{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:BN5NGVD5LUPZMVT7HYYBQ562CL","short_pith_number":"pith:BN5NGVD5","canonical_record":{"source":{"id":"2402.15441","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-13T09:19:05Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2feb24b68416338f7ab52436b44f2eaaf103002efe4d9098ce7302f19759a5d0","abstract_canon_sha256":"d5e3a553f7a70e83e0049463d4424b7a2004eab7ff17c3f852deb87c59fd5c7f"},"schema_version":"1.0"},"canonical_sha256":"0b7ad3547d5d1f96567f3e301877da12c6ae53803955dcfd99efe9ed93b1949b","source":{"kind":"arxiv","id":"2402.15441","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.15441","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"arxiv_version","alias_value":"2402.15441v4","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.15441","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"pith_short_12","alias_value":"BN5NGVD5LUPZ","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"pith_short_16","alias_value":"BN5NGVD5LUPZMVT7","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"pith_short_8","alias_value":"BN5NGVD5","created_at":"2026-07-05T08:35:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:BN5NGVD5LUPZMVT7HYYBQ562CL","target":"record","payload":{"canonical_record":{"source":{"id":"2402.15441","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-13T09:19:05Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2feb24b68416338f7ab52436b44f2eaaf103002efe4d9098ce7302f19759a5d0","abstract_canon_sha256":"d5e3a553f7a70e83e0049463d4424b7a2004eab7ff17c3f852deb87c59fd5c7f"},"schema_version":"1.0"},"canonical_sha256":"0b7ad3547d5d1f96567f3e301877da12c6ae53803955dcfd99efe9ed93b1949b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:35:00.500482Z","signature_b64":"vQY84+OjuCFCUB/+tyBxzew0Qa/6rQ+++qLrK7mYc85mfds+WSAMg1d7uTT7JtzTt29R1uWZrE17NLZvsuD6Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0b7ad3547d5d1f96567f3e301877da12c6ae53803955dcfd99efe9ed93b1949b","last_reissued_at":"2026-07-05T08:35:00.500014Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:35:00.500014Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.15441","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:35:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zp6wuf2Mafd/qbNopif1IgBvpeUhTfU0sAb/rtBNlhiybG+W34QLQux4a/KhiBbkexSb8kx2KNPzQFCQS2kJAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T23:19:39.829752Z"},"content_sha256":"e6f99a71c55e933173cb19a4812e44cb9baa6c0f9456fe10223e518f778fc24d","schema_version":"1.0","event_id":"sha256:e6f99a71c55e933173cb19a4812e44cb9baa6c0f9456fe10223e518f778fc24d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:BN5NGVD5LUPZMVT7HYYBQ562CL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Active Few-Shot Fine-Tuning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Andreas Krause, Bhavya Sukhija, Jonas H\\\"ubotter, Lenart Treven, Yarden As","submitted_at":"2024-02-13T09:19:05Z","abstract_excerpt":"We study the question: How can we select the right data for fine-tuning to a specific task? We call this data selection problem active fine-tuning and show that it is an instance of transductive active learning, a novel generalization of classical active learning. We propose ITL, short for information-based transductive learning, an approach which samples adaptively to maximize information gained about the specified task. We are the first to show, under general regularity assumptions, that such decision rules converge uniformly to the smallest possible uncertainty obtainable from the accessibl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.15441","kind":"arxiv","version":4},"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/2402.15441/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":"2026-07-05T08:35:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Eo1GnoUxqDYgRpnYQLNsWnW265TCLYScXKvrU0oUjbZ/nEg37mfzZPVsLYT5HZuBM7WJlmrfnFtKh/4gfdLQCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T23:19:39.830127Z"},"content_sha256":"9ed868cdd7ee547c55cab438bffe9f168b97e790334b86d4abdfa91a6b7e0827","schema_version":"1.0","event_id":"sha256:9ed868cdd7ee547c55cab438bffe9f168b97e790334b86d4abdfa91a6b7e0827"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BN5NGVD5LUPZMVT7HYYBQ562CL/bundle.json","state_url":"https://pith.