{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SWIXSYO5ZSKY5VBSE3LGCJAA6Q","short_pith_number":"pith:SWIXSYO5","canonical_record":{"source":{"id":"2509.09931","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2025-09-12T02:33:01Z","cross_cats_sorted":[],"title_canon_sha256":"7b996fe9a49d13771f4b5bdb97362c5bdf7f2055a7792675d67f9a0abb4761c0","abstract_canon_sha256":"398d4b83c1e2f2430beef212352c3d375fa79b4b09ff12c1a48b4ae216884808"},"schema_version":"1.0"},"canonical_sha256":"95917961ddcc958ed43226d6612400f431d0f9da103d344492807bdcedfcaf80","source":{"kind":"arxiv","id":"2509.09931","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.09931","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"arxiv_version","alias_value":"2509.09931v1","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.09931","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_12","alias_value":"SWIXSYO5ZSKY","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_16","alias_value":"SWIXSYO5ZSKY5VBS","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_8","alias_value":"SWIXSYO5","created_at":"2026-07-05T12:09:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SWIXSYO5ZSKY5VBSE3LGCJAA6Q","target":"record","payload":{"canonical_record":{"source":{"id":"2509.09931","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2025-09-12T02:33:01Z","cross_cats_sorted":[],"title_canon_sha256":"7b996fe9a49d13771f4b5bdb97362c5bdf7f2055a7792675d67f9a0abb4761c0","abstract_canon_sha256":"398d4b83c1e2f2430beef212352c3d375fa79b4b09ff12c1a48b4ae216884808"},"schema_version":"1.0"},"canonical_sha256":"95917961ddcc958ed43226d6612400f431d0f9da103d344492807bdcedfcaf80","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:09:52.337113Z","signature_b64":"TmSZlrFPWIVYpLCVbs77bqB69vN1WZTfgUqoY8ibsUduj6XjxP4nztFvwyPO7x2XKZFh3/XGi+cE0X2owyjyBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"95917961ddcc958ed43226d6612400f431d0f9da103d344492807bdcedfcaf80","last_reissued_at":"2026-07-05T12:09:52.336627Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:09:52.336627Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2509.09931","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":"2026-07-05T12:09:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Yq3nVl41GC9OE+4x+vmLwCJ07w4GfHunElKl77WaQ21rUwpta+mtawWEyN8kPsbKAMNO7Op7Vouv3E+mBz27Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T21:51:38.628998Z"},"content_sha256":"4a814464008c0beda0fe349f1acddd723e730d6dcaf11f78107dc3089d5b071e","schema_version":"1.0","event_id":"sha256:4a814464008c0beda0fe349f1acddd723e730d6dcaf11f78107dc3089d5b071e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SWIXSYO5ZSKY5VBSE3LGCJAA6Q","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Acoustic Scene Classification Using CNN-GRU Model Without Knowledge Distillation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"eess.AS","authors_text":"Ee-Leng Tan, Haowen Li, Jun Wei Yeow, Santi Peksi, Woon-Seng Gan, Ziyi Yang","submitted_at":"2025-09-12T02:33:01Z","abstract_excerpt":"In this technical report, we present the SNTL-NTU team's Task 1 submission for the Low-Complexity Acoustic Scenes and Events (DCASE) 2025 challenge. This submission departs from the typical application of knowledge distillation from a teacher to a student model, aiming to achieve high performance with limited complexity. The proposed model is based on a CNN-GRU model and is trained solely using the TAU Urban Acoustic Scene 2022 Mobile development dataset, without utilizing any external datasets, except for MicIRP, which is used for device impulse response (DIR) augmentation. The proposed model"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.09931","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/2509.09931/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":"2026-07-05T12:09:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zLKC37yZi7ZuefR0+wJyxdX1orVF0m0KD/qcPmMUNPneUZCvJN4tvGrVAvICMOP/dHt0LZAdMv6dCjlduKApAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T21:51:38.629501Z"},"content_sha256":"bfc7914b1b340e7980cc3563335d24489d64f0be1171d623586779ffece7fac6","schema_version":"1.0","event_id":"sha256:bfc7914b1b340e7980cc3563335d24489d64f0be1171d623586779ffece7fac6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SWIXSYO5ZSKY5VBSE3LGCJAA6Q/bundle.json","state_url":"https://pith.science