{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:2DXJJBOCZLZRA7YNGG5JQTFFRK","short_pith_number":"pith:2DXJJBOC","canonical_record":{"source":{"id":"2608.08627","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-08-09T10:20:20Z","cross_cats_sorted":[],"title_canon_sha256":"619e781ed3ab0fd96bd281e77f0e1cf2d726169e4de04af2d1d6ea266c93357a","abstract_canon_sha256":"0e03fe664bab1e2d1425ae7018a63cc34eed73d5520be32b67cbca33263936a9"},"schema_version":"1.0"},"canonical_sha256":"d0ee9485c2caf3107f0d31ba984ca58a9160ebc3faad02250b6b61aa3cbb4290","source":{"kind":"arxiv","id":"2608.08627","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.08627","created_at":"2026-08-11T01:23:12Z"},{"alias_kind":"arxiv_version","alias_value":"2608.08627v1","created_at":"2026-08-11T01:23:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.08627","created_at":"2026-08-11T01:23:12Z"},{"alias_kind":"pith_short_12","alias_value":"2DXJJBOCZLZR","created_at":"2026-08-11T01:23:12Z"},{"alias_kind":"pith_short_16","alias_value":"2DXJJBOCZLZRA7YN","created_at":"2026-08-11T01:23:12Z"},{"alias_kind":"pith_short_8","alias_value":"2DXJJBOC","created_at":"2026-08-11T01:23:12Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:2DXJJBOCZLZRA7YNGG5JQTFFRK","target":"record","payload":{"canonical_record":{"source":{"id":"2608.08627","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-08-09T10:20:20Z","cross_cats_sorted":[],"title_canon_sha256":"619e781ed3ab0fd96bd281e77f0e1cf2d726169e4de04af2d1d6ea266c93357a","abstract_canon_sha256":"0e03fe664bab1e2d1425ae7018a63cc34eed73d5520be32b67cbca33263936a9"},"schema_version":"1.0"},"canonical_sha256":"d0ee9485c2caf3107f0d31ba984ca58a9160ebc3faad02250b6b61aa3cbb4290","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-11T01:23:12.674162Z","signature_b64":"Hs+zcqJ7h1ghMOQlzYX+VlMBpIOfoOk+pvFaTi6TllY6c1FqrLE0c1Q7ckdOq7Qs0kaEWkLIOxhZfzAWWOQQDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d0ee9485c2caf3107f0d31ba984ca58a9160ebc3faad02250b6b61aa3cbb4290","last_reissued_at":"2026-08-11T01:23:12.671673Z","signature_status":"signed_v1","first_computed_at":"2026-08-11T01:23:12.671673Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.08627","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-11T01:23:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"19yU8B4L7SCHJPGsOpS98G8xjud22+wgysToWYu6YTDKEMc3a9DJYFtEaQd3PVeCy8GlkX9h0/pAvb6Z9+SqCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T02:13:49.692754Z"},"content_sha256":"892e502629d7f7d5150951d55c3cdbafe058ca28f39422ef546f627171631994","schema_version":"1.0","event_id":"sha256:892e502629d7f7d5150951d55c3cdbafe058ca28f39422ef546f627171631994"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:2DXJJBOCZLZRA7YNGG5JQTFFRK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"UniMoMo: Expert Merging-Based MoE Acceleration for Large Recommendation Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Bin Gu, Changjiang Jiang, Chao Huang, Fanhu Zeng, Jianbo Zhao, Lei Xin, Peize Li, Xuyang Zhao, Yanyue Xie, Zhenglun Kong, Zitong Wang, Zunhai Su","submitted_at":"2026-08-09T10:20:20Z","abstract_excerpt":"Sparse mixture-of-experts (MoE) layers expand recommendation capacity through conditional computation, yet a trained checkpoint still stores and routes over its full expert bank. We study a deployment problem: convert that checkpoint to a smaller standard MoE under an explicit expert budget, without adding a compression-specific online module. To address this, we introduce UniMoMo, a post-training compression framework formulated as a constrained graph coarsening problem. Rather than relying on parameter distance, UniMoMo groups experts based on their functional similarity, using an unlabeled "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.08627","kind":"arxiv","version":1},"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/2608.08627/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":"2026-08-11T01:23:12Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D7Z63PpRWgEJuX4rIq5rt4jxNfGLGpjqOpuhi0QUTjl97IwKHnnq4W1qGlxvvludy7KGrbU7mGOhTPwZuYjlAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T02:13:49.693077Z"},"content_sha256":"f9bcca619db3667ca9a44d662ff8ce35912fc1c98804a7fe3cdbed8293d0c000","schema_version":"1.0","event_id":"sha256:f9bcca619db3667ca9a44d662ff8ce35912fc1c98804a7fe3cdbed8293d0c000"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2DXJJBOCZLZRA7YNGG5JQTFFRK/bundle.json","state_url":"https://pith.science