{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:D22TNB3MJLLWOG35OP2QY7KIZE","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":"c2bcf8ad1ed5a0c83619f0eb2d8c14c5c146ee728e37f9988acb6d2517b7791a","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-03T17:39:29Z","title_canon_sha256":"a95378ff52452e8114f78bdf20c0624c7cb6d52899f38fef54df1c09b3d02e87"},"schema_version":"1.0","source":{"id":"2606.05134","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.05134","created_at":"2026-06-04T01:10:07Z"},{"alias_kind":"arxiv_version","alias_value":"2606.05134v1","created_at":"2026-06-04T01:10:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.05134","created_at":"2026-06-04T01:10:07Z"},{"alias_kind":"pith_short_12","alias_value":"D22TNB3MJLLW","created_at":"2026-06-04T01:10:07Z"},{"alias_kind":"pith_short_16","alias_value":"D22TNB3MJLLWOG35","created_at":"2026-06-04T01:10:07Z"},{"alias_kind":"pith_short_8","alias_value":"D22TNB3M","created_at":"2026-06-04T01:10:07Z"}],"graph_snapshots":[{"event_id":"sha256:17a578cd7453382b85fd89ef2e7c1ca088605897a1d0036fb486dab602596bdd","target":"graph","created_at":"2026-06-04T01:10:07Z","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/2606.05134/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep active learning has previously been explored for LLM in-context sample selection, but not with methods that utilise recent advances in understanding of transformer activations. In this paper, we test the hypothesis that model activations could provide a fine-grained signal to optimise the selection of in-context examples. We present the most comprehensive analysis to date of MLP activation-based deep active learning methods applied to in-context learning, including how different attention masking strategies impact active learning across diverse classification and generative datasets, usin","authors_text":"Geoff V. Merrett, Stuart E. Middleton, Yaseen M. Osman","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-03T17:39:29Z","title":"Activation-Based Active Learning for In-Context Learning: Challenges and Insights"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.05134","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:dad3ab20a5d90735046727dd6de92a187a6c359b346283537777cd631c19b94e","target":"record","created_at":"2026-06-04T01:10:07Z","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":"c2bcf8ad1ed5a0c83619f0eb2d8c14c5c146ee728e37f9988acb6d2517b7791a","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-06-03T17:39:29Z","title_canon_sha256":"a95378ff52452e8114f78bdf20c0624c7cb6d52899f38fef54df1c09b3d02e87"},"schema_version":"1.0","source":{"id":"2606.05134","kind":"arxiv","version":1}},"canonical_sha256":"1eb536876c4ad7671b7d73f50c7d48c93289366a8ba6f2160a702afec119b4d6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1eb536876c4ad7671b7d73f50c7d48c93289366a8ba6f2160a702afec119b4d6","first_computed_at":"2026-06-04T01:10:07.905471Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-04T01:10:07.905471Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"xJREVPZjSwH12b6XbnAuv8zN123dFGXRhoQc57Ccvg6SwYovuIz/hSGDuBMq5o+Tbc37r7OsYuM5/Sd9KvkuCg==","signature_status":"signed_v1","signed_at":"2026-06-04T01:10:07.906033Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.05134","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dad3ab20a5d90735046727dd6de92a187a6c359b346283537777cd631c19b94e","sha256:17a578cd7453382b85fd89ef2e7c1ca088605897a1d0036fb486dab602596bdd"],"state_sha256":"efd1c8ea54558740685696b6c90fce49e802025cedf6b1909d4395236e043733"}