{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:IZYFYNTEIH6PLEP45PXOFCKXIC","short_pith_number":"pith:IZYFYNTE","canonical_record":{"source":{"id":"1312.6594","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2013-12-20T16:36:40Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6828da8dc75f256ffa82a3f055377e7ec2348de522f06b5df7e2dd8716678a73","abstract_canon_sha256":"16a16718186487d0b14b040fc7124503a35cd2b066fb27461fe386c4745ecbb7"},"schema_version":"1.0"},"canonical_sha256":"46705c366441fcf591fcebeee2895740843ac5a8146f7aa19053f1c67ad447b4","source":{"kind":"arxiv","id":"1312.6594","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1312.6594","created_at":"2026-05-18T02:59:20Z"},{"alias_kind":"arxiv_version","alias_value":"1312.6594v3","created_at":"2026-05-18T02:59:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1312.6594","created_at":"2026-05-18T02:59:20Z"},{"alias_kind":"pith_short_12","alias_value":"IZYFYNTEIH6P","created_at":"2026-05-18T12:27:49Z"},{"alias_kind":"pith_short_16","alias_value":"IZYFYNTEIH6PLEP4","created_at":"2026-05-18T12:27:49Z"},{"alias_kind":"pith_short_8","alias_value":"IZYFYNTE","created_at":"2026-05-18T12:27:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:IZYFYNTEIH6PLEP45PXOFCKXIC","target":"record","payload":{"canonical_record":{"source":{"id":"1312.6594","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2013-12-20T16:36:40Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"6828da8dc75f256ffa82a3f055377e7ec2348de522f06b5df7e2dd8716678a73","abstract_canon_sha256":"16a16718186487d0b14b040fc7124503a35cd2b066fb27461fe386c4745ecbb7"},"schema_version":"1.0"},"canonical_sha256":"46705c366441fcf591fcebeee2895740843ac5a8146f7aa19053f1c67ad447b4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:59:20.293452Z","signature_b64":"X1MfCFisOvt1Gwrii0QCJ18LVUAE9IuGGuXvN4+5DEaBBd9bx2PKaddVdy2C8QUH/2IlevkrTv3edwfCsA2DBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"46705c366441fcf591fcebeee2895740843ac5a8146f7aa19053f1c67ad447b4","last_reissued_at":"2026-05-18T02:59:20.292694Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:59:20.292694Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1312.6594","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:59:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R1JkgrxstutdK2TIejN0hWer1ZtaPspWx1Abx6GzkuOKovSiHPZ13mch8+WM2id3NpZb/BBOIPu+hJyRpXhdAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T15:27:45.758751Z"},"content_sha256":"5ace5bdfa3649506c6946eb030610fdba20648272b0aff8a65beba60d9847510","schema_version":"1.0","event_id":"sha256:5ace5bdfa3649506c6946eb030610fdba20648272b0aff8a65beba60d9847510"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:IZYFYNTEIH6PLEP45PXOFCKXIC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sequentially Generated Instance-Dependent Image Representations for Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Gabriel Dulac-Arnold, Ludovic Denoyer, Matthieu Cord, Nicolas Thome, Patrick Gallinari","submitted_at":"2013-12-20T16:36:40Z","abstract_excerpt":"In this paper, we investigate a new framework for image classification that adaptively generates spatial representations. Our strategy is based on a sequential process that learns to explore the different regions of any image in order to infer its category. In particular, the choice of regions is specific to each image, directed by the actual content of previously selected regions.The capacity of the system to handle incomplete image information as well as its adaptive region selection allow the system to perform well in budgeted classification tasks by exploiting a dynamicly generated represe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1312.6594","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-18T02:59:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CP07Ra2KmgVw+vKXb4vm+JLVjfyDGUz/zYeWVsqKKGCi9rmXkDacgl/ziIj3x7EQQCC903ZY3MQ1cGn8hOXaCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-29T15:27:45.759459Z"},"content_sha256":"8f77d708828f8b22f7faba5f36c0e59b993fc8bd82b32773102e16d549a4b9a6","schema_version":"1.0","event_id":"sha256:8f77d708828f8b22f7faba5f36c0e59b993fc8bd82b32773102e16d549a4b9a6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IZYFYNTEIH6PLEP45PXOFCKXIC/bundle.json","state_url":"https://pith.science/pith/IZYFYNTEIH6PLEP45PXOFCKXIC