{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:YYS6RDWJPRDJ3AAF3ZEDMYIFVH","short_pith_number":"pith:YYS6RDWJ","canonical_record":{"source":{"id":"2312.13211","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-12-20T17:27:25Z","cross_cats_sorted":[],"title_canon_sha256":"51060e434ccc7844075c840dce7fb04d31e229ea61e2c605b7990a01905c9da9","abstract_canon_sha256":"c76c218e1602c701441607cb97db13c06e6d0539218da6dafe023eb43779feef"},"schema_version":"1.0"},"canonical_sha256":"c625e88ec97c469d8005de48366105a9cc13e6f06d2e1d86c08d54a86a07a29f","source":{"kind":"arxiv","id":"2312.13211","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.13211","created_at":"2026-07-05T07:26:33Z"},{"alias_kind":"arxiv_version","alias_value":"2312.13211v1","created_at":"2026-07-05T07:26:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.13211","created_at":"2026-07-05T07:26:33Z"},{"alias_kind":"pith_short_12","alias_value":"YYS6RDWJPRDJ","created_at":"2026-07-05T07:26:33Z"},{"alias_kind":"pith_short_16","alias_value":"YYS6RDWJPRDJ3AAF","created_at":"2026-07-05T07:26:33Z"},{"alias_kind":"pith_short_8","alias_value":"YYS6RDWJ","created_at":"2026-07-05T07:26:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:YYS6RDWJPRDJ3AAF3ZEDMYIFVH","target":"record","payload":{"canonical_record":{"source":{"id":"2312.13211","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-12-20T17:27:25Z","cross_cats_sorted":[],"title_canon_sha256":"51060e434ccc7844075c840dce7fb04d31e229ea61e2c605b7990a01905c9da9","abstract_canon_sha256":"c76c218e1602c701441607cb97db13c06e6d0539218da6dafe023eb43779feef"},"schema_version":"1.0"},"canonical_sha256":"c625e88ec97c469d8005de48366105a9cc13e6f06d2e1d86c08d54a86a07a29f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:26:33.439633Z","signature_b64":"iBL4KURE5IKTSuJGISxiRNhjDwoiPu9+r38qVYWxeBUVutnMKvAzBzkzw6lTs5fRdfdGwj9cyTN5HhyPl5InAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c625e88ec97c469d8005de48366105a9cc13e6f06d2e1d86c08d54a86a07a29f","last_reissued_at":"2026-07-05T07:26:33.439153Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:26:33.439153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.13211","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":"2026-07-05T07:26:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2jUGGJV1z4ourqKjXubXoZCmBLcxdxrp+ewsaSuv5jEAZID1Rut6+7OdXlXNDrGPJ0IEX2q1sweSWl8qgsZLDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T05:12:18.435061Z"},"content_sha256":"2a4f4ad4c55ac65614bb9029896897d97ae0a408d625e804e38fe5a4c1d90cf1","schema_version":"1.0","event_id":"sha256:2a4f4ad4c55ac65614bb9029896897d97ae0a408d625e804e38fe5a4c1d90cf1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:YYS6RDWJPRDJ3AAF3ZEDMYIFVH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DSFormer: Effective Compression of Text-Transformers by Dense-Sparse Weight Factorization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Pratyush Kumar, Rahul Chand, Yashoteja Prabhu","submitted_at":"2023-12-20T17:27:25Z","abstract_excerpt":"With the tremendous success of large transformer models in natural language understanding, down-sizing them for cost-effective deployments has become critical. Recent studies have explored the low-rank weight factorization techniques which are efficient to train, and apply out-of-the-box to any transformer architecture. Unfortunately, the low-rank assumption tends to be over-restrictive and hinders the expressiveness of the compressed model. This paper proposes, DSFormer, a simple alternative factorization scheme which expresses a target weight matrix as the product of a small dense and a semi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.13211","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/2312.13211/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":"2026-07-05T07:26:33Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iGLgp9ogpPKIe23K8IV0Rd46CSL+SPf5HA/CMOj/+9zhQYhjKZ2nrHaJTHmOQl+GHtXnFsRQMo3s19YuvSARBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T05:12:18.435453Z"},"content_sha256":"f3abc61a9f733a4ebdaf1f8f2816cabb12453dc6f2f7c5d4580bdb6c67aa62d7","schema_version":"1.0","event_id":"sha256:f3abc61a9f733a4ebdaf1f8f2816cabb12453dc6f2f7c5d4580bdb6c67aa62d7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YYS6RDWJPRDJ3AAF3ZEDMYIFVH/bundle.json","state_url":"https://pith.science