{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:37OXJOHNJ4UUW2LCHJGLZ3KAHU","short_pith_number":"pith:37OXJOHN","canonical_record":{"source":{"id":"2604.16400","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.DC","submitted_at":"2026-03-31T09:49:47Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"3fe01046848d74d05da32219038fe0fcbef897e177ccf8bf58660806f9a9ba46","abstract_canon_sha256":"e139ad95cfc1865f9c91c09719816564215cec5599db475de3cdbbe6518c34f6"},"schema_version":"1.0"},"canonical_sha256":"dfdd74b8ed4f294b69623a4cbced403d3cc2cef8a47846d757aaf076d3da6876","source":{"kind":"arxiv","id":"2604.16400","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.16400","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"arxiv_version","alias_value":"2604.16400v2","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.16400","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"pith_short_12","alias_value":"37OXJOHNJ4UU","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"pith_short_16","alias_value":"37OXJOHNJ4UUW2LC","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"pith_short_8","alias_value":"37OXJOHN","created_at":"2026-05-20T00:02:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:37OXJOHNJ4UUW2LCHJGLZ3KAHU","target":"record","payload":{"canonical_record":{"source":{"id":"2604.16400","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.DC","submitted_at":"2026-03-31T09:49:47Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"3fe01046848d74d05da32219038fe0fcbef897e177ccf8bf58660806f9a9ba46","abstract_canon_sha256":"e139ad95cfc1865f9c91c09719816564215cec5599db475de3cdbbe6518c34f6"},"schema_version":"1.0"},"canonical_sha256":"dfdd74b8ed4f294b69623a4cbced403d3cc2cef8a47846d757aaf076d3da6876","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:02:11.594105Z","signature_b64":"VnepsDuvhDqR6atCmMxWKTPgRJGiFOiZrhW9aZIgVlW7BR2hCqdatBjn3OQyXaF5f9oSreUOXoTj4beE0xiWCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"dfdd74b8ed4f294b69623a4cbced403d3cc2cef8a47846d757aaf076d3da6876","last_reissued_at":"2026-05-20T00:02:11.593432Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:02:11.593432Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2604.16400","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-20T00:02:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"d1vAzrwo7NkThhARei3GObPB6rl8Nx/dn+Bi5/Rbyk3+OERYNmBbhikTXQrslWltVMMtK0b0C5LDgIKCxg+oDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-24T17:46:11.064880Z"},"content_sha256":"2e130f504794607ddff8f6d4133a92b3260abab08bd52083d0d3a159387ea859","schema_version":"1.0","event_id":"sha256:2e130f504794607ddff8f6d4133a92b3260abab08bd52083d0d3a159387ea859"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:37OXJOHNJ4UUW2LCHJGLZ3KAHU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CoLLM: Continuous Adaptation for SLO-Aware LLM Serving on Shared GPU Clusters","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.DC","authors_text":"Na Yan, Shaoyuan Huang, Tiancheng Zhang, Wenyu Wang, Xiaofei Wang, Xiaokai Wang, Yansha Deng, Yunfeng Zhao","submitted_at":"2026-03-31T09:49:47Z","abstract_excerpt":"As Large Language Models (LLMs) are increasingly adopted in edge intelligence to power domain-specific applications and personalized services, the quality and efficiency of the LLM post-training phase-including fine-tuning and inference, have become critical due to constrained resources. Although recent advances in federated parameter-efficient fine-tuning (FL PEFT) and low-latency inference have improved individual task performance, fine-tuning and inference are still handled as isolated workloads, which overlooks their interdependence and results in redundant deployments and delayed improvem"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.16400","kind":"arxiv","version":2},"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/2604.16400/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":"2026-05-20T00:02:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uxPcN9qlfd4a8AcR57iM328Xdg3Fd6XfYQqftABWN7jxaFF49vJfybL/d72rOjD9ibvchct0lOvI0lm/9PsRDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-24T17:46:11.065583Z"},"content_sha256":"593a301a99ae405bcda03a1b54d7a87f6668b04821edc713e7e8f2af3a3878fa","schema_version":"1.0","event_id":"sha256:593a301a99ae405bcda03a1b54d7a87f6668b04821edc713e7e8f2af3a3878fa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/37OXJOHNJ4UUW2LCHJGLZ3KAHU/bundle.json","state_url":"https://pith.science/pith/37