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
| { | |
| "description": "Generation settings for the query-variation TSV files under msmarco-dev/, trec-dl-2019/, and trec-dl-2020/, released alongside 'Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval' (SIGIR 2026, DOI: 10.1145/3805712.3808567).", | |
| "splits": { | |
| "msmarco-dev": {"num_queries": 6980, "source": "MS MARCO Passage Ranking Dev queries"}, | |
| "trec-dl-2019": {"num_queries": 43, "source": "TREC Deep Learning 2019 passage-ranking topics"}, | |
| "trec-dl-2020": {"num_queries": 54, "source": "TREC Deep Learning 2020 passage-ranking topics"} | |
| }, | |
| "perturbation_types": [ | |
| {"name": "misspelling", "seeded": true, "description": "Character-level misspelling injection."}, | |
| {"name": "reordering", "seeded": true, "description": "Word-order shuffling."}, | |
| {"name": "synonym", "seeded": true, "description": "Adversarial synonym replacement."}, | |
| {"name": "paraphrase", "seeded": true, "description": "Back-translation and seq2seq paraphrasing."}, | |
| {"name": "naturality", "seeded": false, "description": "Deterministic style-normalization (stop-word removal); identical output regardless of seed."} | |
| ], | |
| "file_format": { | |
| "extension": "tsv", | |
| "columns": ["qid", "original_query", "perturbed_query", "perturbation", "seed"], | |
| "seeded_attacks": "one row per (qid, seed) pair, five seeds stacked in a single file", | |
| "naturality": "one row per qid; seed column is the literal string 'deterministic'" | |
| }, | |
| "generation_code": "robustness/query_variations (penha transformations) in the Lost-in-Decoding repository: https://github.com/kidist-amde/lost-in-decoding/tree/main/robustness/query_variations", | |
| "provenance": "Derived evaluation artifacts created from the official MS MARCO Dev queries and official TREC Deep Learning 2019/2020 topics for the Lost in Decoding study.", | |
| "source_paper": "Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval (DOI: 10.1145/3805712.3808567, arXiv:2604.23396)", | |
| "source_repository": "https://github.com/kidist-amde/lost-in-decoding" | |
| } | |