
| (December 2021 English Wikipedia, Mistral-tokenizer preprocessed release), |
| [LAMBADA](https://huggingface.co/datasets/EleutherAI/lambada_openai), |
| [C4](https://huggingface.co/datasets/allenai/c4) (`en`), and |
| [FineWeb-Edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu) |
| (`sample-10BT`). |
| - **Open-domain QA and transfer evaluation:** |
| [Natural Questions Open (NQ)](https://huggingface.co/datasets/google-research-datasets/nq_open), |
| [WebQuestions (WebQA)](https://huggingface.co/datasets/Stanford/web_questions), |
| [TriviaQA](https://huggingface.co/datasets/mandarjoshi/trivia_qa) |
| (the `rc.nocontext` RC no-context subset; validation split), |
| [TruthfulQA](https://huggingface.co/datasets/truthfulqa/truthful_qa) |
| (`multiple_choice`), and |
| [HotpotQA](https://huggingface.co/datasets/hotpotqa/hotpot_qa) (`distractor`). |
| - **Multiple-choice and classification evaluation:** |
| [HellaSwag](https://huggingface.co/datasets/Rowan/hellaswag), |
| [PIQA](https://huggingface.co/datasets/ybisk/piqa), |
| [ARC](https://huggingface.co/datasets/allenai/ai2_arc) (Easy and Challenge), |
| [Winogrande](https://huggingface.co/datasets/allenai/winogrande) |
| (`winogrande_xl`), [BoolQ](https://huggingface.co/datasets/google/boolq), |
| [SuperGLUE RTE](https://huggingface.co/datasets/aps/super_glue) (`rte`), |
| [OpenBookQA](https://huggingface.co/datasets/allenai/openbookqa), |
| [SciQ](https://huggingface.co/datasets/allenai/sciq), and |
| [RACE](https://huggingface.co/datasets/ehovy/race) (`high`). |
|
|
| See the paper's dataset and evaluation protocol for the exact splits and |
| preprocessing. Wikipedia-2021 is the factual/encyclopedic corpus used for the |
| QA memory-contribution experiments. |
|
|
| `OLAResearchX/XMemTransfer-Results` is a release-results and metadata index. |
| Its `arxiv:2608.17050` tag is what makes it appear under **Datasets citing this |
| paper** on the paper page; that Hugging Face panel lists repositories that |
| declare a paper link, rather than automatically listing every external source |
| dataset referenced in this card. |
|
|
| ## License |
|
|
| Apache-2.0, matching the XMemTransfer code release. |
|
|