science/pith/BN5NGVD5LUPZMVT7HYYBQ562CL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BN5NGVD5LUPZMVT7HYYBQ562CL/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":"2026-07-06T23:19:39Z","links":{"resolver":"https://pith.science/pith/BN5NGVD5LUPZMVT7HYYBQ562CL","bundle":"https://pith.science/pith/BN5NGVD5LUPZMVT7HYYBQ562CL/bundle.json","state":"https://pith.science/pith/BN5NGVD5LUPZMVT7HYYBQ562CL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BN5NGVD5LUPZMVT7HYYBQ562CL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BN5NGVD5LUPZMVT7HYYBQ562CL","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":"d5e3a553f7a70e83e0049463d4424b7a2004eab7ff17c3f852deb87c59fd5c7f","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-13T09:19:05Z","title_canon_sha256":"2feb24b68416338f7ab52436b44f2eaaf103002efe4d9098ce7302f19759a5d0"},"schema_version":"1.0","source":{"id":"2402.15441","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.15441","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"arxiv_version","alias_value":"2402.15441v4","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.15441","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"pith_short_12","alias_value":"BN5NGVD5LUPZ","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"pith_short_16","alias_value":"BN5NGVD5LUPZMVT7","created_at":"2026-07-05T08:35:00Z"},{"alias_kind":"pith_short_8","alias_value":"BN5NGVD5","created_at":"2026-07-05T08:35:00Z"}],"graph_snapshots":[{"event_id":"sha256:9ed868cdd7ee547c55cab438bffe9f168b97e790334b86d4abdfa91a6b7e0827","target":"graph","created_at":"2026-07-05T08:35:00Z","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/2402.15441/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We study the question: How can we select the right data for fine-tuning to a specific task? We call this data selection problem active fine-tuning and show that it is an instance of transductive active learning, a novel generalization of classical active learning. We propose ITL, short for information-based transductive learning, an approach which samples adaptively to maximize information gained about the specified task. We are the first to show, under general regularity assumptions, that such decision rules converge uniformly to the smallest possible uncertainty obtainable from the accessibl","authors_text":"Andreas Krause, Bhavya Sukhija, Jonas H\\\"ubotter, Lenart Treven, Yarden As","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-13T09:19:05Z","title":"Active Few-Shot Fine-Tuning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.15441","kind":"arxiv","version":4},"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:e6f99a71c55e933173cb19a4812e44cb9baa6c0f9456fe10223e518f778fc24d","target":"record","created_at":"2026-07-05T08:35:00Z","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":"d5e3a553f7a70e83e0049463d4424b7a2004eab7ff17c3f852deb87c59fd5c7f","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-13T09:19:05Z","title_canon_sha256":"2feb24b68416338f7ab52436b44f2eaaf103002efe4d9098ce7302f19759a5d0"},"schema_version":"1.0","source":{"id":"2402.15441","kind":"arxiv","version":4}},"canonical_sha256":"0b7ad3547d5d1f96567f3e301877da12c6ae53803955dcfd99efe9ed93b1949b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0b7ad3547d5d1f96567f3e301877da12c6ae53803955dcfd99efe9ed93b1949b","first_computed_at":"2026-07-05T08:35:00.500014Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:35:00.500014Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vQY84+OjuCFCUB/+tyBxzew0Qa/6rQ+++qLrK7mYc85mfds+WSAMg1d7uTT7JtzTt29R1uWZrE17NLZvsuD6Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T08:35:00.500482Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.15441","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e6f99a71c55e933173cb19a4812e44cb9baa6c0f9456fe10223e518f778fc24d","sha256:9ed868cdd7ee547c55cab438bffe9f168b97e790334b86d4abdfa91a6b7e0827"],"state_sha256":"0e41dbff017e181e33607c616b6a6fde7bb1a52056e8ea3237ca591acf885954"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zUo0+KynfzpadGUbOzCvO7w0fiBad9RTKMBhcmfBlRgOOsNMuxsFi1hvN/uuVlPEQiAAlNiaLL70+sALBJpgDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T23:19:39.832145Z","bundle_sha256":"8da8bbf0e8792a009a4cb0a443264b850459eed0b0a39897f2bb53bf1bd7eb18"}}