{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:IDS6QE63U3PK7XBWKZIS4IRV7I","short_pith_number":"pith:IDS6QE63","canonical_record":{"source":{"id":"1711.02326","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-11-07T07:52:12Z","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"title_canon_sha256":"c56a1dba08765d774092e8a24a05b4335feb457ab8493c192312df0968f57af9","abstract_canon_sha256":"97fc27ed91adc7d9173aa4bea486c84d8094ec5d19ad23f296c9e5a92a016d79"},"schema_version":"1.0"},"canonical_sha256":"40e5e813dba6deafdc3656512e2235fa2b524fb7ae1410cfb48e68faf15f58a6","source":{"kind":"arxiv","id":"1711.02326","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.02326","created_at":"2026-05-18T00:31:08Z"},{"alias_kind":"arxiv_version","alias_value":"1711.02326v1","created_at":"2026-05-18T00:31:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.02326","created_at":"2026-05-18T00:31:08Z"},{"alias_kind":"pith_short_12","alias_value":"IDS6QE63U3PK","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"IDS6QE63U3PK7XBW","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"IDS6QE63","created_at":"2026-05-18T12:31:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:IDS6QE63U3PK7XBWKZIS4IRV7I","target":"record","payload":{"canonical_record":{"source":{"id":"1711.02326","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-11-07T07:52:12Z","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"title_canon_sha256":"c56a1dba08765d774092e8a24a05b4335feb457ab8493c192312df0968f57af9","abstract_canon_sha256":"97fc27ed91adc7d9173aa4bea486c84d8094ec5d19ad23f296c9e5a92a016d79"},"schema_version":"1.0"},"canonical_sha256":"40e5e813dba6deafdc3656512e2235fa2b524fb7ae1410cfb48e68faf15f58a6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:31:08.219726Z","signature_b64":"s9qliCrQ60j0ilrBiTSeuKBtn/74LmiW0/GMajqh9c6OFwwqyQ0BhxL9iw2bQwIjEqpclJ0zorXm1gGtol3QDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"40e5e813dba6deafdc3656512e2235fa2b524fb7ae1410cfb48e68faf15f58a6","last_reissued_at":"2026-05-18T00:31:08.219124Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:31:08.219124Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1711.02326","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":"2026-05-18T00:31:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CB5Y4zZNznBf7Iv2oycvOkWO5SlgXyCle+fa9Vi13hZkBe4Vvc7HBbsgJv5Y5B6jDNL9dwXKd0TquZKSxONzDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T21:00:24.298355Z"},"content_sha256":"d10e2235983c9d0ac0bb1e6f98a655e7bc2208f9db6620fc62e9c90a639a77c9","schema_version":"1.0","event_id":"sha256:d10e2235983c9d0ac0bb1e6f98a655e7bc2208f9db6620fc62e9c90a639a77c9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:IDS6QE63U3PK7XBWKZIS4IRV7I","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE","stat.ML"],"primary_cat":"cs.AI","authors_text":"Anirudh Goyal, Chris Pal, Jonathan Binas, Laurent Charlin, Nan Rosemary Ke, Olexa Bilaniuk, Yoshua Bengio","submitted_at":"2017-11-07T07:52:12Z","abstract_excerpt":"A major drawback of backpropagation through time (BPTT) is the difficulty of learning long-term dependencies, coming from having to propagate credit information backwards through every single step of the forward computation. This makes BPTT both computationally impractical and biologically implausible. For this reason, full backpropagation through time is rarely used on long sequences, and truncated backpropagation through time is used as a heuristic. However, this usually leads to biased estimates of the gradient in which longer term dependencies are ignored. Addressing this issue, we propose"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.02326","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":""},"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":"2026-05-18T00:31:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q92WD38YE85y8+0GFUD009eOZasEVxQqELoEnMgoHJ0KYx9tUporPC+NLeM+978Q4egFxvHoWXPxhfVLwBUcAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T21:00:24.298731Z"},"content_sha256":"045c8fcf217bc05af3742c224ebb46e7469fd8ddfcaed5a4ef1d340602f14e8b","schema_version":"1.0","event_id":"sha256:045c8fcf217bc05af3742c224ebb46e7469fd8ddfcaed5a4ef1d340602f14e8b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IDS6QE63U3PK7XBWKZIS4IRV7I/bundle.json","state_url":"https://pith.science/pith/IDS6QE63U3PK7XBWKZIS4IRV7I/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IDS6QE63U3PK7XBWKZIS4IRV7I/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":"2026-05-26T21:00:24Z","links":{"resolver":"https://pith.science/pith/IDS6QE63U3PK7XBWKZIS4IRV7I","bundle":"https://pith.science/pith/IDS6QE63U3PK7XBWKZIS4IRV7I/bundle.json","state":"https://pith.science/pith/IDS6QE63U3PK7XBWKZIS4IRV7I/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IDS6QE63U3PK7XBWKZIS4IRV7I/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:IDS6QE63U3PK7XBWKZIS4IRV7I","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":"97fc27ed91adc7d9173aa4bea486c84d8094ec5d19ad23f296c9e5a92a016d79","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-11-07T07:52:12Z","title_canon_sha256":"c56a1dba08765d774092e8a24a05b4335feb457ab8493c192312df0968f57af9"},"schema_version":"1.0","source":{"id":"1711.02326","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1711.02326","created_at":"2026-05-18T00:31:08Z"},{"alias_kind":"arxiv_version","alias_value":"1711.02326v1","created_at":"2026-05-18T00:31:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1711.02326","created_at":"2026-05-18T00:31:08Z"},{"alias_kind":"pith_short_12","alias_value":"IDS6QE63U3PK","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_16","alias_value":"IDS6QE63U3PK7XBW","created_at":"2026-05-18T12:31:21Z"},{"alias_kind":"pith_short_8","alias_value":"IDS6QE63","created_at":"2026-05-18T12:31:21Z"}],"graph_snapshots":[{"event_id":"sha256:045c8fcf217bc05af3742c224ebb46e7469fd8ddfcaed5a4ef1d340602f14e8b","target":"graph","created_at":"2026-05-18T00:31:08Z","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":"A major drawback of backpropagation through time (BPTT) is the difficulty of learning long-term dependencies, coming from having to propagate credit information backwards through every single step of the forward computation. This makes BPTT both computationally impractical and biologically implausible. For this reason, full backpropagation through time is rarely used on long sequences, and truncated backpropagation through time is used as a heuristic. However, this usually leads to biased estimates of the gradient in which longer term dependencies are ignored. Addressing this issue, we propose","authors_text":"Anirudh Goyal, Chris Pal, Jonathan Binas, Laurent Charlin, Nan Rosemary Ke, Olexa Bilaniuk, Yoshua Bengio","cross_cats":["cs.LG","cs.NE","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-11-07T07:52:12Z","title":"Sparse Attentive Backtracking: Long-Range Credit Assignment in Recurrent Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1711.02326","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:d10e2235983c9d0ac0bb1e6f98a655e7bc2208f9db6620fc62e9c90a639a77c9","target":"record","created_at":"2026-05-18T00:31:08Z","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":"97fc27ed91adc7d9173aa4bea486c84d8094ec5d19ad23f296c9e5a92a016d79","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2017-11-07T07:52:12Z","title_canon_sha256":"c56a1dba08765d774092e8a24a05b4335feb457ab8493c192312df0968f57af9"},"schema_version":"1.0","source":{"id":"1711.02326","kind":"arxiv","version":1}},"canonical_sha256":"40e5e813dba6deafdc3656512e2235fa2b524fb7ae1410cfb48e68faf15f58a6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"40e5e813dba6deafdc3656512e2235fa2b524fb7ae1410cfb48e68faf15f58a6","first_computed_at":"2026-05-18T00:31:08.219124Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:31:08.219124Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s9qliCrQ60j0ilrBiTSeuKBtn/74LmiW0/GMajqh9c6OFwwqyQ0BhxL9iw2bQwIjEqpclJ0zorXm1gGtol3QDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:31:08.219726Z","signed_message":"canonical_sha256_bytes"},"source_id":"1711.02326","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d10e2235983c9d0ac0bb1e6f98a655e7bc2208f9db6620fc62e9c90a639a77c9","sha256:045c8fcf217bc05af3742c224ebb46e7469fd8ddfcaed5a4ef1d340602f14e8b"],"state_sha256":"ee4dc4da347bdc37536dd984df3d98f9e0e5a49203934caf1553ab1962562bcf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GwBwWOn9lWRXLvAkPS9uqexSVmEeNhYM/hnLXaY5WPV5Om1V0Sn/ZXmTbE6kLwVbbTNG3B3etqsykskafo98Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T21:00:24.301107Z","bundle_sha256":"43eb3e77946e17124fc79ae54190adc6af9d20c8638dc0fe34e80ff3108b8fc2"}}