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IZYFYNTEIH6PLEP45PXOFCKXIC/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":"2026-05-29T15:27:45Z","links":{"resolver":"https://pith.science/pith/IZYFYNTEIH6PLEP45PXOFCKXIC","bundle":"https://pith.science/pith/IZYFYNTEIH6PLEP45PXOFCKXIC/bundle.json","state":"https://pith.science/pith/IZYFYNTEIH6PLEP45PXOFCKXIC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IZYFYNTEIH6PLEP45PXOFCKXIC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:IZYFYNTEIH6PLEP45PXOFCKXIC","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":"16a16718186487d0b14b040fc7124503a35cd2b066fb27461fe386c4745ecbb7","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2013-12-20T16:36:40Z","title_canon_sha256":"6828da8dc75f256ffa82a3f055377e7ec2348de522f06b5df7e2dd8716678a73"},"schema_version":"1.0","source":{"id":"1312.6594","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1312.6594","created_at":"2026-05-18T02:59:20Z"},{"alias_kind":"arxiv_version","alias_value":"1312.6594v3","created_at":"2026-05-18T02:59:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1312.6594","created_at":"2026-05-18T02:59:20Z"},{"alias_kind":"pith_short_12","alias_value":"IZYFYNTEIH6P","created_at":"2026-05-18T12:27:49Z"},{"alias_kind":"pith_short_16","alias_value":"IZYFYNTEIH6PLEP4","created_at":"2026-05-18T12:27:49Z"},{"alias_kind":"pith_short_8","alias_value":"IZYFYNTE","created_at":"2026-05-18T12:27:49Z"}],"graph_snapshots":[{"event_id":"sha256:8f77d708828f8b22f7faba5f36c0e59b993fc8bd82b32773102e16d549a4b9a6","target":"graph","created_at":"2026-05-18T02:59:20Z","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"},"paper":{"abstract_excerpt":"In this paper, we investigate a new framework for image classification that adaptively generates spatial representations. Our strategy is based on a sequential process that learns to explore the different regions of any image in order to infer its category. In particular, the choice of regions is specific to each image, directed by the actual content of previously selected regions.The capacity of the system to handle incomplete image information as well as its adaptive region selection allow the system to perform well in budgeted classification tasks by exploiting a dynamicly generated represe","authors_text":"Gabriel Dulac-Arnold, Ludovic Denoyer, Matthieu Cord, Nicolas Thome, Patrick Gallinari","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2013-12-20T16:36:40Z","title":"Sequentially Generated Instance-Dependent Image Representations for Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1312.6594","kind":"arxiv","version":3},"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":"sha256:5ace5bdfa3649506c6946eb030610fdba20648272b0aff8a65beba60d9847510","target":"record","created_at":"2026-05-18T02:59:20Z","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":"16a16718186487d0b14b040fc7124503a35cd2b066fb27461fe386c4745ecbb7","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2013-12-20T16:36:40Z","title_canon_sha256":"6828da8dc75f256ffa82a3f055377e7ec2348de522f06b5df7e2dd8716678a73"},"schema_version":"1.0","source":{"id":"1312.6594","kind":"arxiv","version":3}},"canonical_sha256":"46705c366441fcf591fcebeee2895740843ac5a8146f7aa19053f1c67ad447b4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"46705c366441fcf591fcebeee2895740843ac5a8146f7aa19053f1c67ad447b4","first_computed_at":"2026-05-18T02:59:20.292694Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:59:20.292694Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"X1MfCFisOvt1Gwrii0QCJ18LVUAE9IuGGuXvN4+5DEaBBd9bx2PKaddVdy2C8QUH/2IlevkrTv3edwfCsA2DBg==","signature_status":"signed_v1","signed_at":"2026-05-18T02:59:20.293452Z","signed_message":"canonical_sha256_bytes"},"source_id":"1312.6594","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5ace5bdfa3649506c6946eb030610fdba20648272b0aff8a65beba60d9847510","sha256:8f77d708828f8b22f7faba5f36c0e59b993fc8bd82b32773102e16d549a4b9a6"],"state_sha256":"eb0548079dbe05ce82042698d77cfc9341027925b7e91dc9f451167af2137abe"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Tul+beS97sB0/w7qtR9YoxzLYnBTYciQ3Fgy7CWNPqapGkqoQV/a1YAOex1df2hQdGOvZ73GjCCR292Csv79CA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-29T15:27:45.762967Z","bundle_sha256":"c591b509f25b33d25b29113626532b35024f8187e136978f76ffa00c085ff954"}}