{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:ZUBDNLML5GIX4UDAAFF4L2RCGH","short_pith_number":"pith:ZUBDNLML","canonical_record":{"source":{"id":"2104.07367","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-15T10:50:21Z","cross_cats_sorted":["cs.SI"],"title_canon_sha256":"a8cd4754448be0b6b3b8514cb40c3d73fbd4ea21bb54eab9917bf7b9b0935454","abstract_canon_sha256":"d7f2b639c2f2d929d64a8e8dfdc15e874e65333a6d97d55fbca45d656bfc43cb"},"schema_version":"1.0"},"canonical_sha256":"cd0236ad8be9917e5060014bc5ea2231c86182e945e436a5afee8bfb1ff2e06c","source":{"kind":"arxiv","id":"2104.07367","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.07367","created_at":"2026-07-05T02:32:27Z"},{"alias_kind":"arxiv_version","alias_value":"2104.07367v1","created_at":"2026-07-05T02:32:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.07367","created_at":"2026-07-05T02:32:27Z"},{"alias_kind":"pith_short_12","alias_value":"ZUBDNLML5GIX","created_at":"2026-07-05T02:32:27Z"},{"alias_kind":"pith_short_16","alias_value":"ZUBDNLML5GIX4UDA","created_at":"2026-07-05T02:32:27Z"},{"alias_kind":"pith_short_8","alias_value":"ZUBDNLML","created_at":"2026-07-05T02:32:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:ZUBDNLML5GIX4UDAAFF4L2RCGH","target":"record","payload":{"canonical_record":{"source":{"id":"2104.07367","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-15T10:50:21Z","cross_cats_sorted":["cs.SI"],"title_canon_sha256":"a8cd4754448be0b6b3b8514cb40c3d73fbd4ea21bb54eab9917bf7b9b0935454","abstract_canon_sha256":"d7f2b639c2f2d929d64a8e8dfdc15e874e65333a6d97d55fbca45d656bfc43cb"},"schema_version":"1.0"},"canonical_sha256":"cd0236ad8be9917e5060014bc5ea2231c86182e945e436a5afee8bfb1ff2e06c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:32:27.194118Z","signature_b64":"XcpOcjf/S97AUQR1AlXcukfFVPAfrQUq3z6AlV46MgpP0oOMCIDww6gXtxYEHZpWpfQD6dkhaTr8yAY52iM4BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"cd0236ad8be9917e5060014bc5ea2231c86182e945e436a5afee8bfb1ff2e06c","last_reissued_at":"2026-07-05T02:32:27.193631Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:32:27.193631Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.07367","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":"2026-07-05T02:32:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zSmoq28KQvnXjy89oRnG/Qz2M2MUnCgkyowPPhy6oEotpJIluNmp4I+qHSLf6QPoQclG9E+ebpEqqdjsujA3Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T13:01:20.185962Z"},"content_sha256":"11f5baaeedb3b5e8898867433a79d460bf6e24dbd97429f5e764894cbb05ea74","schema_version":"1.0","event_id":"sha256:11f5baaeedb3b5e8898867433a79d460bf6e24dbd97429f5e764894cbb05ea74"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:ZUBDNLML5GIX4UDAAFF4L2RCGH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"BERT based Transformers lead the way in Extraction of Health Information from Social Media","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SI"],"primary_cat":"cs.CL","authors_text":"Abhiraj Tiwari, Kumud Lakara, Nishesh Singh, Parthivi Choubey, Sahil Khose, Saisha Kashyap, Sidharth R, Ujjwal Verma","submitted_at":"2021-04-15T10:50:21Z","abstract_excerpt":"This paper describes our submissions for the Social Media Mining for Health (SMM4H)2021 shared tasks. We participated in 2 tasks:(1) Classification, extraction and normalization of adverse drug effect (ADE) mentions in English tweets (Task-1) and (2) Classification of COVID-19 tweets containing symptoms(Task-6). Our approach for the first task uses the language representation model RoBERTa with a binary classification head. For the second task, we use BERTweet, based on RoBERTa. Fine-tuning is performed on the pre-trained models for both tasks. The models are placed on top of a custom domain-s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.07367","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2104.07367/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":"2026-07-05T02:32:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FIWPGI/SIwhkHv/4vWOq0gGx+1j+C55F2aKtAiL2hHywNuRSUGFGsRA/JtjHy8IPdnDp76Vfzp21rTGHRw42CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T13:01:20.186759Z"},"content_sha256":"a2cc322ea17890300f80130ae833096415222fc58ccfd87bdbb5c08b8c2bf09f","schema_version":"1.0","event_id":"sha256:a2cc322ea17890300f80130ae833096415222fc58ccfd87bdbb5c08b8c2bf09f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ZUBDNLML5GIX4UDAAFF4L2RCGH/bundle.json","state_url":"https://pith.science