{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:V7SFAZSLQNCJNQHT3SCBO7GOPA","short_pith_number":"pith:V7SFAZSL","canonical_record":{"source":{"id":"2412.04144","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-05T13:12:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f0f333e3d3b5fc053c915d1ce874c30218a3689af6096cbb5183b885019b0424","abstract_canon_sha256":"98b0b239b40b3d3205f39c3132901e2c33fcc88031bd240d6e529060dd72418b"},"schema_version":"1.0"},"canonical_sha256":"afe450664b834496c0f3dc84177cce783c8b3f5be24adeed7cf83412f4abed51","source":{"kind":"arxiv","id":"2412.04144","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.04144","created_at":"2026-07-05T10:09:13Z"},{"alias_kind":"arxiv_version","alias_value":"2412.04144v3","created_at":"2026-07-05T10:09:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.04144","created_at":"2026-07-05T10:09:13Z"},{"alias_kind":"pith_short_12","alias_value":"V7SFAZSLQNCJ","created_at":"2026-07-05T10:09:13Z"},{"alias_kind":"pith_short_16","alias_value":"V7SFAZSLQNCJNQHT","created_at":"2026-07-05T10:09:13Z"},{"alias_kind":"pith_short_8","alias_value":"V7SFAZSL","created_at":"2026-07-05T10:09:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:V7SFAZSLQNCJNQHT3SCBO7GOPA","target":"record","payload":{"canonical_record":{"source":{"id":"2412.04144","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-05T13:12:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f0f333e3d3b5fc053c915d1ce874c30218a3689af6096cbb5183b885019b0424","abstract_canon_sha256":"98b0b239b40b3d3205f39c3132901e2c33fcc88031bd240d6e529060dd72418b"},"schema_version":"1.0"},"canonical_sha256":"afe450664b834496c0f3dc84177cce783c8b3f5be24adeed7cf83412f4abed51","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:09:13.092038Z","signature_b64":"D2PDXqRQ/qJDbWcyAFlqFOEU/fiSmTgDbxkiAZZrlBlhYhoGRux+4NyrKbmZZG1mik4angYoHKmhfznyEtwIBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"afe450664b834496c0f3dc84177cce783c8b3f5be24adeed7cf83412f4abed51","last_reissued_at":"2026-07-05T10:09:13.091568Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:09:13.091568Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.04144","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:09:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rmEwQuldG0WwbNLjdK4BuvLtk/T1MM3saPvjlQs7c8ew2OXy/iwqWL0ifjoII6zoi+kFZC6NiEdWPG6NnFqSCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T23:08:48.169332Z"},"content_sha256":"d7644dadafd1ad058e38b1ef43c5c92252097ec43410512375cd6aa42ef6ea8d","schema_version":"1.0","event_id":"sha256:d7644dadafd1ad058e38b1ef43c5c92252097ec43410512375cd6aa42ef6ea8d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:V7SFAZSLQNCJNQHT3SCBO7GOPA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"If You Can't Use Them, Recycle Them: Optimizing Merging at Scale Mitigates Performance Tradeoffs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Ahmet \\\"Ust\\\"un, Arash Ahmadian, Honglak Lee, Lu Wang, Matthias Gall\\'e, Muhammad Khalifa, Tom Hosking, Tom Sherborne, Yi-Chern Tan","submitted_at":"2024-12-05T13:12:51Z","abstract_excerpt":"Model merging has shown great promise at combining expert models, but the benefit of merging is unclear when merging \"generalist\" models trained on many tasks. We explore merging in the context of large (~100B) models, by recycling checkpoints that exhibit tradeoffs among different tasks. Such checkpoints are often created in the process of developing a frontier model, and the suboptimal ones are usually discarded. Given a pool of model checkpoints obtained from different training runs (e.g., different stages, objectives, hyperparameters, and data mixtures), which naturally show tradeoffs acro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.04144","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/2412.04144/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:09:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LXViFC3dYlzpxPXksmwptOFDyWcy4ELHsiJqh/wsfb+sTY85wDRpsBydO9SnCRInE1K9dg3649v1+larVmE0BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T23:08:48.169720Z"},"content_sha256":"c5ca9ad5a37055ec200240dd90143f6da0196bf7d0a16b5583d32194378250e2","schema_version":"1.0","event_id":"sha256:c5ca9ad5a37055ec200240dd90143f6da0196bf7d0a16b5583d32194378250e2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/V7SFAZSLQNCJNQHT3SCBO7GOPA/bundle.json","state_url":"https://pith.science/pith/