OXJOHNJ4UUW2LCHJGLZ3KAHU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/37OXJOHNJ4UUW2LCHJGLZ3KAHU/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":"2026-05-24T17:46:11Z","links":{"resolver":"https://pith.science/pith/37OXJOHNJ4UUW2LCHJGLZ3KAHU","bundle":"https://pith.science/pith/37OXJOHNJ4UUW2LCHJGLZ3KAHU/bundle.json","state":"https://pith.science/pith/37OXJOHNJ4UUW2LCHJGLZ3KAHU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/37OXJOHNJ4UUW2LCHJGLZ3KAHU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:37OXJOHNJ4UUW2LCHJGLZ3KAHU","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":"e139ad95cfc1865f9c91c09719816564215cec5599db475de3cdbbe6518c34f6","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.DC","submitted_at":"2026-03-31T09:49:47Z","title_canon_sha256":"3fe01046848d74d05da32219038fe0fcbef897e177ccf8bf58660806f9a9ba46"},"schema_version":"1.0","source":{"id":"2604.16400","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2604.16400","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"arxiv_version","alias_value":"2604.16400v2","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2604.16400","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"pith_short_12","alias_value":"37OXJOHNJ4UU","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"pith_short_16","alias_value":"37OXJOHNJ4UUW2LC","created_at":"2026-05-20T00:02:11Z"},{"alias_kind":"pith_short_8","alias_value":"37OXJOHN","created_at":"2026-05-20T00:02:11Z"}],"graph_snapshots":[{"event_id":"sha256:593a301a99ae405bcda03a1b54d7a87f6668b04821edc713e7e8f2af3a3878fa","target":"graph","created_at":"2026-05-20T00:02:11Z","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/2604.16400/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As Large Language Models (LLMs) are increasingly adopted in edge intelligence to power domain-specific applications and personalized services, the quality and efficiency of the LLM post-training phase-including fine-tuning and inference, have become critical due to constrained resources. Although recent advances in federated parameter-efficient fine-tuning (FL PEFT) and low-latency inference have improved individual task performance, fine-tuning and inference are still handled as isolated workloads, which overlooks their interdependence and results in redundant deployments and delayed improvem","authors_text":"Na Yan, Shaoyuan Huang, Tiancheng Zhang, Wenyu Wang, Xiaofei Wang, Xiaokai Wang, Yansha Deng, Yunfeng Zhao","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.DC","submitted_at":"2026-03-31T09:49:47Z","title":"CoLLM: Continuous Adaptation for SLO-Aware LLM Serving on Shared GPU Clusters"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2604.16400","kind":"arxiv","version":2},"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":"sha256:2e130f504794607ddff8f6d4133a92b3260abab08bd52083d0d3a159387ea859","target":"record","created_at":"2026-05-20T00:02:11Z","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":"e139ad95cfc1865f9c91c09719816564215cec5599db475de3cdbbe6518c34f6","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.DC","submitted_at":"2026-03-31T09:49:47Z","title_canon_sha256":"3fe01046848d74d05da32219038fe0fcbef897e177ccf8bf58660806f9a9ba46"},"schema_version":"1.0","source":{"id":"2604.16400","kind":"arxiv","version":2}},"canonical_sha256":"dfdd74b8ed4f294b69623a4cbced403d3cc2cef8a47846d757aaf076d3da6876","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dfdd74b8ed4f294b69623a4cbced403d3cc2cef8a47846d757aaf076d3da6876","first_computed_at":"2026-05-20T00:02:11.593432Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:02:11.593432Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VnepsDuvhDqR6atCmMxWKTPgRJGiFOiZrhW9aZIgVlW7BR2hCqdatBjn3OQyXaF5f9oSreUOXoTj4beE0xiWCg==","signature_status":"signed_v1","signed_at":"2026-05-20T00:02:11.594105Z","signed_message":"canonical_sha256_bytes"},"source_id":"2604.16400","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2e130f504794607ddff8f6d4133a92b3260abab08bd52083d0d3a159387ea859","sha256:593a301a99ae405bcda03a1b54d7a87f6668b04821edc713e7e8f2af3a3878fa"],"state_sha256":"c96583f6ac60595ae04f8283e695f2605a9f3f7e7acea468fd377f008bd3c2ef"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VQHBU6vGaWdT3WMFR0xBACmpHnVSZRzIQuKPNx3nHlwOO1mAzhuzSwNSid6S16FuMq9QwnmEki4MbIj20fwUAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-24T17:46:11.068340Z","bundle_sha256":"baad97d3a7ba81932f866680e1223a9c1616f86dede0ab63ad02d32562939233"}}