{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/generator-a-long-context-generative-genomic","title":"GENERator: A Long-Context Generative Genomic Foundation Model","arxiv_id":"2502.07272","date":"2025-02-11","proceeding":null,"authors":["Wei Wu","Qiuyi Li","Mingyang Li","Kun fu","Fuli Feng","Jieping Ye","Hui Xiong","Zheng Wang"],"abstract":"Advancements in DNA sequencing technologies have significantly improved our ability to decode genomic sequences. However, the prediction and interpretation of these sequences remain challenging due to the intricate nature of genetic material. Large language models (LLMs) have introduced new opportunities for biological sequence analysis. Recent developments in genomic language models have underscored the potential of LLMs in deciphering DNA sequences. Nonetheless, existing models often face limitations in robustness and application scope, primarily due to constraints in model structure and training data scale. To address these limitations, we present GENERator, a generative genomic foundation model featuring a context length of 98k base pairs (bp) and 1.2B parameters. Trained on an expansive dataset comprising 386B bp of eukaryotic DNA, the GENERator demonstrates state-of-the-art performance across both established and newly proposed benchmarks. The model adheres to the central dogma of molecular biology, accurately generating protein-coding sequences that translate into proteins structurally analogous to known families. It also shows significant promise in sequence optimization, particularly through the prompt-responsive generation of enhancer sequences with specific activity profiles. These capabilities position the GENERator as a pivotal tool for genomic research and biotechnological advancement, enhancing our ability to interpret and predict complex biological systems and enabling precise genomic interventions. Implementation details and supplementary resources are available at https://github.com/GenerTeam/GENERator.","url_abs":"https://arxiv.org/abs/2502.07272v3","url_pdf":"https://arxiv.org/pdf/2502.07272v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"generator-a-long-context-generative-genomic","repo_url":"https://github.com/generteam/generator","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"model","task_name":"model"}],"methods":[{"method_slug":"base","method_name":"BASE"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2502.07272","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2502.07272"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/generteam/generator","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":8},"by_repo_kind":{"official":{"samples":8,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"bd38aef5ac2339e7","entry":"calculate_accuracy","repo":"generteam/generator","repo_kind":"official","path":"src/tasks/downstream/sequence_recovery.py","file_url":"https://github.com/generteam/generator/blob/HEAD/src/tasks/downstream/sequence_recovery.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"bd38aef5ac2339e7"}},{"code_sha256_prefix":"c15e3fbc70c0a517","entry":"compute_logits_parallel","repo":"generteam/generator","repo_kind":"official","path":"src/tasks/downstream/variant_effect_prediction.py","file_url":"https://github.com/generteam/generator/blob/HEAD/src/tasks/downstream/variant_effect_prediction.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c15e3fbc70c0a517"}},{"code_sha256_prefix":"628b4145daeb0431","entry":"compute_logits_shard","repo":"generteam/generator","repo_kind":"official","path":"src/tasks/downstream/variant_effect_prediction.py","file_url":"https://github.com/generteam/generator/blob/HEAD/src/tasks/downstream/variant_effect_prediction.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"628b4145daeb0431"}},{"code_sha256_prefix":"e4c309376f141755","entry":"get_training_args","repo":"generteam/generator","repo_kind":"official","path":"src/tasks/downstream/fine_tuning.py","file_url":"https://github.com/generteam/generator/blob/HEAD/src/tasks/downstream/fine_tuning.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"e4c309376f141755"}},{"code_sha256_prefix":"5a3497d4b2c9e9af","entry":"load_and_prepare_data","repo":"generteam/generator","repo_kind":"official","path":"src/tasks/downstream/variant_effect_prediction.py","file_url":"https://github.com/generteam/generator/blob/HEAD/src/tasks/downstream/variant_effect_prediction.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"5a3497d4b2c9e9af"}},{"code_sha256_prefix":"5d3c1f73af6af134","entry":"process_data_shard","repo":"generteam/generator","repo_kind":"official","path":"src/tasks/downstream/sequence_recovery.py","file_url":"https://github.com/generteam/generator/blob/HEAD/src/tasks/downstream/sequence_recovery.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"5d3c1f73af6af134"}},{"code_sha256_prefix":"f888f5737ed04936","entry":"resolve_precision","repo":"generteam/generator","repo_kind":"official","path":"src/tasks/downstream/fine_tuning.py","file_url":"https://github.com/generteam/generator/blob/HEAD/src/tasks/downstream/fine_tuning.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"f888f5737ed04936"}},{"code_sha256_prefix":"1a68c98f205238b5","entry":"should_use_wandb","repo":"generteam/generator","repo_kind":"official","path":"src/tasks/downstream/fine_tuning.py","file_url":"https://github.com/generteam/generator/blob/HEAD/src/tasks/downstream/fine_tuning.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"1a68c98f205238b5"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}