/pith/2DXJJBOCZLZRA7YNGG5JQTFFRK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2DXJJBOCZLZRA7YNGG5JQTFFRK/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":"2026-08-19T02:13:49Z","links":{"resolver":"https://pith.science/pith/2DXJJBOCZLZRA7YNGG5JQTFFRK","bundle":"https://pith.science/pith/2DXJJBOCZLZRA7YNGG5JQTFFRK/bundle.json","state":"https://pith.science/pith/2DXJJBOCZLZRA7YNGG5JQTFFRK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2DXJJBOCZLZRA7YNGG5JQTFFRK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:2DXJJBOCZLZRA7YNGG5JQTFFRK","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":"0e03fe664bab1e2d1425ae7018a63cc34eed73d5520be32b67cbca33263936a9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-08-09T10:20:20Z","title_canon_sha256":"619e781ed3ab0fd96bd281e77f0e1cf2d726169e4de04af2d1d6ea266c93357a"},"schema_version":"1.0","source":{"id":"2608.08627","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.08627","created_at":"2026-08-11T01:23:12Z"},{"alias_kind":"arxiv_version","alias_value":"2608.08627v1","created_at":"2026-08-11T01:23:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.08627","created_at":"2026-08-11T01:23:12Z"},{"alias_kind":"pith_short_12","alias_value":"2DXJJBOCZLZR","created_at":"2026-08-11T01:23:12Z"},{"alias_kind":"pith_short_16","alias_value":"2DXJJBOCZLZRA7YN","created_at":"2026-08-11T01:23:12Z"},{"alias_kind":"pith_short_8","alias_value":"2DXJJBOC","created_at":"2026-08-11T01:23:12Z"}],"graph_snapshots":[{"event_id":"sha256:f9bcca619db3667ca9a44d662ff8ce35912fc1c98804a7fe3cdbed8293d0c000","target":"graph","created_at":"2026-08-11T01:23:12Z","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/2608.08627/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sparse mixture-of-experts (MoE) layers expand recommendation capacity through conditional computation, yet a trained checkpoint still stores and routes over its full expert bank. We study a deployment problem: convert that checkpoint to a smaller standard MoE under an explicit expert budget, without adding a compression-specific online module. To address this, we introduce UniMoMo, a post-training compression framework formulated as a constrained graph coarsening problem. Rather than relying on parameter distance, UniMoMo groups experts based on their functional similarity, using an unlabeled ","authors_text":"Bin Gu, Changjiang Jiang, Chao Huang, Fanhu Zeng, Jianbo Zhao, Lei Xin, Peize Li, Xuyang Zhao, Yanyue Xie, Zhenglun Kong, Zitong Wang, Zunhai Su","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-08-09T10:20:20Z","title":"UniMoMo: Expert Merging-Based MoE Acceleration for Large Recommendation Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.08627","kind":"arxiv","version":1},"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":"sha256:892e502629d7f7d5150951d55c3cdbafe058ca28f39422ef546f627171631994","target":"record","created_at":"2026-08-11T01:23:12Z","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":"0e03fe664bab1e2d1425ae7018a63cc34eed73d5520be32b67cbca33263936a9","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-08-09T10:20:20Z","title_canon_sha256":"619e781ed3ab0fd96bd281e77f0e1cf2d726169e4de04af2d1d6ea266c93357a"},"schema_version":"1.0","source":{"id":"2608.08627","kind":"arxiv","version":1}},"canonical_sha256":"d0ee9485c2caf3107f0d31ba984ca58a9160ebc3faad02250b6b61aa3cbb4290","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d0ee9485c2caf3107f0d31ba984ca58a9160ebc3faad02250b6b61aa3cbb4290","first_computed_at":"2026-08-11T01:23:12.671673Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-11T01:23:12.671673Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Hs+zcqJ7h1ghMOQlzYX+VlMBpIOfoOk+pvFaTi6TllY6c1FqrLE0c1Q7ckdOq7Qs0kaEWkLIOxhZfzAWWOQQDw==","signature_status":"signed_v1","signed_at":"2026-08-11T01:23:12.674162Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.08627","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:892e502629d7f7d5150951d55c3cdbafe058ca28f39422ef546f627171631994","sha256:f9bcca619db3667ca9a44d662ff8ce35912fc1c98804a7fe3cdbed8293d0c000"],"state_sha256":"9c7882bfa03b8cde1028a4653d24cbef9f7d6eb1db520fe849b571171b69814e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YtP+G0j/9PMbQb8jls3F1jDNObLFoVu1jis3dRiOkK5tM84H0iBGXGuUBOpO6F5ZpbzKJjLlaKaEZDv1wDGxAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T02:13:49.696178Z","bundle_sha256":"e4854d9507229bde8152d3c42122c08b7c024162c32d65461509bbb46989ff92"}}