{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:DJVJPHJYUGWFWENWL5VIGWXWR7","short_pith_number":"pith:DJVJPHJY","canonical_record":{"source":{"id":"2507.00061","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-27T06:51:51Z","cross_cats_sorted":["cs.AI","eess.SP"],"title_canon_sha256":"c35e57c5d9bbf1e060efabcd4254b7b657bda7c0191852f986792c7c1991d311","abstract_canon_sha256":"abd820933b11d0f73ed44433ee3349bcf542478b63d4e4eb064922400992a800"},"schema_version":"1.0"},"canonical_sha256":"1a6a979d38a1ac5b11b65f6a835af68ff3fc53bbb97dceb731f401d4371d99a4","source":{"kind":"arxiv","id":"2507.00061","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.00061","created_at":"2026-07-05T11:29:36Z"},{"alias_kind":"arxiv_version","alias_value":"2507.00061v1","created_at":"2026-07-05T11:29:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.00061","created_at":"2026-07-05T11:29:36Z"},{"alias_kind":"pith_short_12","alias_value":"DJVJPHJYUGWF","created_at":"2026-07-05T11:29:36Z"},{"alias_kind":"pith_short_16","alias_value":"DJVJPHJYUGWFWENW","created_at":"2026-07-05T11:29:36Z"},{"alias_kind":"pith_short_8","alias_value":"DJVJPHJY","created_at":"2026-07-05T11:29:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:DJVJPHJYUGWFWENWL5VIGWXWR7","target":"record","payload":{"canonical_record":{"source":{"id":"2507.00061","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-27T06:51:51Z","cross_cats_sorted":["cs.AI","eess.SP"],"title_canon_sha256":"c35e57c5d9bbf1e060efabcd4254b7b657bda7c0191852f986792c7c1991d311","abstract_canon_sha256":"abd820933b11d0f73ed44433ee3349bcf542478b63d4e4eb064922400992a800"},"schema_version":"1.0"},"canonical_sha256":"1a6a979d38a1ac5b11b65f6a835af68ff3fc53bbb97dceb731f401d4371d99a4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:29:36.013885Z","signature_b64":"F77s7ZtOU4iGPLboFlkZ6g5R/+hwTPaYQl4NYlM/jlKShAsWhbN8HTGL9jddmaBJZT7imO72y76jh9bo2I5+Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1a6a979d38a1ac5b11b65f6a835af68ff3fc53bbb97dceb731f401d4371d99a4","last_reissued_at":"2026-07-05T11:29:36.013398Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:29:36.013398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.00061","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":"2026-07-05T11:29:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+0KwY1PcgtMLjHF+Go7g69kGCfpx82r/3/tLJsaZ/lK3bKscM3yacMSo97qFtDN2FUo6s6gcUOs1rE5pHCIdAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:50:42.569450Z"},"content_sha256":"c890650a22056b9f691154ef5aa059a7dcaf066da73f325107902c46be1496d3","schema_version":"1.0","event_id":"sha256:c890650a22056b9f691154ef5aa059a7dcaf066da73f325107902c46be1496d3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:DJVJPHJYUGWFWENWL5VIGWXWR7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Smooth-Distill: A Self-distillation Framework for Multitask Learning with Wearable Sensor Data","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","eess.SP"],"primary_cat":"cs.LG","authors_text":"Duc-Nghia Tran, Duc-Tan Tran, Hieu H. Pham, Hoang-Dieu Vu, Nicolas Vuillerme, Quang-Tu Pham","submitted_at":"2025-06-27T06:51:51Z","abstract_excerpt":"This paper introduces Smooth-Distill, a novel self-distillation framework designed to simultaneously perform human activity recognition (HAR) and sensor placement detection using wearable sensor data. The proposed approach utilizes a unified CNN-based architecture, MTL-net, which processes accelerometer data and branches into two outputs for each respective task. Unlike conventional distillation methods that require separate teacher and student models, the proposed framework utilizes a smoothed, historical version of the model itself as the teacher, significantly reducing training computationa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.00061","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/2507.00061/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":"2026-07-05T11:29:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E27x8vio6ckVePHafAJl6ljnCuJjZngWXnZn+8YeL2L2j1ObiD02M/nmW/WlNd1vVZlKS07chs+zg0usK6xPBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:50:42.570667Z"},"content_sha256":"6e2f85517f0bbb7daf27632bb2ba2d6191849b503a5166189c616d1613258baa","schema_version":"1.0","event_id":"sha256:6e2f85517f0bbb7daf27632bb2ba2d6191849b503a5166189c616d1613258baa"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DJVJPHJYUGWFWENWL5VIGWXWR7/bundle.json","state_url":"https://pith.science