{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:JLGVJULLC2ETORFGOF235RTZY6","short_pith_number":"pith:JLGVJULL","canonical_record":{"source":{"id":"2411.07213","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-11T18:36:17Z","cross_cats_sorted":[],"title_canon_sha256":"d2e95a89d172ca498b063b7b637b398cb3845f241f0f30836c2afc10134221a3","abstract_canon_sha256":"a89fc50eb5dd90a0a184c4dfc4eb442c6c374c7b2aa357df703640dac588409e"},"schema_version":"1.0"},"canonical_sha256":"4acd54d16b16893744a67175bec679c7acb0f660409283aa6349b2e0faebbfb8","source":{"kind":"arxiv","id":"2411.07213","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.07213","created_at":"2026-07-05T09:33:58Z"},{"alias_kind":"arxiv_version","alias_value":"2411.07213v1","created_at":"2026-07-05T09:33:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.07213","created_at":"2026-07-05T09:33:58Z"},{"alias_kind":"pith_short_12","alias_value":"JLGVJULLC2ET","created_at":"2026-07-05T09:33:58Z"},{"alias_kind":"pith_short_16","alias_value":"JLGVJULLC2ETORFG","created_at":"2026-07-05T09:33:58Z"},{"alias_kind":"pith_short_8","alias_value":"JLGVJULL","created_at":"2026-07-05T09:33:58Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:JLGVJULLC2ETORFGOF235RTZY6","target":"record","payload":{"canonical_record":{"source":{"id":"2411.07213","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-11T18:36:17Z","cross_cats_sorted":[],"title_canon_sha256":"d2e95a89d172ca498b063b7b637b398cb3845f241f0f30836c2afc10134221a3","abstract_canon_sha256":"a89fc50eb5dd90a0a184c4dfc4eb442c6c374c7b2aa357df703640dac588409e"},"schema_version":"1.0"},"canonical_sha256":"4acd54d16b16893744a67175bec679c7acb0f660409283aa6349b2e0faebbfb8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:33:58.853643Z","signature_b64":"Q5JZftgXhjgKoPc1fyxGsVTw1YXbkv1JG9kmwKjy3aC0bRAaUE+jgTmN/8D28+eOp4NFNiMlHI3rAbphlvagCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4acd54d16b16893744a67175bec679c7acb0f660409283aa6349b2e0faebbfb8","last_reissued_at":"2026-07-05T09:33:58.853231Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:33:58.853231Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.07213","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:33:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kHoS3iBZEW+0a1lgtmBl+/8DC9ekUrOoXJHdU8yP7av05E/ERaXQcRHSgqTxOLYHVObmMXBerMO4/k2CMDEGDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:43:48.251836Z"},"content_sha256":"6e78cc415ac49ef1aab1dc7a272de72ef387798e60500227e18ec41d34eba143","schema_version":"1.0","event_id":"sha256:6e78cc415ac49ef1aab1dc7a272de72ef387798e60500227e18ec41d34eba143"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:JLGVJULLC2ETORFGOF235RTZY6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Comparing Bottom-Up and Top-Down Steering Approaches on In-Context Learning Tasks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"David Krueger, Dmitrii Krasheninnikov, Joe Kwon, Madeline Brumley, Usman Anwar","submitted_at":"2024-11-11T18:36:17Z","abstract_excerpt":"A key objective of interpretability research on large language models (LLMs) is to develop methods for robustly steering models toward desired behaviors. To this end, two distinct approaches to interpretability -- ``bottom-up\" and ``top-down\" -- have been presented, but there has been little quantitative comparison between them. We present a case study comparing the effectiveness of representative vector steering methods from each branch: function vectors (FV; arXiv:2310.15213), as a bottom-up method, and in-context vectors (ICV; arXiv:2311.06668) as a top-down method. While both aim to captur"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.07213","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2411.07213/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:33:58Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DJZHiQ7dqSL26rJHXKBquMC7IjSb5jCGdndk6I7Qfx99Qgh+qo+Cz/eyiJfnDGDvus7avSh21M2BlYDMmJA7Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:43:48.252212Z"},"content_sha256":"ca829365970a0c9fb5678f8571422e99e47c7b477c74a0afb2ca73db86d8f179","schema_version":"1.0","event_id":"sha256:ca829365970a0c9fb5678f8571422e99e47c7b477c74a0afb2ca73db86d8f179"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JLGVJULLC2ETORFGOF235RTZY6/bundle.json","state_url":"https://pith.science/pith/