{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:SLIAF6AQ2L7TMA3WUEJJ63T6KH","short_pith_number":"pith:SLIAF6AQ","canonical_record":{"source":{"id":"2605.28207","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-27T09:27:36Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fa44536ea11da5999129901f73cee698a743ea7e230fde4963b1a932ee13dd48","abstract_canon_sha256":"7090822ff55e223e86fe029c9cc0c7fdaf081ad29bceb4a8aacd96e476e05ff1"},"schema_version":"1.0"},"canonical_sha256":"92d002f810d2ff360376a1129f6e7e51cda07aa6cb14206f6ff55bfb7f183a2d","source":{"kind":"arxiv","id":"2605.28207","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.28207","created_at":"2026-05-28T01:05:02Z"},{"alias_kind":"arxiv_version","alias_value":"2605.28207v1","created_at":"2026-05-28T01:05:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.28207","created_at":"2026-05-28T01:05:02Z"},{"alias_kind":"pith_short_12","alias_value":"SLIAF6AQ2L7T","created_at":"2026-05-28T01:05:02Z"},{"alias_kind":"pith_short_16","alias_value":"SLIAF6AQ2L7TMA3W","created_at":"2026-05-28T01:05:02Z"},{"alias_kind":"pith_short_8","alias_value":"SLIAF6AQ","created_at":"2026-05-28T01:05:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:SLIAF6AQ2L7TMA3WUEJJ63T6KH","target":"record","payload":{"canonical_record":{"source":{"id":"2605.28207","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-27T09:27:36Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fa44536ea11da5999129901f73cee698a743ea7e230fde4963b1a932ee13dd48","abstract_canon_sha256":"7090822ff55e223e86fe029c9cc0c7fdaf081ad29bceb4a8aacd96e476e05ff1"},"schema_version":"1.0"},"canonical_sha256":"92d002f810d2ff360376a1129f6e7e51cda07aa6cb14206f6ff55bfb7f183a2d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-28T01:05:02.619075Z","signature_b64":"WZ2dMW7K38XlUGJRLj4lcfAM9JJ1JRg7aSm5xksYq53SogHucnCb8L8RXAPDxJ4lXW5VFOUQYe/kGxN6MA4xDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"92d002f810d2ff360376a1129f6e7e51cda07aa6cb14206f6ff55bfb7f183a2d","last_reissued_at":"2026-05-28T01:05:02.618625Z","signature_status":"signed_v1","first_computed_at":"2026-05-28T01:05:02.618625Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.28207","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":"2026-05-28T01:05:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bg3RQcFPmH7hWDubZTumiHgOcJ3BcbpucVQGZUt8koUVoxltKNLfnQ/SCG3m7M8iKXL5MabUot0lycaVkzv+Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T12:19:33.093129Z"},"content_sha256":"c2050936c5ec765442b46334284b28a33978bd236ae7a6be1d6828b5fc3500d4","schema_version":"1.0","event_id":"sha256:c2050936c5ec765442b46334284b28a33978bd236ae7a6be1d6828b5fc3500d4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:SLIAF6AQ2L7TMA3WUEJJ63T6KH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Pruning and Distilling Mixture-of-Experts into Dense Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Gyeongman Kim, Haechan Kim, Jaewoong Cho, Jihun Yun, Joonghyun Bae, Junhyuck Kim","submitted_at":"2026-05-27T09:27:36Z","abstract_excerpt":"Mixture-of-Experts (MoE) is now the dominant architecture for frontier language models, yet it requires all expert parameters to be loaded in memory, making it less preferable for memory-constrained deployment. Existing compression methods reduce the number of experts but the output remains an MoE model with the same fundamental limitation. We present the first systematic framework for converting a trained MoE into a standard fully dense architecture: experts are scored, selected, and grouped, then concatenated into a dense FFN and refined by knowledge distillation from the MoE teacher. We eva"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.28207","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/2605.28207/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":"2026-05-28T01:05:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"efWy7fxny2cDn0JD+jgzLnjmIpj36eIIHA34fOXLHYwz9BqM84hdlx3WrfxwCQEuNDIpiFbcxwqxb5IBYD20Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T12:19:33.093522Z"},"content_sha256":"b1e87e9674a105e61ea96ab9e123758415ecd6c137fab4b6786e3c49f8128a18","schema_version":"1.0","event_id":"sha256:b1e87e9674a105e61ea96ab9e123758415ecd6c137fab4b6786e3c49f8128a18"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SLIAF6AQ2L7TMA3WUEJJ63T6KH/bundle.json","state_url":"https