{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:NOY3Z5BAHIYGAWS3UXVAIDKCNV","short_pith_number":"pith:NOY3Z5BA","schema_version":"1.0","canonical_sha256":"6bb1bcf4203a30605a5ba5ea040d426d7f27a8dbdc314533d421ddee2a2e14f5","source":{"kind":"arxiv","id":"2505.00985","version":3},"attestation_state":"computed","paper":{"title":"Position: Enough of Scaling LLMs! Lets Focus on Downscaling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ayan Sengupta, Tanmoy Chakraborty, Yash Goel","submitted_at":"2025-05-02T04:13:27Z","abstract_excerpt":"We challenge the dominant focus on neural scaling laws and advocate for a paradigm shift toward downscaling in the development of large language models (LLMs). While scaling laws have provided critical insights into performance improvements through increasing model and dataset size, we emphasize the significant limitations of this approach, particularly in terms of computational inefficiency, environmental impact, and deployment constraints. To address these challenges, we propose a holistic framework for downscaling LLMs that seeks to maintain performance while drastically reducing resource d"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2505.00985","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-02T04:13:27Z","cross_cats_sorted":[],"title_canon_sha256":"0aad5d96477d480dc5f85d16acb7f271fe36f68585b28a8320b588ce2af9e66e","abstract_canon_sha256":"7168bf50d27fcb0a70541a1c54992513aa884604ec9cd6cb8d69120e23cfe1ee"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:12.482918Z","signature_b64":"3OX/BFhFWJeFjcTt0LHCGoqTM/uaRVzTrzqBJ+ceY/PgUbjIAqKMJhKkXWuNaoZ8QwY+p71KxIyNkAuzPj8RDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6bb1bcf4203a30605a5ba5ea040d426d7f27a8dbdc314533d421ddee2a2e14f5","last_reissued_at":"2026-07-05T11:09:12.482434Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:12.482434Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Position: Enough of Scaling LLMs! Lets Focus on Downscaling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Ayan Sengupta, Tanmoy Chakraborty, Yash Goel","submitted_at":"2025-05-02T04:13:27Z","abstract_excerpt":"We challenge the dominant focus on neural scaling laws and advocate for a paradigm shift toward downscaling in the development of large language models (LLMs). While scaling laws have provided critical insights into performance improvements through increasing model and dataset size, we emphasize the significant limitations of this approach, particularly in terms of computational inefficiency, environmental impact, and deployment constraints. To address these challenges, we propose a holistic framework for downscaling LLMs that seeks to maintain performance while drastically reducing resource d"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.00985","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2505.00985/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2505.00985","created_at":"2026-07-05T11:09:12.482490+00:00"},{"alias_kind":"arxiv_version","alias_value":"2505.00985v3","created_at":"2026-07-05T11:09:12.482490+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.00985","created_at":"2026-07-05T11:09:12.482490+00:00"},{"alias_kind":"pith_short_12","alias_value":"NOY3Z5BAHIYG","created_at":"2026-07-05T11:09:12.482490+00:00"},{"alias_kind":"pith_short_16","alias_value":"NOY3Z5BAHIYGAWS3","created_at":"2026-07-05T11:09:12.482490+00:00"},{"alias_kind":"pith_short_8","alias_value":"NOY3Z5BA","created_at":"2026-07-05T11:09:12.482490+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/NOY3Z5BAHIYGAWS3UXVAIDKCNV","json":"https://pith.science/pith/NOY3Z5BAHIYGAWS3UXVAIDKCNV.json","graph_json":"https://pith.science/api/pith-number/NOY3Z5BAHIYGAWS3UXVAIDKCNV/graph.json","events_json":"https://pith.science/api/pith-number/NOY3Z5BAHIYGAWS3UXVAIDKCNV/events.json","paper":"https://pith.science/paper/NOY3Z5BA"},"agent_actions":{"view_html":"https://pith.science/pith/NOY3Z5BAHIYGAWS3UXVAIDKCNV","download_json":"https://pith.science/pith/NOY3Z5BAHIYGAWS3UXVAIDKCNV.json","view_paper":"https://pith.science/paper/NOY3Z5BA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2505.00985&json=true","fetch_graph":"https://pith.science/api/pith-number/NOY3Z5BAHIYGAWS3UXVAIDKCNV/graph.json","fetch_events":"https://pith.science/api/pith-number/NOY3Z5BAHIYGAWS3UXVAIDKCNV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/NOY3Z5BAHIYGAWS3UXVAIDKCNV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/NOY3Z5BAHIYGAWS3UXVAIDKCNV/action/storage_attestation","attest_author":"https://pith.science/pith/NOY3Z5BAHIYGAWS3UXVAIDKCNV/action/author_attestation","sign_citation":"https://pith.science/pith/NOY3Z5BAHIYGAWS3UXVAIDKCNV/action/citation_signature","submit_replication":"https://pith.science/pith/NOY3Z5BAHIYGAWS3UXVAIDKCNV/action/replication_record"}},"created_at":"2026-07-05T11:09:12.482490+00:00","updated_at":"2026-07-05T11:09:12.482490+00:00"}