{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:4IYGDDVPBD43DEDZLPVT4N7QKL","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":"823ddc22076c152e6600bc4dea92b14adeb1963e1243d53cf77e2446094825f4","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-05-19T13:30:34Z","title_canon_sha256":"19d49e86ddbe99119e8b36bff047b33ad1ee7628a30e36772994d19447edfaea"},"schema_version":"1.0","source":{"id":"2105.09121","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.09121","created_at":"2026-07-05T04:35:56Z"},{"alias_kind":"arxiv_version","alias_value":"2105.09121v3","created_at":"2026-07-05T04:35:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.09121","created_at":"2026-07-05T04:35:56Z"},{"alias_kind":"pith_short_12","alias_value":"4IYGDDVPBD43","created_at":"2026-07-05T04:35:56Z"},{"alias_kind":"pith_short_16","alias_value":"4IYGDDVPBD43DEDZ","created_at":"2026-07-05T04:35:56Z"},{"alias_kind":"pith_short_8","alias_value":"4IYGDDVP","created_at":"2026-07-05T04:35:56Z"}],"graph_snapshots":[{"event_id":"sha256:91975d708f47bfb775b385efa99f3d84cca4b834753b2406d4a54c6cc6c13995","target":"graph","created_at":"2026-07-05T04:35:56Z","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/2105.09121/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deploying deep learning models in time-critical applications with limited computational resources, for instance in edge computing systems and IoT networks, is a challenging task that often relies on dynamic inference methods such as early exiting. In this paper, we introduce a novel architecture for early exiting based on the vision transformer architecture, as well as a fine-tuning strategy that significantly increase the accuracy of early exit branches compared to conventional approaches while introducing less overhead. Through extensive experiments on image and audio classification as well ","authors_text":"Alexandros Iosifidis, Arian Bakhtiarnia, Qi Zhang","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-05-19T13:30:34Z","title":"Single-Layer Vision Transformers for More Accurate Early Exits with Less Overhead"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.09121","kind":"arxiv","version":3},"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:d725673b4681ee406b86357f1729885322c7df50b8e44908ae7a35f30e892dae","target":"record","created_at":"2026-07-05T04:35:56Z","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":"823ddc22076c152e6600bc4dea92b14adeb1963e1243d53cf77e2446094825f4","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2021-05-19T13:30:34Z","title_canon_sha256":"19d49e86ddbe99119e8b36bff047b33ad1ee7628a30e36772994d19447edfaea"},"schema_version":"1.0","source":{"id":"2105.09121","kind":"arxiv","version":3}},"canonical_sha256":"e230618eaf08f9b190795beb3e37f052fac70145461c1849abbdb37dfeccac65","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e230618eaf08f9b190795beb3e37f052fac70145461c1849abbdb37dfeccac65","first_computed_at":"2026-07-05T04:35:56.109776Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:35:56.109776Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"p+HWnbh0d3XIgavFmFH0hmsYq7b5g/CE3WJlg2fL3QsLWiQO3e14U+hVQTj3rpGc6KcTZQzwo2akUpsJmIeZCg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:35:56.110261Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.09121","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d725673b4681ee406b86357f1729885322c7df50b8e44908ae7a35f30e892dae","sha256:91975d708f47bfb775b385efa99f3d84cca4b834753b2406d4a54c6cc6c13995"],"state_sha256":"be63a504ff676ea7f9f4d304ab02ccf03daa20108ed30584e23172b614e36208"}