{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:IYQSZFQLVSZ6OGDF722PA2LY4V","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":"da56c2a355c745e30233c985d60c85eda9f83557948dd3187cd77e31abea7c62","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-15T04:44:23Z","title_canon_sha256":"2ec93615c2e06b63a62ee668577f28a1302958b26016d5d7825df10d6b9b89ce"},"schema_version":"1.0","source":{"id":"2410.11268","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.11268","created_at":"2026-07-05T10:22:07Z"},{"alias_kind":"arxiv_version","alias_value":"2410.11268v2","created_at":"2026-07-05T10:22:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.11268","created_at":"2026-07-05T10:22:07Z"},{"alias_kind":"pith_short_12","alias_value":"IYQSZFQLVSZ6","created_at":"2026-07-05T10:22:07Z"},{"alias_kind":"pith_short_16","alias_value":"IYQSZFQLVSZ6OGDF","created_at":"2026-07-05T10:22:07Z"},{"alias_kind":"pith_short_8","alias_value":"IYQSZFQL","created_at":"2026-07-05T10:22:07Z"}],"graph_snapshots":[{"event_id":"sha256:bc8f2d3074c43c48c480ab2a17ad911ebaa7a57b350cffd26fed03beb66e7d00","target":"graph","created_at":"2026-07-05T10:22:07Z","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/2410.11268/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In-context learning has been recognized as a key factor in the success of Large Language Models (LLMs). It refers to the model's ability to learn patterns on the fly from provided in-context examples in the prompt during inference. Previous studies have demonstrated that the Transformer architecture used in LLMs can implement a single-step gradient descent update by processing in-context examples in a single forward pass. Recent work has further shown that, during in-context learning, a looped Transformer can implement multi-step gradient descent updates in forward passes. However, their theor","authors_text":"Bo Chen, Xiaoyu Li, Yingyu Liang, Zhao Song, Zhenmei Shi","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-15T04:44:23Z","title":"Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.11268","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:f90e68e3e410ebe335be875e8c01d479b81b137d57289ee22db70ef717cee56b","target":"record","created_at":"2026-07-05T10:22:07Z","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":"da56c2a355c745e30233c985d60c85eda9f83557948dd3187cd77e31abea7c62","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-10-15T04:44:23Z","title_canon_sha256":"2ec93615c2e06b63a62ee668577f28a1302958b26016d5d7825df10d6b9b89ce"},"schema_version":"1.0","source":{"id":"2410.11268","kind":"arxiv","version":2}},"canonical_sha256":"46212c960bacb3e71865feb4f06978e5666d8cc2a5a3c3436da98804bb99e2fb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"46212c960bacb3e71865feb4f06978e5666d8cc2a5a3c3436da98804bb99e2fb","first_computed_at":"2026-07-05T10:22:07.813391Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:22:07.813391Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"abJB97qJvFcnSBpIKvQ78N2izKpTWCD2WJUV+Puf9DhaAn0emebbRZhn3AeNHsz1SbcteCuwmZHRvneZs7fZCw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:22:07.814064Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.11268","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f90e68e3e410ebe335be875e8c01d479b81b137d57289ee22db70ef717cee56b","sha256:bc8f2d3074c43c48c480ab2a17ad911ebaa7a57b350cffd26fed03beb66e7d00"],"state_sha256":"0fa38d2cbc6cc7ef097dd3cc55cb68049579e304656b8b4bfdf61191160a2b14"}