{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:MYBTXKUYYP6ICJZPUCHTG3ZAX6","short_pith_number":"pith:MYBTXKUY","canonical_record":{"source":{"id":"2503.01359","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-03T09:52:46Z","cross_cats_sorted":[],"title_canon_sha256":"a92b34c9d30efbd653bb1d7066a1397cc0ff63d627aa686795b17d94b2dcbec1","abstract_canon_sha256":"8d72130c161f3f01d86a3806900d4eb910a10ef2773cf18273b76d8984ef7172"},"schema_version":"1.0"},"canonical_sha256":"66033baa98c3fc81272fa08f336f20bf94b24bd9a413ad4e263d3d0eea454cf7","source":{"kind":"arxiv","id":"2503.01359","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.01359","created_at":"2026-07-05T10:23:05Z"},{"alias_kind":"arxiv_version","alias_value":"2503.01359v1","created_at":"2026-07-05T10:23:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.01359","created_at":"2026-07-05T10:23:05Z"},{"alias_kind":"pith_short_12","alias_value":"MYBTXKUYYP6I","created_at":"2026-07-05T10:23:05Z"},{"alias_kind":"pith_short_16","alias_value":"MYBTXKUYYP6ICJZP","created_at":"2026-07-05T10:23:05Z"},{"alias_kind":"pith_short_8","alias_value":"MYBTXKUY","created_at":"2026-07-05T10:23:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:MYBTXKUYYP6ICJZPUCHTG3ZAX6","target":"record","payload":{"canonical_record":{"source":{"id":"2503.01359","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-03T09:52:46Z","cross_cats_sorted":[],"title_canon_sha256":"a92b34c9d30efbd653bb1d7066a1397cc0ff63d627aa686795b17d94b2dcbec1","abstract_canon_sha256":"8d72130c161f3f01d86a3806900d4eb910a10ef2773cf18273b76d8984ef7172"},"schema_version":"1.0"},"canonical_sha256":"66033baa98c3fc81272fa08f336f20bf94b24bd9a413ad4e263d3d0eea454cf7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:23:05.493793Z","signature_b64":"1teldGubeib6KkTipn8xcD88znjUicc4/FAxkctnTuyFoPy9QgZpPl7aptV1Ar1AzkJaETBxoKBGqBuWic9MCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"66033baa98c3fc81272fa08f336f20bf94b24bd9a413ad4e263d3d0eea454cf7","last_reissued_at":"2026-07-05T10:23:05.493130Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:23:05.493130Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.01359","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":"2026-07-05T10:23:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uUua1n9eYwytHnJBANoDT6w56k0eH18/iA754qRxojL640DrcCKnTwel8g30tn8sZDCAVMuuuSML4sQeluebCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T07:04:08.252130Z"},"content_sha256":"ed2fced9a9f3df604c4e2de596b10348d0e6ea6968b44ab6e979c3a1b40fe65f","schema_version":"1.0","event_id":"sha256:ed2fced9a9f3df604c4e2de596b10348d0e6ea6968b44ab6e979c3a1b40fe65f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:MYBTXKUYYP6ICJZPUCHTG3ZAX6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeRS: Towards Extremely Efficient Upcycled Mixture-of-Experts Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Baopu Li, Chenyu Huang, Gang Yu, Jianjian Cao, Lin Zhang, Peng Ye, Tao Chen, Yongqi Huang","submitted_at":"2025-03-03T09:52:46Z","abstract_excerpt":"Upcycled Mixture-of-Experts (MoE) models have shown great potential in various tasks by converting the original Feed-Forward Network (FFN) layers in pre-trained dense models into MoE layers. However, these models still suffer from significant parameter inefficiency due to the introduction of multiple experts. In this work, we propose a novel DeRS (Decompose, Replace, and Synthesis) paradigm to overcome this shortcoming, which is motivated by our observations about the unique redundancy mechanisms of upcycled MoE experts. Specifically, DeRS decomposes the experts into one expert-shared base wei"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.01359","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/2503.01359/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":"2026-07-05T10:23:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2CeLjUag/GpABI0IzgPRVTCveLNG8CBp7yBlkXGZdcYe9fYOOGaIHx4fRHfHNFV01AAeXQAFPeKvjrYm2AH8AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T07:04:08.252695Z"},"content_sha256":"e4b15fb6d1eb91803a12bd9bcbfb1cd3f5b6a697b0204a17bf33cbc1a8db7c3f","schema_version":"1.0","event_id":"sha256:e4b15fb6d1eb91803a12bd9bcbfb1cd3f5b6a697b0204a17bf33cbc1a8db7c3f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MYBTXKUYYP6ICJZPUCHTG3ZAX6/bundle.json","state_url":"https://pith