{
  "id": "2506.06105",
  "title": "Text-to-LoRA: Instant Transformer Adaption",
  "authors": "Rujikorn Charakorn, Edoardo Cetin, Yujin Tang, Robert Tjarko Lange",
  "first_public": "2025-06-06",
  "first_public_source": "https://arxiv.org/abs/2506.06105",
  "arxiv_first_submission": "2025-06-06",
  "date_label": "arXiv v1",
  "arxiv": "2506.06105",
  "paper_url": "https://arxiv.org/abs/2506.06105",
  "venue": "ICML 2025",
  "lens": [
    "generated-adapters"
  ],
  "related_terms": [
    "Text-to-LoRA",
    "T2L",
    "task description",
    "adapter generation"
  ],
  "summary": "Uses a hypernetwork to generate LoRA adapters from task descriptions.",
  "contribution": "Trains hypernetworks to reconstruct existing adapters or learn from supervised task data. Tests adapter compression and generation for unseen tasks.",
  "limitations": "Reconstruction-trained T2L underperforms the supervised variant on unseen tasks.",
  "program_form": "Generated LoRA matrices.",
  "conditioning": "A natural-language task description.",
  "execution": "A base transformer performs the task with the generated LoRA.",
  "relationship": "PAW cites Text-to-LoRA as prior work on generating adapters. PAW develops fuzzy-function programming, FuzzyBench, and an interface for reusable neural programs.",
  "relationship_source": "https://arxiv.org/html/2607.02512v1#S10",
  "provenance": "arXiv record and paper.",
  "author_names": [
    "Rujikorn Charakorn",
    "Edoardo Cetin",
    "Yujin Tang",
    "Robert Tjarko Lange"
  ],
  "record_url": "https://programasweights.com/reading-list/papers/2506.06105/",
  "legacy_record_url": "https://programasweights.com/reading-list/papers/#paper-2506-06105",
  "citation_date": "2025-06-06",
  "json_url": "https://programasweights.com/reading-list/papers/2506.06105/record.json",
  "markdown_url": "https://programasweights.com/reading-list/papers/2506.06105/index.md",
  "bibtex_url": "https://programasweights.com/reading-list/papers/2506.06105/citation.bib",
  "csl_url": "https://programasweights.com/reading-list/papers/2506.06105/citation.csl.json",
  "publication": {
    "title": "Text-to-LoRA: Instant Transformer Adaption",
    "author_names": [
      "Rujikorn Charakorn",
      "Edoardo Cetin",
      "Yujin Tang",
      "Robert Tjarko Lange"
    ],
    "year": 2025,
    "type": "paper-conference",
    "container_title": "Proceedings of the 42nd International Conference on Machine Learning",
    "url": "https://proceedings.mlr.press/v267/charakorn25a.html",
    "source_url": "https://proceedings.mlr.press/v267/charakorn25a.html",
    "verified_at": "2026-10-19",
    "volume": "267",
    "publisher": "PMLR",
    "pages": "7485-7514"
  },
  "publication_bibtex_url": "https://programasweights.com/reading-list/papers/2506.06105/publication.bib",
  "publication_csl_url": "https://programasweights.com/reading-list/papers/2506.06105/publication.csl.json",
  "method_comparisons": [
    {
      "title": "From generated adapters to reusable functions",
      "text": "Hypter, HINT, HyperTuning, and Text-to-LoRA generate adaptations from descriptions or examples. PAW uses generated parameters as part of a program that can be saved, called from ordinary code, and reused by a fixed interpreter.",
      "source_ids": [
        "2101.00420",
        "2212.10315",
        "2211.12485",
        "2506.06105",
        "2607.02512"
      ],
      "source_urls": [
        "https://arxiv.org/html/2607.02512v1#S10",
        "https://proceedings.mlr.press/v267/charakorn25a.html"
      ],
      "source_labels": [
        "PAW related work",
        "Text-to-LoRA paper"
      ],
      "topic_id": "generated-adapters",
      "topic_label": "Generated weights and adapters",
      "topic_url": "https://programasweights.com/reading-list/guides/compilation/#generated-adapters"
    }
  ]
}