{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:F4ZX5Y46KERJZUQVGCTZ4HWV42","short_pith_number":"pith:F4ZX5Y46","canonical_record":{"source":{"id":"2308.04243","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-08T13:17:20Z","cross_cats_sorted":[],"title_canon_sha256":"cf4bffc040d2db7642312483d484c1d6a9f20eda2e84a2980bc3c66dc700dcbb","abstract_canon_sha256":"418784bd9a9f5a7314480dd287130ce8ff2998e49add309269ecfc774ad118c3"},"schema_version":"1.0"},"canonical_sha256":"2f337ee39e51229cd21530a79e1ed5e69560e2beea02ca549411283df8d4d8d5","source":{"kind":"arxiv","id":"2308.04243","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.04243","created_at":"2026-07-05T06:39:24Z"},{"alias_kind":"arxiv_version","alias_value":"2308.04243v1","created_at":"2026-07-05T06:39:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.04243","created_at":"2026-07-05T06:39:24Z"},{"alias_kind":"pith_short_12","alias_value":"F4ZX5Y46KERJ","created_at":"2026-07-05T06:39:24Z"},{"alias_kind":"pith_short_16","alias_value":"F4ZX5Y46KERJZUQV","created_at":"2026-07-05T06:39:24Z"},{"alias_kind":"pith_short_8","alias_value":"F4ZX5Y46","created_at":"2026-07-05T06:39:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:F4ZX5Y46KERJZUQVGCTZ4HWV42","target":"record","payload":{"canonical_record":{"source":{"id":"2308.04243","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-08T13:17:20Z","cross_cats_sorted":[],"title_canon_sha256":"cf4bffc040d2db7642312483d484c1d6a9f20eda2e84a2980bc3c66dc700dcbb","abstract_canon_sha256":"418784bd9a9f5a7314480dd287130ce8ff2998e49add309269ecfc774ad118c3"},"schema_version":"1.0"},"canonical_sha256":"2f337ee39e51229cd21530a79e1ed5e69560e2beea02ca549411283df8d4d8d5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:39:24.549557Z","signature_b64":"y/Y1B/9Hx6o32hciiE4budoVCwcjK0Cbs5wj+AS8dq9qukfeD2IJKUd1ye+P/+ho3EaAPae3z/IGjjZyyzjADg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2f337ee39e51229cd21530a79e1ed5e69560e2beea02ca549411283df8d4d8d5","last_reissued_at":"2026-07-05T06:39:24.548932Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:39:24.548932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.04243","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":"2026-07-05T06:39:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lurU1eVQ+BwvaFmaRWU1IVsiFDy6yI1Jmc1YH3XoAFZ4lLEn6oAmkqbJ92+Y8jMbLyg4q+zosYBSnkTvdL3lBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T18:38:43.502117Z"},"content_sha256":"fa73e18e044251d83f9b18f70ab7af9280d67176931177351380bf5b62bc5ace","schema_version":"1.0","event_id":"sha256:fa73e18e044251d83f9b18f70ab7af9280d67176931177351380bf5b62bc5ace"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:F4ZX5Y46KERJZUQVGCTZ4HWV42","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AICSD: Adaptive Inter-Class Similarity Distillation for Semantic Segmentation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Amir M. Mansourian, Rozhan Ahmadi, Shohreh Kasaei","submitted_at":"2023-08-08T13:17:20Z","abstract_excerpt":"In recent years, deep neural networks have achieved remarkable accuracy in computer vision tasks. With inference time being a crucial factor, particularly in dense prediction tasks such as semantic segmentation, knowledge distillation has emerged as a successful technique for improving the accuracy of lightweight student networks. The existing methods often neglect the information in channels and among different classes. To overcome these limitations, this paper proposes a novel method called Inter-Class Similarity Distillation (ICSD) for the purpose of knowledge distillation. The proposed met"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.04243","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/2308.04243/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":"2026-07-05T06:39:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WdwVfCwnrsVCyRUGwuwbWZ0TDH0PEk7LpSESSebjA7L9/LPRTyf6wcpGzDUUuaAYaFXoaJX38kbvw4RYPrkgDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T18:38:43.502672Z"},"content_sha256":"78c7b3e896678a46332a18a752fb4faa6b084a9d42f4078254b572a64cbd59b2","schema_version":"1.0","event_id":"sha256:78c7b3e896678a46332a18a752fb4faa6b084a9d42f4078254b572a64cbd59b2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/F4ZX5Y46KERJZUQVGCTZ4HWV42/bundle.json","state_url":"https://pith.science/pith/F4ZX5Y46KERJZUQVGCTZ4HWV42/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/F4ZX5Y46KERJZUQVGCTZ4HWV42/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":"2026-08-03T18:38:43Z","links":{"resolver":"https://pith.science/pith/F4ZX5Y46KERJZUQVGCTZ4HWV42","bundle":"https://pith.science/pith/F4ZX5Y46KERJZUQVGCTZ4HWV42/bundle.json","state":"https://pith.science/pith/F4ZX5Y46KERJZUQVGCTZ4HWV42/state.json","well_known_bundle":"https://pith.science/.well-known/pith/F4ZX5Y46KERJZUQVGCTZ4HWV42/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:F4ZX5Y46KERJZUQVGCTZ4HWV42","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":"418784bd9a9f5a7314480dd287130ce8ff2998e49add309269ecfc774ad118c3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-08T13:17:20Z","title_canon_sha256":"cf4bffc040d2db7642312483d484c1d6a9f20eda2e84a2980bc3c66dc700dcbb"},"schema_version":"1.0","source":{"id":"2308.04243","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.04243","created_at":"2026-07-05T06:39:24Z"},{"alias_kind":"arxiv_version","alias_value":"2308.04243v1","created_at":"2026-07-05T06:39:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.04243","created_at":"2026-07-05T06:39:24Z"},{"alias_kind":"pith_short_12","alias_value":"F4ZX5Y46KERJ","created_at":"2026-07-05T06:39:24Z"},{"alias_kind":"pith_short_16","alias_value":"F4ZX5Y46KERJZUQV","created_at":"2026-07-05T06:39:24Z"},{"alias_kind":"pith_short_8","alias_value":"F4ZX5Y46","created_at":"2026-07-05T06:39:24Z"}],"graph_snapshots":[{"event_id":"sha256:78c7b3e896678a46332a18a752fb4faa6b084a9d42f4078254b572a64cbd59b2","target":"graph","created_at":"2026-07-05T06:39:24Z","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/2308.04243/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, deep neural networks have achieved remarkable accuracy in computer vision tasks. With inference time being a crucial factor, particularly in dense prediction tasks such as semantic segmentation, knowledge distillation has emerged as a successful technique for improving the accuracy of lightweight student networks. The existing methods often neglect the information in channels and among different classes. To overcome these limitations, this paper proposes a novel method called Inter-Class Similarity Distillation (ICSD) for the purpose of knowledge distillation. The proposed met","authors_text":"Amir M. Mansourian, Rozhan Ahmadi, Shohreh Kasaei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-08T13:17:20Z","title":"AICSD: Adaptive Inter-Class Similarity Distillation for Semantic Segmentation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.04243","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:fa73e18e044251d83f9b18f70ab7af9280d67176931177351380bf5b62bc5ace","target":"record","created_at":"2026-07-05T06:39:24Z","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":"418784bd9a9f5a7314480dd287130ce8ff2998e49add309269ecfc774ad118c3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-08-08T13:17:20Z","title_canon_sha256":"cf4bffc040d2db7642312483d484c1d6a9f20eda2e84a2980bc3c66dc700dcbb"},"schema_version":"1.0","source":{"id":"2308.04243","kind":"arxiv","version":1}},"canonical_sha256":"2f337ee39e51229cd21530a79e1ed5e69560e2beea02ca549411283df8d4d8d5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2f337ee39e51229cd21530a79e1ed5e69560e2beea02ca549411283df8d4d8d5","first_computed_at":"2026-07-05T06:39:24.548932Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:39:24.548932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"y/Y1B/9Hx6o32hciiE4budoVCwcjK0Cbs5wj+AS8dq9qukfeD2IJKUd1ye+P/+ho3EaAPae3z/IGjjZyyzjADg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:39:24.549557Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.04243","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fa73e18e044251d83f9b18f70ab7af9280d67176931177351380bf5b62bc5ace","sha256:78c7b3e896678a46332a18a752fb4faa6b084a9d42f4078254b572a64cbd59b2"],"state_sha256":"8a067051f757b71308430e2ba1cdbeb88c8fd4aa65f31dbf1aa86d52f25b2d53"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8+QqggODgC0NPpTfebC7SlGgN1lCF1McNDX7MqIrn6FM//yXGhxqhB6fpF3+jlqAqed8cldXUZ10h68kz70jCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T18:38:43.506353Z","bundle_sha256":"752e4310fcd4fb57f6bacd29ce150cacf9753d91a4ae49ce2e059ac306425d97"}}