Transformers
PyTorch
t5
generative-retrieval
information-retrieval
msmarco
robustness
reproducibility
text-generation-inference
Instructions to use kiyam/lost-in-decoding-pag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kiyam/lost-in-decoding-pag with Transformers:
# Load model directly from transformers import AutoTokenizer, T5ForLexicalSemanticGeneration tokenizer = AutoTokenizer.from_pretrained("kiyam/lost-in-decoding-pag") model = T5ForLexicalSemanticGeneration.from_pretrained("kiyam/lost-in-decoding-pag", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| # Lost in Decoding — Evaluation Artifacts | |
| **Provenance:** derived evaluation artifacts created from the official MS | |
| MARCO Dev queries and official TREC Deep Learning 2019/2020 topics, for this | |
| paper (*Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior | |
| in Generative Retrieval*, SIGIR 2026, | |
| [DOI: 10.1145/3805712.3808567](https://doi.org/10.1145/3805712.3808567) · | |
| [arXiv:2604.23396](https://arxiv.org/abs/2604.23396)), not part of the | |
| original PAG release. | |
| The generation code and metadata here are Apache-2.0-licensed. The perturbed | |
| query **text** is a derived artifact of the original MS MARCO / TREC-DL query | |
| text and remains subject to the same provenance constraints as that source | |
| text — see [`../LICENSE.md`](../LICENSE.md). | |
| ## `msmarco-dev/`, `trec-dl-2019/`, `trec-dl-2020/` | |
| Query variations (misspelling, reordering, synonym replacement, paraphrasing, | |
| naturality normalization) used for the RQ2 robustness evaluation, one | |
| directory per evaluation split: | |
| | Directory | Split | Queries | | |
| |---|---|---| | |
| | `msmarco-dev/` | MS MARCO Passage Ranking Dev | 6,980 | | |
| | `trec-dl-2019/` | TREC Deep Learning 2019 passage-ranking topics | 43 | | |
| | `trec-dl-2020/` | TREC Deep Learning 2020 passage-ranking topics | 54 | | |
| Each directory contains one TSV file per perturbation type: | |
| `misspelling.tsv`, `reordering.tsv`, `synonym.tsv`, `paraphrase.tsv`, | |
| `naturality.tsv`. | |
| **Columns:** `qid`, `original_query`, `perturbed_query`, `perturbation`, `seed` | |
| ```text | |
| qid original_query perturbed_query perturbation seed | |
| 1037798 who is robert gray who is robrt gray misspelling 42 | |
| ``` | |
| - **Seeded perturbations** (`misspelling`, `reordering`, `synonym`, | |
| `paraphrase`): five seeds — `1999`, `5`, `27`, `2016`, `2026` — stacked as | |
| separate rows per `qid` within the same file. | |
| - **`naturality`:** a deterministic style-normalization rule rather than a | |
| randomized perturbation, so it produces identical output for every seed. | |
| Represented as a single row per `qid` with `seed=deterministic` rather than | |
| five duplicate rows. | |
| `msmarco-dev/original_qids.txt` lists the 6,980 Dev query IDs covered by | |
| these files (a subset of the full MS MARCO Dev qrel set). | |
| Implemented in | |
| [`robustness/query_variations/penha/`](https://github.com/kidist-amde/lost-in-decoding/tree/main/robustness/query_variations/penha) | |
| in the code repository. | |
| ## `metadata/` | |
| - `generation_config.json`: perturbation types, split sizes, file format, and provenance. | |
| - `seeds.json`: seed values and which perturbations use them. | |
| ## `data_download/` | |
| The original MS MARCO passage collection, MS MARCO Dev queries/qrels, and | |
| TREC-DL 2019/2020 topics/qrels are **not** redistributed in this repository. | |
| Scripts to fetch them directly from their official sources (Microsoft, | |
| NIST) are provided at the repository root: | |
| ```bash | |
| git clone https://huggingface.co/kiyam/lost-in-decoding-pag | |
| cd lost-in-decoding-pag | |
| bash data_download/prepare_evaluation_data.sh | |
| ``` | |
| See [`../data_download/`](../data_download/) for individual per-dataset | |
| scripts and checksums. | |
| ## Citation | |
| If you use these artifacts, please cite: | |
| ```bibtex | |
| @inproceedings{mekonnen2026lost, | |
| title = {Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval}, | |
| author = {Mekonnen, Kidist Amde and Li, Yongkang and Tang, Yubao and Lupart, Simon and de Rijke, Maarten}, | |
| booktitle = {Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval}, | |
| pages = {2994--3005}, | |
| year = {2026}, | |
| doi = {10.1145/3805712.3808567} | |
| } | |
| ``` | |