{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:W5VIDIVDXVKD2F7SSRRDX2EP3R","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":"5d05b80ad6137d802948f8bddb5710ee5b243eb869a33a2b47b59faeda75401f","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-04-06T07:07:41Z","title_canon_sha256":"1407a79487821e44b8748d21f56e4f1e9e2bad53d6f2bb32775c2f508cf682c6"},"schema_version":"1.0","source":{"id":"2004.02435","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2004.02435","created_at":"2026-07-05T01:13:59Z"},{"alias_kind":"arxiv_version","alias_value":"2004.02435v2","created_at":"2026-07-05T01:13:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2004.02435","created_at":"2026-07-05T01:13:59Z"},{"alias_kind":"pith_short_12","alias_value":"W5VIDIVDXVKD","created_at":"2026-07-05T01:13:59Z"},{"alias_kind":"pith_short_16","alias_value":"W5VIDIVDXVKD2F7S","created_at":"2026-07-05T01:13:59Z"},{"alias_kind":"pith_short_8","alias_value":"W5VIDIVD","created_at":"2026-07-05T01:13:59Z"}],"graph_snapshots":[{"event_id":"sha256:b6ac3dd1996e192fdda8419c7286a9e0b9d668f2595c5ee28b127a74fd9ae9a2","target":"graph","created_at":"2026-07-05T01:13:59Z","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/2004.02435/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Bayesian deep neural networks (DNNs) can provide a mathematically grounded framework to quantify uncertainty in predictions from image captioning models. We propose a Bayesian variant of policy-gradient based reinforcement learning training technique for image captioning models to directly optimize non-differentiable image captioning quality metrics such as CIDEr-D. We extend the well-known Self-Critical Sequence Training (SCST) approach for image captioning models by incorporating Bayesian inference, and refer to it as B-SCST. The \"baseline\" for the policy-gradients in B-SCST is generated by ","authors_text":"Mahesh Subedar, Omesh Tickoo, Shashank Bujimalla","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-04-06T07:07:41Z","title":"B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2004.02435","kind":"arxiv","version":2},"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:aa665feb9e599d3f65291792ce2da0fd0ad99b26a9eeb6d17ee8f7cc2702a7d0","target":"record","created_at":"2026-07-05T01:13:59Z","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":"5d05b80ad6137d802948f8bddb5710ee5b243eb869a33a2b47b59faeda75401f","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-04-06T07:07:41Z","title_canon_sha256":"1407a79487821e44b8748d21f56e4f1e9e2bad53d6f2bb32775c2f508cf682c6"},"schema_version":"1.0","source":{"id":"2004.02435","kind":"arxiv","version":2}},"canonical_sha256":"b76a81a2a3bd543d17f294623be88fdc4e6ea239f18c159ef6c8479c313226c2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b76a81a2a3bd543d17f294623be88fdc4e6ea239f18c159ef6c8479c313226c2","first_computed_at":"2026-07-05T01:13:59.525450Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:13:59.525450Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1SDAo9m2onhU2JMQlck/DXHMxa9kzoPildF/yRridjy24kDERE+s9JIxWZy6f8itwmjMIHVfaylNX2YdPVtSDg==","signature_status":"signed_v1","signed_at":"2026-07-05T01:13:59.525909Z","signed_message":"canonical_sha256_bytes"},"source_id":"2004.02435","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aa665feb9e599d3f65291792ce2da0fd0ad99b26a9eeb6d17ee8f7cc2702a7d0","sha256:b6ac3dd1996e192fdda8419c7286a9e0b9d668f2595c5ee28b127a74fd9ae9a2"],"state_sha256":"50c2f196c7cf1ab141efd659b349231d8c0689ee9b37a126f83a4d168ddc4728"}