/pith/YYS6RDWJPRDJ3AAF3ZEDMYIFVH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YYS6RDWJPRDJ3AAF3ZEDMYIFVH/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":"2026-07-07T05:12:18Z","links":{"resolver":"https://pith.science/pith/YYS6RDWJPRDJ3AAF3ZEDMYIFVH","bundle":"https://pith.science/pith/YYS6RDWJPRDJ3AAF3ZEDMYIFVH/bundle.json","state":"https://pith.science/pith/YYS6RDWJPRDJ3AAF3ZEDMYIFVH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YYS6RDWJPRDJ3AAF3ZEDMYIFVH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:YYS6RDWJPRDJ3AAF3ZEDMYIFVH","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":"c76c218e1602c701441607cb97db13c06e6d0539218da6dafe023eb43779feef","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-12-20T17:27:25Z","title_canon_sha256":"51060e434ccc7844075c840dce7fb04d31e229ea61e2c605b7990a01905c9da9"},"schema_version":"1.0","source":{"id":"2312.13211","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.13211","created_at":"2026-07-05T07:26:33Z"},{"alias_kind":"arxiv_version","alias_value":"2312.13211v1","created_at":"2026-07-05T07:26:33Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.13211","created_at":"2026-07-05T07:26:33Z"},{"alias_kind":"pith_short_12","alias_value":"YYS6RDWJPRDJ","created_at":"2026-07-05T07:26:33Z"},{"alias_kind":"pith_short_16","alias_value":"YYS6RDWJPRDJ3AAF","created_at":"2026-07-05T07:26:33Z"},{"alias_kind":"pith_short_8","alias_value":"YYS6RDWJ","created_at":"2026-07-05T07:26:33Z"}],"graph_snapshots":[{"event_id":"sha256:f3abc61a9f733a4ebdaf1f8f2816cabb12453dc6f2f7c5d4580bdb6c67aa62d7","target":"graph","created_at":"2026-07-05T07:26:33Z","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/2312.13211/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the tremendous success of large transformer models in natural language understanding, down-sizing them for cost-effective deployments has become critical. Recent studies have explored the low-rank weight factorization techniques which are efficient to train, and apply out-of-the-box to any transformer architecture. Unfortunately, the low-rank assumption tends to be over-restrictive and hinders the expressiveness of the compressed model. This paper proposes, DSFormer, a simple alternative factorization scheme which expresses a target weight matrix as the product of a small dense and a semi","authors_text":"Pratyush Kumar, Rahul Chand, Yashoteja Prabhu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-12-20T17:27:25Z","title":"DSFormer: Effective Compression of Text-Transformers by Dense-Sparse Weight Factorization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.13211","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":"sha256:2a4f4ad4c55ac65614bb9029896897d97ae0a408d625e804e38fe5a4c1d90cf1","target":"record","created_at":"2026-07-05T07:26:33Z","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":"c76c218e1602c701441607cb97db13c06e6d0539218da6dafe023eb43779feef","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-12-20T17:27:25Z","title_canon_sha256":"51060e434ccc7844075c840dce7fb04d31e229ea61e2c605b7990a01905c9da9"},"schema_version":"1.0","source":{"id":"2312.13211","kind":"arxiv","version":1}},"canonical_sha256":"c625e88ec97c469d8005de48366105a9cc13e6f06d2e1d86c08d54a86a07a29f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c625e88ec97c469d8005de48366105a9cc13e6f06d2e1d86c08d54a86a07a29f","first_computed_at":"2026-07-05T07:26:33.439153Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:26:33.439153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iBL4KURE5IKTSuJGISxiRNhjDwoiPu9+r38qVYWxeBUVutnMKvAzBzkzw6lTs5fRdfdGwj9cyTN5HhyPl5InAA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:26:33.439633Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.13211","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2a4f4ad4c55ac65614bb9029896897d97ae0a408d625e804e38fe5a4c1d90cf1","sha256:f3abc61a9f733a4ebdaf1f8f2816cabb12453dc6f2f7c5d4580bdb6c67aa62d7"],"state_sha256":"ebf49534816dadfab47a4a0fef360b7f34f99b389e464885aed031412a89f35d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"X+w+TiRel4CfWUc4a5J0xy5SyeCwzEnGvaJHd6d26eM4PFFATrV99lRFtNJJStxeWVrUfINtXZS5ldT3Xd8ECw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T05:12:18.437696Z","bundle_sha256":"2faff6c9a39d2ae84d908ec214dfeb090cf3f4c33caf9c1270cbf0f10863f557"}}