/pith/DJVJPHJYUGWFWENWL5VIGWXWR7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DJVJPHJYUGWFWENWL5VIGWXWR7/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":"2026-08-09T05:50:42Z","links":{"resolver":"https://pith.science/pith/DJVJPHJYUGWFWENWL5VIGWXWR7","bundle":"https://pith.science/pith/DJVJPHJYUGWFWENWL5VIGWXWR7/bundle.json","state":"https://pith.science/pith/DJVJPHJYUGWFWENWL5VIGWXWR7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DJVJPHJYUGWFWENWL5VIGWXWR7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:DJVJPHJYUGWFWENWL5VIGWXWR7","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":"abd820933b11d0f73ed44433ee3349bcf542478b63d4e4eb064922400992a800","cross_cats_sorted":["cs.AI","eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-27T06:51:51Z","title_canon_sha256":"c35e57c5d9bbf1e060efabcd4254b7b657bda7c0191852f986792c7c1991d311"},"schema_version":"1.0","source":{"id":"2507.00061","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.00061","created_at":"2026-07-05T11:29:36Z"},{"alias_kind":"arxiv_version","alias_value":"2507.00061v1","created_at":"2026-07-05T11:29:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.00061","created_at":"2026-07-05T11:29:36Z"},{"alias_kind":"pith_short_12","alias_value":"DJVJPHJYUGWF","created_at":"2026-07-05T11:29:36Z"},{"alias_kind":"pith_short_16","alias_value":"DJVJPHJYUGWFWENW","created_at":"2026-07-05T11:29:36Z"},{"alias_kind":"pith_short_8","alias_value":"DJVJPHJY","created_at":"2026-07-05T11:29:36Z"}],"graph_snapshots":[{"event_id":"sha256:6e2f85517f0bbb7daf27632bb2ba2d6191849b503a5166189c616d1613258baa","target":"graph","created_at":"2026-07-05T11:29:36Z","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/2507.00061/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper introduces Smooth-Distill, a novel self-distillation framework designed to simultaneously perform human activity recognition (HAR) and sensor placement detection using wearable sensor data. The proposed approach utilizes a unified CNN-based architecture, MTL-net, which processes accelerometer data and branches into two outputs for each respective task. Unlike conventional distillation methods that require separate teacher and student models, the proposed framework utilizes a smoothed, historical version of the model itself as the teacher, significantly reducing training computationa","authors_text":"Duc-Nghia Tran, Duc-Tan Tran, Hieu H. Pham, Hoang-Dieu Vu, Nicolas Vuillerme, Quang-Tu Pham","cross_cats":["cs.AI","eess.SP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-27T06:51:51Z","title":"Smooth-Distill: A Self-distillation Framework for Multitask Learning with Wearable Sensor Data"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.00061","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:c890650a22056b9f691154ef5aa059a7dcaf066da73f325107902c46be1496d3","target":"record","created_at":"2026-07-05T11:29:36Z","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":"abd820933b11d0f73ed44433ee3349bcf542478b63d4e4eb064922400992a800","cross_cats_sorted":["cs.AI","eess.SP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-06-27T06:51:51Z","title_canon_sha256":"c35e57c5d9bbf1e060efabcd4254b7b657bda7c0191852f986792c7c1991d311"},"schema_version":"1.0","source":{"id":"2507.00061","kind":"arxiv","version":1}},"canonical_sha256":"1a6a979d38a1ac5b11b65f6a835af68ff3fc53bbb97dceb731f401d4371d99a4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1a6a979d38a1ac5b11b65f6a835af68ff3fc53bbb97dceb731f401d4371d99a4","first_computed_at":"2026-07-05T11:29:36.013398Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:29:36.013398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"F77s7ZtOU4iGPLboFlkZ6g5R/+hwTPaYQl4NYlM/jlKShAsWhbN8HTGL9jddmaBJZT7imO72y76jh9bo2I5+Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T11:29:36.013885Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.00061","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c890650a22056b9f691154ef5aa059a7dcaf066da73f325107902c46be1496d3","sha256:6e2f85517f0bbb7daf27632bb2ba2d6191849b503a5166189c616d1613258baa"],"state_sha256":"c5c46c7ff5a73b3370196fd032178cb6088c7ed53c68d603311214f862bf7132"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q/NmV0eXv6HJzoUMKo7Is+t7gty3h1dkYUs5ODAIG/hWFmE5mjRia1A0r8LMHqLtoOU9Wz4gejzaLX/2I9BHBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T05:50:42.578214Z","bundle_sha256":"35eda026cff2ca3fca9f19deb696500987748487b1d145119959b2dbbf2c48d9"}}