{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XUHHR7BSFRW4RIDEKTYWLV4LXJ","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":"a3902538de41a54669309841b30bd6f2cbcc80f50907b25a2278130318d80b32","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-01T11:39:04Z","title_canon_sha256":"83b112e891205a57208300702c147ad169e1ebee85d2aa06883e58b57d3b19c9"},"schema_version":"1.0","source":{"id":"2402.00518","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00518","created_at":"2026-07-05T07:40:12Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00518v1","created_at":"2026-07-05T07:40:12Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00518","created_at":"2026-07-05T07:40:12Z"},{"alias_kind":"pith_short_12","alias_value":"XUHHR7BSFRW4","created_at":"2026-07-05T07:40:12Z"},{"alias_kind":"pith_short_16","alias_value":"XUHHR7BSFRW4RIDE","created_at":"2026-07-05T07:40:12Z"},{"alias_kind":"pith_short_8","alias_value":"XUHHR7BS","created_at":"2026-07-05T07:40:12Z"}],"graph_snapshots":[{"event_id":"sha256:b07f52f9045df9c9170a7294a6ffdbbdac38f0b973424c1000e99cfa71cf2d4a","target":"graph","created_at":"2026-07-05T07:40:12Z","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/2402.00518/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This work introduces EE-Tuning, a lightweight and economical solution to training/tuning early-exit large language models (LLMs). In contrast to the common approach of full-parameter pre-training, EE-Tuning augments any pre-trained (and possibly fine-tuned) standard LLM with additional early-exit layers that are tuned in a parameter-efficient manner, which requires significantly less computational resources and training data. Our implementation of EE-Tuning achieves outstanding training efficiency via extensive performance optimizations, as well as scalability due to its full compatibility wit","authors_text":"Bolin Ding, Jingren Zhou, Xuchen Pan, Yaliang Li, Yanxi Chen","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-01T11:39:04Z","title":"EE-Tuning: An Economical yet Scalable Solution for Tuning Early-Exit Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00518","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:f3f4252983c0ed34d4c0bc37e0529ca60036a1776a5e504f81fb619b80e19188","target":"record","created_at":"2026-07-05T07:40:12Z","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":"a3902538de41a54669309841b30bd6f2cbcc80f50907b25a2278130318d80b32","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-01T11:39:04Z","title_canon_sha256":"83b112e891205a57208300702c147ad169e1ebee85d2aa06883e58b57d3b19c9"},"schema_version":"1.0","source":{"id":"2402.00518","kind":"arxiv","version":1}},"canonical_sha256":"bd0e78fc322c6dc8a06454f165d78bba6e50d4297029026bbaef2f680efe809d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bd0e78fc322c6dc8a06454f165d78bba6e50d4297029026bbaef2f680efe809d","first_computed_at":"2026-07-05T07:40:12.915017Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:40:12.915017Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"KiDFjLJAuHeNWyjByICPJGxiWqC/+YSRrg7LH+0Nq5POxt7EbE0Z59ZHl05H1Cf9XFpsYm41Yn9onY7xjW6uAA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:40:12.915550Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.00518","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f3f4252983c0ed34d4c0bc37e0529ca60036a1776a5e504f81fb619b80e19188","sha256:b07f52f9045df9c9170a7294a6ffdbbdac38f0b973424c1000e99cfa71cf2d4a"],"state_sha256":"da28ffb2620eed36ae9e2adae249944b5385c971218758bb4c129f8bdd002a37"}