JLGVJULLC2ETORFGOF235RTZY6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JLGVJULLC2ETORFGOF235RTZY6/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-06T17:43:48Z","links":{"resolver":"https://pith.science/pith/JLGVJULLC2ETORFGOF235RTZY6","bundle":"https://pith.science/pith/JLGVJULLC2ETORFGOF235RTZY6/bundle.json","state":"https://pith.science/pith/JLGVJULLC2ETORFGOF235RTZY6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JLGVJULLC2ETORFGOF235RTZY6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JLGVJULLC2ETORFGOF235RTZY6","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":"a89fc50eb5dd90a0a184c4dfc4eb442c6c374c7b2aa357df703640dac588409e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-11T18:36:17Z","title_canon_sha256":"d2e95a89d172ca498b063b7b637b398cb3845f241f0f30836c2afc10134221a3"},"schema_version":"1.0","source":{"id":"2411.07213","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.07213","created_at":"2026-07-05T09:33:58Z"},{"alias_kind":"arxiv_version","alias_value":"2411.07213v1","created_at":"2026-07-05T09:33:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.07213","created_at":"2026-07-05T09:33:58Z"},{"alias_kind":"pith_short_12","alias_value":"JLGVJULLC2ET","created_at":"2026-07-05T09:33:58Z"},{"alias_kind":"pith_short_16","alias_value":"JLGVJULLC2ETORFG","created_at":"2026-07-05T09:33:58Z"},{"alias_kind":"pith_short_8","alias_value":"JLGVJULL","created_at":"2026-07-05T09:33:58Z"}],"graph_snapshots":[{"event_id":"sha256:ca829365970a0c9fb5678f8571422e99e47c7b477c74a0afb2ca73db86d8f179","target":"graph","created_at":"2026-07-05T09:33:58Z","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/2411.07213/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A key objective of interpretability research on large language models (LLMs) is to develop methods for robustly steering models toward desired behaviors. To this end, two distinct approaches to interpretability -- ``bottom-up\" and ``top-down\" -- have been presented, but there has been little quantitative comparison between them. We present a case study comparing the effectiveness of representative vector steering methods from each branch: function vectors (FV; arXiv:2310.15213), as a bottom-up method, and in-context vectors (ICV; arXiv:2311.06668) as a top-down method. While both aim to captur","authors_text":"David Krueger, Dmitrii Krasheninnikov, Joe Kwon, Madeline Brumley, Usman Anwar","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-11T18:36:17Z","title":"Comparing Bottom-Up and Top-Down Steering Approaches on In-Context Learning Tasks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.07213","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":"sha256:6e78cc415ac49ef1aab1dc7a272de72ef387798e60500227e18ec41d34eba143","target":"record","created_at":"2026-07-05T09:33:58Z","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":"a89fc50eb5dd90a0a184c4dfc4eb442c6c374c7b2aa357df703640dac588409e","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-11-11T18:36:17Z","title_canon_sha256":"d2e95a89d172ca498b063b7b637b398cb3845f241f0f30836c2afc10134221a3"},"schema_version":"1.0","source":{"id":"2411.07213","kind":"arxiv","version":1}},"canonical_sha256":"4acd54d16b16893744a67175bec679c7acb0f660409283aa6349b2e0faebbfb8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4acd54d16b16893744a67175bec679c7acb0f660409283aa6349b2e0faebbfb8","first_computed_at":"2026-07-05T09:33:58.853231Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:33:58.853231Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Q5JZftgXhjgKoPc1fyxGsVTw1YXbkv1JG9kmwKjy3aC0bRAaUE+jgTmN/8D28+eOp4NFNiMlHI3rAbphlvagCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:33:58.853643Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.07213","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6e78cc415ac49ef1aab1dc7a272de72ef387798e60500227e18ec41d34eba143","sha256:ca829365970a0c9fb5678f8571422e99e47c7b477c74a0afb2ca73db86d8f179"],"state_sha256":"717955ec324019862a46f3157d1396b20846b4cef0ea3e019afedcee0452dd4e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EcRg1w0LA0Bi/t66qNQ3QLS7rOtCDhoRoIPoK/JZj6YRumsm/wJ1pVvsHH1JvYoYnV05zFMK3GVzfA6vGBIqBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T17:43:48.254196Z","bundle_sha256":"9cee80edb93f03eb78c486680897569253715ce810153f85a47bcce0a750401e"}}