/pith/ZUBDNLML5GIX4UDAAFF4L2RCGH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ZUBDNLML5GIX4UDAAFF4L2RCGH/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":"2026-07-07T13:01:20Z","links":{"resolver":"https://pith.science/pith/ZUBDNLML5GIX4UDAAFF4L2RCGH","bundle":"https://pith.science/pith/ZUBDNLML5GIX4UDAAFF4L2RCGH/bundle.json","state":"https://pith.science/pith/ZUBDNLML5GIX4UDAAFF4L2RCGH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ZUBDNLML5GIX4UDAAFF4L2RCGH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:ZUBDNLML5GIX4UDAAFF4L2RCGH","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":"d7f2b639c2f2d929d64a8e8dfdc15e874e65333a6d97d55fbca45d656bfc43cb","cross_cats_sorted":["cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-15T10:50:21Z","title_canon_sha256":"a8cd4754448be0b6b3b8514cb40c3d73fbd4ea21bb54eab9917bf7b9b0935454"},"schema_version":"1.0","source":{"id":"2104.07367","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.07367","created_at":"2026-07-05T02:32:27Z"},{"alias_kind":"arxiv_version","alias_value":"2104.07367v1","created_at":"2026-07-05T02:32:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.07367","created_at":"2026-07-05T02:32:27Z"},{"alias_kind":"pith_short_12","alias_value":"ZUBDNLML5GIX","created_at":"2026-07-05T02:32:27Z"},{"alias_kind":"pith_short_16","alias_value":"ZUBDNLML5GIX4UDA","created_at":"2026-07-05T02:32:27Z"},{"alias_kind":"pith_short_8","alias_value":"ZUBDNLML","created_at":"2026-07-05T02:32:27Z"}],"graph_snapshots":[{"event_id":"sha256:a2cc322ea17890300f80130ae833096415222fc58ccfd87bdbb5c08b8c2bf09f","target":"graph","created_at":"2026-07-05T02:32:27Z","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/2104.07367/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper describes our submissions for the Social Media Mining for Health (SMM4H)2021 shared tasks. We participated in 2 tasks:(1) Classification, extraction and normalization of adverse drug effect (ADE) mentions in English tweets (Task-1) and (2) Classification of COVID-19 tweets containing symptoms(Task-6). Our approach for the first task uses the language representation model RoBERTa with a binary classification head. For the second task, we use BERTweet, based on RoBERTa. Fine-tuning is performed on the pre-trained models for both tasks. The models are placed on top of a custom domain-s","authors_text":"Abhiraj Tiwari, Kumud Lakara, Nishesh Singh, Parthivi Choubey, Sahil Khose, Saisha Kashyap, Sidharth R, Ujjwal Verma","cross_cats":["cs.SI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-15T10:50:21Z","title":"BERT based Transformers lead the way in Extraction of Health Information from Social Media"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.07367","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":"sha256:11f5baaeedb3b5e8898867433a79d460bf6e24dbd97429f5e764894cbb05ea74","target":"record","created_at":"2026-07-05T02:32:27Z","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":"d7f2b639c2f2d929d64a8e8dfdc15e874e65333a6d97d55fbca45d656bfc43cb","cross_cats_sorted":["cs.SI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-15T10:50:21Z","title_canon_sha256":"a8cd4754448be0b6b3b8514cb40c3d73fbd4ea21bb54eab9917bf7b9b0935454"},"schema_version":"1.0","source":{"id":"2104.07367","kind":"arxiv","version":1}},"canonical_sha256":"cd0236ad8be9917e5060014bc5ea2231c86182e945e436a5afee8bfb1ff2e06c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cd0236ad8be9917e5060014bc5ea2231c86182e945e436a5afee8bfb1ff2e06c","first_computed_at":"2026-07-05T02:32:27.193631Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:32:27.193631Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XcpOcjf/S97AUQR1AlXcukfFVPAfrQUq3z6AlV46MgpP0oOMCIDww6gXtxYEHZpWpfQD6dkhaTr8yAY52iM4BA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:32:27.194118Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.07367","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:11f5baaeedb3b5e8898867433a79d460bf6e24dbd97429f5e764894cbb05ea74","sha256:a2cc322ea17890300f80130ae833096415222fc58ccfd87bdbb5c08b8c2bf09f"],"state_sha256":"023c73b8a36c3976fc34258734e1a501403ff72608c40a981b15cd6e60b37426"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SFT/cju+k8KQaYR3tVi0N2F0qNUJ6WxBb7QuEieWR9mUsh3BYCqQAVRKEG2QsZBaNY6wwE9AEjtPE/Wjes13DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T13:01:20.190678Z","bundle_sha256":"145039f6188e8087a19fb2d5879b2ff2fdd89df31ce13dace66730c479522842"}}