{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NH6DEQ4PHHQFCQASODCS5RZR55","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":"77ba69ce483fa6b2672ec2e8f654b7364f9372f88551c662707d79e2528b43ab","cross_cats_sorted":["cs.CV","cs.IT","cs.LG","eess.IV","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-12T02:12:41Z","title_canon_sha256":"b14ea8a551d0f7a9e6c3fa42d3578dee5605accad93ca8e83b074fb3457817f6"},"schema_version":"1.0","source":{"id":"2411.07483","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.07483","created_at":"2026-07-05T10:44:19Z"},{"alias_kind":"arxiv_version","alias_value":"2411.07483v2","created_at":"2026-07-05T10:44:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.07483","created_at":"2026-07-05T10:44:19Z"},{"alias_kind":"pith_short_12","alias_value":"NH6DEQ4PHHQF","created_at":"2026-07-05T10:44:19Z"},{"alias_kind":"pith_short_16","alias_value":"NH6DEQ4PHHQFCQAS","created_at":"2026-07-05T10:44:19Z"},{"alias_kind":"pith_short_8","alias_value":"NH6DEQ4P","created_at":"2026-07-05T10:44:19Z"}],"graph_snapshots":[{"event_id":"sha256:00e1993cf00af1f5e286e9e8178698ed686a84bad4c43ae28c813daf78568148","target":"graph","created_at":"2026-07-05T10:44:19Z","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/2411.07483/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Knowledge distillation deploys complex machine learning models in resource-constrained environments by training a smaller student model to emulate internal representations of a complex teacher model. However, the teacher's representations can also encode nuisance or additional information not relevant to the downstream task. Distilling such irrelevant information can actually impede the performance of a capacity-limited student model. This observation motivates our primary question: What are the information-theoretic limits of knowledge distillation? To this end, we leverage Partial Informatio","authors_text":"Barproda Halder, Faisal Hamman, Ilia Sucholutsky, Pasan Dissanayake, Qiuyi Zhang, Sanghamitra Dutta","cross_cats":["cs.CV","cs.IT","cs.LG","eess.IV","math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-12T02:12:41Z","title":"Quantifying Knowledge Distillation Using Partial Information Decomposition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.07483","kind":"arxiv","version":2},"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":"sha256:037285c87dc4594d7e83fe8dfa8f1395dab95127a00403d80d441a045064a440","target":"record","created_at":"2026-07-05T10:44:19Z","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":"77ba69ce483fa6b2672ec2e8f654b7364f9372f88551c662707d79e2528b43ab","cross_cats_sorted":["cs.CV","cs.IT","cs.LG","eess.IV","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"stat.ML","submitted_at":"2024-11-12T02:12:41Z","title_canon_sha256":"b14ea8a551d0f7a9e6c3fa42d3578dee5605accad93ca8e83b074fb3457817f6"},"schema_version":"1.0","source":{"id":"2411.07483","kind":"arxiv","version":2}},"canonical_sha256":"69fc32438f39e051401270c52ec731ef726c2e783a6971dd84b437ab2ed49468","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"69fc32438f39e051401270c52ec731ef726c2e783a6971dd84b437ab2ed49468","first_computed_at":"2026-07-05T10:44:19.773713Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:44:19.773713Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kcGLmMCQQO5sj0C/tEWEFMYFs0R4bf2e2eMAXhG0D2/mzgiw43Nz2rlG7F/33ujcrn/TZ7EmSTKAOcqufn7zCg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:44:19.774143Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.07483","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:037285c87dc4594d7e83fe8dfa8f1395dab95127a00403d80d441a045064a440","sha256:00e1993cf00af1f5e286e9e8178698ed686a84bad4c43ae28c813daf78568148"],"state_sha256":"ce6b56602012f8589d3a78ae87faa10a4c5dba0c6bab7ddb1582d4615651a9af"}