{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:7Q74TS3KQYN33CBHRDY6RK24QQ","short_pith_number":"pith:7Q74TS3K","canonical_record":{"source":{"id":"2101.04899","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-01-13T06:21:27Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7e78d75f5e08b30a28b34e7d8bf443e6e24215e6eb7729980799b1e0854233aa","abstract_canon_sha256":"8ee7f228a25f7192209969c11db0e92eae456f4a7338190811eeaf64d316e4a2"},"schema_version":"1.0"},"canonical_sha256":"fc3fc9cb6a861bbd882788f1e8ab5c843371799648d702d71eeabbfcc21649c0","source":{"kind":"arxiv","id":"2101.04899","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.04899","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"arxiv_version","alias_value":"2101.04899v2","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.04899","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"pith_short_12","alias_value":"7Q74TS3KQYN3","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"pith_short_16","alias_value":"7Q74TS3KQYN33CBH","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"pith_short_8","alias_value":"7Q74TS3K","created_at":"2026-07-05T03:47:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:7Q74TS3KQYN33CBHRDY6RK24QQ","target":"record","payload":{"canonical_record":{"source":{"id":"2101.04899","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-01-13T06:21:27Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"7e78d75f5e08b30a28b34e7d8bf443e6e24215e6eb7729980799b1e0854233aa","abstract_canon_sha256":"8ee7f228a25f7192209969c11db0e92eae456f4a7338190811eeaf64d316e4a2"},"schema_version":"1.0"},"canonical_sha256":"fc3fc9cb6a861bbd882788f1e8ab5c843371799648d702d71eeabbfcc21649c0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:47:14.178137Z","signature_b64":"s1cTS0vacK6j9D2hsGN71DAWarcFtV4yEOm2Dd9Px3SKaUkeuM/xTVyz/uIka/krXVYCXA2xWOnRN4KgZefSBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fc3fc9cb6a861bbd882788f1e8ab5c843371799648d702d71eeabbfcc21649c0","last_reissued_at":"2026-07-05T03:47:14.177699Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:47:14.177699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2101.04899","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T03:47:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MtH5EmwgL088UTCXrV0AL2nD7butY++gYHd3sxQqZGQOn+6AcJGIMJ4KN3kZKTAWtCtFjoB07ut6MyFmll4ABg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:18:41.089046Z"},"content_sha256":"7e5b9baf29675b781c16201ff8227f6590816dd7383784ffc839c6a2dc7a0539","schema_version":"1.0","event_id":"sha256:7e5b9baf29675b781c16201ff8227f6590816dd7383784ffc839c6a2dc7a0539"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:7Q74TS3KQYN33CBHRDY6RK24QQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Experimental Evaluation of Deep Learning models for Marathi Text Classification","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Atharva Kulkarni, Gayatri Kshirsagar, Jayashree Jagdale, Manali Likhitkar, Meet Mandhane, Raviraj Joshi","submitted_at":"2021-01-13T06:21:27Z","abstract_excerpt":"The Marathi language is one of the prominent languages used in India. It is predominantly spoken by the people of Maharashtra. Over the past decade, the usage of language on online platforms has tremendously increased. However, research on Natural Language Processing (NLP) approaches for Marathi text has not received much attention. Marathi is a morphologically rich language and uses a variant of the Devanagari script in the written form. This works aims to provide a comprehensive overview of available resources and models for Marathi text classification. We evaluate CNN, LSTM, ULMFiT, and BER"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.04899","kind":"arxiv","version":2},"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/2101.04899/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":"2026-07-05T03:47:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vY7C34ay0WMyQdzKpig53u1W7oEzb9lA2LRy+u7xgrQdpDc4Bo8oEWAPyfPHtwFNK+XM6DdiEImfdLZoLvyNDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:18:41.089433Z"},"content_sha256":"013357db2ce26bef62edfcd9e6348d789b2e9795a2c31ee9d6f909fff19a0894","schema_version":"1.0","event_id":"sha256:013357db2ce26bef62edfcd9e6348d789b2e9795a2c31ee9d6f909fff19a0894"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7Q74TS3KQYN33CBHRDY6RK24QQ/bundle.json","state_url":"https://