.science/pith/MYBTXKUYYP6ICJZPUCHTG3ZAX6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MYBTXKUYYP6ICJZPUCHTG3ZAX6/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":"2026-08-08T07:04:08Z","links":{"resolver":"https://pith.science/pith/MYBTXKUYYP6ICJZPUCHTG3ZAX6","bundle":"https://pith.science/pith/MYBTXKUYYP6ICJZPUCHTG3ZAX6/bundle.json","state":"https://pith.science/pith/MYBTXKUYYP6ICJZPUCHTG3ZAX6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MYBTXKUYYP6ICJZPUCHTG3ZAX6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:MYBTXKUYYP6ICJZPUCHTG3ZAX6","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":"8d72130c161f3f01d86a3806900d4eb910a10ef2773cf18273b76d8984ef7172","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-03T09:52:46Z","title_canon_sha256":"a92b34c9d30efbd653bb1d7066a1397cc0ff63d627aa686795b17d94b2dcbec1"},"schema_version":"1.0","source":{"id":"2503.01359","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.01359","created_at":"2026-07-05T10:23:05Z"},{"alias_kind":"arxiv_version","alias_value":"2503.01359v1","created_at":"2026-07-05T10:23:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.01359","created_at":"2026-07-05T10:23:05Z"},{"alias_kind":"pith_short_12","alias_value":"MYBTXKUYYP6I","created_at":"2026-07-05T10:23:05Z"},{"alias_kind":"pith_short_16","alias_value":"MYBTXKUYYP6ICJZP","created_at":"2026-07-05T10:23:05Z"},{"alias_kind":"pith_short_8","alias_value":"MYBTXKUY","created_at":"2026-07-05T10:23:05Z"}],"graph_snapshots":[{"event_id":"sha256:e4b15fb6d1eb91803a12bd9bcbfb1cd3f5b6a697b0204a17bf33cbc1a8db7c3f","target":"graph","created_at":"2026-07-05T10:23:05Z","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/2503.01359/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Upcycled Mixture-of-Experts (MoE) models have shown great potential in various tasks by converting the original Feed-Forward Network (FFN) layers in pre-trained dense models into MoE layers. However, these models still suffer from significant parameter inefficiency due to the introduction of multiple experts. In this work, we propose a novel DeRS (Decompose, Replace, and Synthesis) paradigm to overcome this shortcoming, which is motivated by our observations about the unique redundancy mechanisms of upcycled MoE experts. Specifically, DeRS decomposes the experts into one expert-shared base wei","authors_text":"Baopu Li, Chenyu Huang, Gang Yu, Jianjian Cao, Lin Zhang, Peng Ye, Tao Chen, Yongqi Huang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-03T09:52:46Z","title":"DeRS: Towards Extremely Efficient Upcycled Mixture-of-Experts Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.01359","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:ed2fced9a9f3df604c4e2de596b10348d0e6ea6968b44ab6e979c3a1b40fe65f","target":"record","created_at":"2026-07-05T10:23:05Z","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":"8d72130c161f3f01d86a3806900d4eb910a10ef2773cf18273b76d8984ef7172","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-03-03T09:52:46Z","title_canon_sha256":"a92b34c9d30efbd653bb1d7066a1397cc0ff63d627aa686795b17d94b2dcbec1"},"schema_version":"1.0","source":{"id":"2503.01359","kind":"arxiv","version":1}},"canonical_sha256":"66033baa98c3fc81272fa08f336f20bf94b24bd9a413ad4e263d3d0eea454cf7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"66033baa98c3fc81272fa08f336f20bf94b24bd9a413ad4e263d3d0eea454cf7","first_computed_at":"2026-07-05T10:23:05.493130Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:23:05.493130Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1teldGubeib6KkTipn8xcD88znjUicc4/FAxkctnTuyFoPy9QgZpPl7aptV1Ar1AzkJaETBxoKBGqBuWic9MCg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:23:05.493793Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.01359","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ed2fced9a9f3df604c4e2de596b10348d0e6ea6968b44ab6e979c3a1b40fe65f","sha256:e4b15fb6d1eb91803a12bd9bcbfb1cd3f5b6a697b0204a17bf33cbc1a8db7c3f"],"state_sha256":"53e90d58815171cc5b77f10e4f57052fb007e990b604ee09e80669a5f471ae92"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cHSQTNGKIHYLjxL4Fo3vPOHOhJ0VOKKeBDycGlqCSS/4sNMvZkiRPugVBhK6aKLwpjhJINHUDBvlgorkK41EAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T07:04:08.258808Z","bundle_sha256":"ea6317328f1a014832b8260b0212e2e9f92acd4cb903ce980aebbb9a3a549629"}}