V7SFAZSLQNCJNQHT3SCBO7GOPA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/V7SFAZSLQNCJNQHT3SCBO7GOPA/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T23:08:48Z","links":{"resolver":"https://pith.science/pith/V7SFAZSLQNCJNQHT3SCBO7GOPA","bundle":"https://pith.science/pith/V7SFAZSLQNCJNQHT3SCBO7GOPA/bundle.json","state":"https://pith.science/pith/V7SFAZSLQNCJNQHT3SCBO7GOPA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/V7SFAZSLQNCJNQHT3SCBO7GOPA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:V7SFAZSLQNCJNQHT3SCBO7GOPA","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"98b0b239b40b3d3205f39c3132901e2c33fcc88031bd240d6e529060dd72418b","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-05T13:12:51Z","title_canon_sha256":"f0f333e3d3b5fc053c915d1ce874c30218a3689af6096cbb5183b885019b0424"},"schema_version":"1.0","source":{"id":"2412.04144","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.04144","created_at":"2026-07-05T10:09:13Z"},{"alias_kind":"arxiv_version","alias_value":"2412.04144v3","created_at":"2026-07-05T10:09:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.04144","created_at":"2026-07-05T10:09:13Z"},{"alias_kind":"pith_short_12","alias_value":"V7SFAZSLQNCJ","created_at":"2026-07-05T10:09:13Z"},{"alias_kind":"pith_short_16","alias_value":"V7SFAZSLQNCJNQHT","created_at":"2026-07-05T10:09:13Z"},{"alias_kind":"pith_short_8","alias_value":"V7SFAZSL","created_at":"2026-07-05T10:09:13Z"}],"graph_snapshots":[{"event_id":"sha256:c5ca9ad5a37055ec200240dd90143f6da0196bf7d0a16b5583d32194378250e2","target":"graph","created_at":"2026-07-05T10:09:13Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2412.04144/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Model merging has shown great promise at combining expert models, but the benefit of merging is unclear when merging \"generalist\" models trained on many tasks. We explore merging in the context of large (~100B) models, by recycling checkpoints that exhibit tradeoffs among different tasks. Such checkpoints are often created in the process of developing a frontier model, and the suboptimal ones are usually discarded. Given a pool of model checkpoints obtained from different training runs (e.g., different stages, objectives, hyperparameters, and data mixtures), which naturally show tradeoffs acro","authors_text":"Ahmet \\\"Ust\\\"un, Arash Ahmadian, Honglak Lee, Lu Wang, Matthias Gall\\'e, Muhammad Khalifa, Tom Hosking, Tom Sherborne, Yi-Chern Tan","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-05T13:12:51Z","title":"If You Can't Use Them, Recycle Them: Optimizing Merging at Scale Mitigates Performance Tradeoffs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.04144","kind":"arxiv","version":3},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:d7644dadafd1ad058e38b1ef43c5c92252097ec43410512375cd6aa42ef6ea8d","target":"record","created_at":"2026-07-05T10:09:13Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"98b0b239b40b3d3205f39c3132901e2c33fcc88031bd240d6e529060dd72418b","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-05T13:12:51Z","title_canon_sha256":"f0f333e3d3b5fc053c915d1ce874c30218a3689af6096cbb5183b885019b0424"},"schema_version":"1.0","source":{"id":"2412.04144","kind":"arxiv","version":3}},"canonical_sha256":"afe450664b834496c0f3dc84177cce783c8b3f5be24adeed7cf83412f4abed51","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"afe450664b834496c0f3dc84177cce783c8b3f5be24adeed7cf83412f4abed51","first_computed_at":"2026-07-05T10:09:13.091568Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:09:13.091568Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"D2PDXqRQ/qJDbWcyAFlqFOEU/fiSmTgDbxkiAZZrlBlhYhoGRux+4NyrKbmZZG1mik4angYoHKmhfznyEtwIBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:09:13.092038Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.04144","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d7644dadafd1ad058e38b1ef43c5c92252097ec43410512375cd6aa42ef6ea8d","sha256:c5ca9ad5a37055ec200240dd90143f6da0196bf7d0a16b5583d32194378250e2"],"state_sha256":"0c5389122631ceda2ade4b2f0e9b7453e7061322ddbbbad89bf45fce3f6e9208"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"owA3IbHxGfBEP8P7NggJ+6Nh2y4cdC59uABWSf0/XzOBBfNHrMYp6V8CECoKotuXHV5Uec6LsrXLCEuRtsaJCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T23:08:48.171725Z","bundle_sha256":"9ccb8e8e3538074e1590cd525d6f4ab70f8d8fd4a313b49cd38c12232b20eef0"}}