pith.science/pith/7Q74TS3KQYN33CBHRDY6RK24QQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7Q74TS3KQYN33CBHRDY6RK24QQ/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":"2026-07-07T04:18:41Z","links":{"resolver":"https://pith.science/pith/7Q74TS3KQYN33CBHRDY6RK24QQ","bundle":"https://pith.science/pith/7Q74TS3KQYN33CBHRDY6RK24QQ/bundle.json","state":"https://pith.science/pith/7Q74TS3KQYN33CBHRDY6RK24QQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7Q74TS3KQYN33CBHRDY6RK24QQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:7Q74TS3KQYN33CBHRDY6RK24QQ","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":"8ee7f228a25f7192209969c11db0e92eae456f4a7338190811eeaf64d316e4a2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-01-13T06:21:27Z","title_canon_sha256":"7e78d75f5e08b30a28b34e7d8bf443e6e24215e6eb7729980799b1e0854233aa"},"schema_version":"1.0","source":{"id":"2101.04899","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2101.04899","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"arxiv_version","alias_value":"2101.04899v2","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2101.04899","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"pith_short_12","alias_value":"7Q74TS3KQYN3","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"pith_short_16","alias_value":"7Q74TS3KQYN33CBH","created_at":"2026-07-05T03:47:14Z"},{"alias_kind":"pith_short_8","alias_value":"7Q74TS3K","created_at":"2026-07-05T03:47:14Z"}],"graph_snapshots":[{"event_id":"sha256:013357db2ce26bef62edfcd9e6348d789b2e9795a2c31ee9d6f909fff19a0894","target":"graph","created_at":"2026-07-05T03:47:14Z","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/2101.04899/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The Marathi language is one of the prominent languages used in India. It is predominantly spoken by the people of Maharashtra. Over the past decade, the usage of language on online platforms has tremendously increased. However, research on Natural Language Processing (NLP) approaches for Marathi text has not received much attention. Marathi is a morphologically rich language and uses a variant of the Devanagari script in the written form. This works aims to provide a comprehensive overview of available resources and models for Marathi text classification. We evaluate CNN, LSTM, ULMFiT, and BER","authors_text":"Atharva Kulkarni, Gayatri Kshirsagar, Jayashree Jagdale, Manali Likhitkar, Meet Mandhane, Raviraj Joshi","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-01-13T06:21:27Z","title":"Experimental Evaluation of Deep Learning models for Marathi Text Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2101.04899","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":"sha256:7e5b9baf29675b781c16201ff8227f6590816dd7383784ffc839c6a2dc7a0539","target":"record","created_at":"2026-07-05T03:47:14Z","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":"8ee7f228a25f7192209969c11db0e92eae456f4a7338190811eeaf64d316e4a2","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-01-13T06:21:27Z","title_canon_sha256":"7e78d75f5e08b30a28b34e7d8bf443e6e24215e6eb7729980799b1e0854233aa"},"schema_version":"1.0","source":{"id":"2101.04899","kind":"arxiv","version":2}},"canonical_sha256":"fc3fc9cb6a861bbd882788f1e8ab5c843371799648d702d71eeabbfcc21649c0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fc3fc9cb6a861bbd882788f1e8ab5c843371799648d702d71eeabbfcc21649c0","first_computed_at":"2026-07-05T03:47:14.177699Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:47:14.177699Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s1cTS0vacK6j9D2hsGN71DAWarcFtV4yEOm2Dd9Px3SKaUkeuM/xTVyz/uIka/krXVYCXA2xWOnRN4KgZefSBg==","signature_status":"signed_v1","signed_at":"2026-07-05T03:47:14.178137Z","signed_message":"canonical_sha256_bytes"},"source_id":"2101.04899","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7e5b9baf29675b781c16201ff8227f6590816dd7383784ffc839c6a2dc7a0539","sha256:013357db2ce26bef62edfcd9e6348d789b2e9795a2c31ee9d6f909fff19a0894"],"state_sha256":"430a71b99e0ea6450dbe850c2b80f6e35ae3564a73faf9281791c4bcdb9b1eea"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4bmmoRp+HGxEMlewVaGeSEnCFaXdKmp7qF2tyw3/8PWxeiO8VwEFexeFoaKzdkPGQyn8vTyQYwz0fegQCt9eAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T04:18:41.091634Z","bundle_sha256":"7a6827ee1921c4f95f674a6a130bf42632316d382410a8608c5f6bb287722977"}}