/pith/SWIXSYO5ZSKY5VBSE3LGCJAA6Q/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SWIXSYO5ZSKY5VBSE3LGCJAA6Q/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":"2026-08-04T21:51:38Z","links":{"resolver":"https://pith.science/pith/SWIXSYO5ZSKY5VBSE3LGCJAA6Q","bundle":"https://pith.science/pith/SWIXSYO5ZSKY5VBSE3LGCJAA6Q/bundle.json","state":"https://pith.science/pith/SWIXSYO5ZSKY5VBSE3LGCJAA6Q/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SWIXSYO5ZSKY5VBSE3LGCJAA6Q/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SWIXSYO5ZSKY5VBSE3LGCJAA6Q","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":"398d4b83c1e2f2430beef212352c3d375fa79b4b09ff12c1a48b4ae216884808","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2025-09-12T02:33:01Z","title_canon_sha256":"7b996fe9a49d13771f4b5bdb97362c5bdf7f2055a7792675d67f9a0abb4761c0"},"schema_version":"1.0","source":{"id":"2509.09931","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.09931","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"arxiv_version","alias_value":"2509.09931v1","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.09931","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_12","alias_value":"SWIXSYO5ZSKY","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_16","alias_value":"SWIXSYO5ZSKY5VBS","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_8","alias_value":"SWIXSYO5","created_at":"2026-07-05T12:09:52Z"}],"graph_snapshots":[{"event_id":"sha256:bfc7914b1b340e7980cc3563335d24489d64f0be1171d623586779ffece7fac6","target":"graph","created_at":"2026-07-05T12:09:52Z","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/2509.09931/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this technical report, we present the SNTL-NTU team's Task 1 submission for the Low-Complexity Acoustic Scenes and Events (DCASE) 2025 challenge. This submission departs from the typical application of knowledge distillation from a teacher to a student model, aiming to achieve high performance with limited complexity. The proposed model is based on a CNN-GRU model and is trained solely using the TAU Urban Acoustic Scene 2022 Mobile development dataset, without utilizing any external datasets, except for MicIRP, which is used for device impulse response (DIR) augmentation. The proposed model","authors_text":"Ee-Leng Tan, Haowen Li, Jun Wei Yeow, Santi Peksi, Woon-Seng Gan, Ziyi Yang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2025-09-12T02:33:01Z","title":"Acoustic Scene Classification Using CNN-GRU Model Without Knowledge Distillation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.09931","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":"sha256:4a814464008c0beda0fe349f1acddd723e730d6dcaf11f78107dc3089d5b071e","target":"record","created_at":"2026-07-05T12:09:52Z","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":"398d4b83c1e2f2430beef212352c3d375fa79b4b09ff12c1a48b4ae216884808","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.AS","submitted_at":"2025-09-12T02:33:01Z","title_canon_sha256":"7b996fe9a49d13771f4b5bdb97362c5bdf7f2055a7792675d67f9a0abb4761c0"},"schema_version":"1.0","source":{"id":"2509.09931","kind":"arxiv","version":1}},"canonical_sha256":"95917961ddcc958ed43226d6612400f431d0f9da103d344492807bdcedfcaf80","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"95917961ddcc958ed43226d6612400f431d0f9da103d344492807bdcedfcaf80","first_computed_at":"2026-07-05T12:09:52.336627Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:09:52.336627Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"TmSZlrFPWIVYpLCVbs77bqB69vN1WZTfgUqoY8ibsUduj6XjxP4nztFvwyPO7x2XKZFh3/XGi+cE0X2owyjyBA==","signature_status":"signed_v1","signed_at":"2026-07-05T12:09:52.337113Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.09931","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4a814464008c0beda0fe349f1acddd723e730d6dcaf11f78107dc3089d5b071e","sha256:bfc7914b1b340e7980cc3563335d24489d64f0be1171d623586779ffece7fac6"],"state_sha256":"0ba87c3ac4fa62ef8e2c0efeeaf12d72e9976a2f135d94f5cad8e2267802624e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kyLiziZyVKE4YJSWw8cZWUPL6XaeFzRhmnQV5UYQ1BuvQVlFVmmlHsp/0dO8oXroHfq/cm/HwbUmQOYX6HVkBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T21:51:38.633407Z","bundle_sha256":"929f8cf50234f749d27c50436e91fea78fbc46e5a9fc02836568155decf429cf"}}