://pith.science/pith/SLIAF6AQ2L7TMA3WUEJJ63T6KH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SLIAF6AQ2L7TMA3WUEJJ63T6KH/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":"2026-06-08T12:19:33Z","links":{"resolver":"https://pith.science/pith/SLIAF6AQ2L7TMA3WUEJJ63T6KH","bundle":"https://pith.science/pith/SLIAF6AQ2L7TMA3WUEJJ63T6KH/bundle.json","state":"https://pith.science/pith/SLIAF6AQ2L7TMA3WUEJJ63T6KH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SLIAF6AQ2L7TMA3WUEJJ63T6KH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:SLIAF6AQ2L7TMA3WUEJJ63T6KH","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":"7090822ff55e223e86fe029c9cc0c7fdaf081ad29bceb4a8aacd96e476e05ff1","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-27T09:27:36Z","title_canon_sha256":"fa44536ea11da5999129901f73cee698a743ea7e230fde4963b1a932ee13dd48"},"schema_version":"1.0","source":{"id":"2605.28207","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.28207","created_at":"2026-05-28T01:05:02Z"},{"alias_kind":"arxiv_version","alias_value":"2605.28207v1","created_at":"2026-05-28T01:05:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.28207","created_at":"2026-05-28T01:05:02Z"},{"alias_kind":"pith_short_12","alias_value":"SLIAF6AQ2L7T","created_at":"2026-05-28T01:05:02Z"},{"alias_kind":"pith_short_16","alias_value":"SLIAF6AQ2L7TMA3W","created_at":"2026-05-28T01:05:02Z"},{"alias_kind":"pith_short_8","alias_value":"SLIAF6AQ","created_at":"2026-05-28T01:05:02Z"}],"graph_snapshots":[{"event_id":"sha256:b1e87e9674a105e61ea96ab9e123758415ecd6c137fab4b6786e3c49f8128a18","target":"graph","created_at":"2026-05-28T01:05:02Z","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/2605.28207/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Mixture-of-Experts (MoE) is now the dominant architecture for frontier language models, yet it requires all expert parameters to be loaded in memory, making it less preferable for memory-constrained deployment. Existing compression methods reduce the number of experts but the output remains an MoE model with the same fundamental limitation. We present the first systematic framework for converting a trained MoE into a standard fully dense architecture: experts are scored, selected, and grouped, then concatenated into a dense FFN and refined by knowledge distillation from the MoE teacher. We eva","authors_text":"Gyeongman Kim, Haechan Kim, Jaewoong Cho, Jihun Yun, Joonghyun Bae, Junhyuck Kim","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-27T09:27:36Z","title":"Pruning and Distilling Mixture-of-Experts into Dense Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.28207","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:c2050936c5ec765442b46334284b28a33978bd236ae7a6be1d6828b5fc3500d4","target":"record","created_at":"2026-05-28T01:05:02Z","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":"7090822ff55e223e86fe029c9cc0c7fdaf081ad29bceb4a8aacd96e476e05ff1","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-27T09:27:36Z","title_canon_sha256":"fa44536ea11da5999129901f73cee698a743ea7e230fde4963b1a932ee13dd48"},"schema_version":"1.0","source":{"id":"2605.28207","kind":"arxiv","version":1}},"canonical_sha256":"92d002f810d2ff360376a1129f6e7e51cda07aa6cb14206f6ff55bfb7f183a2d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"92d002f810d2ff360376a1129f6e7e51cda07aa6cb14206f6ff55bfb7f183a2d","first_computed_at":"2026-05-28T01:05:02.618625Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-28T01:05:02.618625Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WZ2dMW7K38XlUGJRLj4lcfAM9JJ1JRg7aSm5xksYq53SogHucnCb8L8RXAPDxJ4lXW5VFOUQYe/kGxN6MA4xDg==","signature_status":"signed_v1","signed_at":"2026-05-28T01:05:02.619075Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.28207","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c2050936c5ec765442b46334284b28a33978bd236ae7a6be1d6828b5fc3500d4","sha256:b1e87e9674a105e61ea96ab9e123758415ecd6c137fab4b6786e3c49f8128a18"],"state_sha256":"69be5b9ed490918b25ba635d7fb19fb504ab36c5fda99470c2dbd3b4ef93b6aa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mhZ76jDvRBrrvUgg9KVCkF8ODgCTlYWmHHxSVM1PdIDXJfSUD3W1ub2BcLHoNfSfY3M5wsFNAK/xTo3fyZOpCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T12:19:33.095502Z","bundle_sha256":"1e8c9c5b7cc1fb2ccedc6590540ab95609b28762ecf1c8cecf9ab2f9093c71f3"}}