{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:LXW3A2TKAVDL67337AZKB3WHVT","short_pith_number":"pith:LXW3A2TK","canonical_record":{"source":{"id":"2104.06182","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-13T13:32:55Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"a05f4b04953dce3ef8b4dfd26834387749bcb21ca21cb9ab344ab14fee6afe5f","abstract_canon_sha256":"e65c4b3ef1a609ceccea9b8f5fb18d79e49c0ffe391a38ff3c71384afb63cfac"},"schema_version":"1.0"},"canonical_sha256":"5dedb06a6a0546bf7f7bf832a0eec7acf590c97a4e8188d037855c8909f3e7a4","source":{"kind":"arxiv","id":"2104.06182","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.06182","created_at":"2026-07-05T02:31:29Z"},{"alias_kind":"arxiv_version","alias_value":"2104.06182v1","created_at":"2026-07-05T02:31:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.06182","created_at":"2026-07-05T02:31:29Z"},{"alias_kind":"pith_short_12","alias_value":"LXW3A2TKAVDL","created_at":"2026-07-05T02:31:29Z"},{"alias_kind":"pith_short_16","alias_value":"LXW3A2TKAVDL6733","created_at":"2026-07-05T02:31:29Z"},{"alias_kind":"pith_short_8","alias_value":"LXW3A2TK","created_at":"2026-07-05T02:31:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:LXW3A2TKAVDL67337AZKB3WHVT","target":"record","payload":{"canonical_record":{"source":{"id":"2104.06182","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-13T13:32:55Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"a05f4b04953dce3ef8b4dfd26834387749bcb21ca21cb9ab344ab14fee6afe5f","abstract_canon_sha256":"e65c4b3ef1a609ceccea9b8f5fb18d79e49c0ffe391a38ff3c71384afb63cfac"},"schema_version":"1.0"},"canonical_sha256":"5dedb06a6a0546bf7f7bf832a0eec7acf590c97a4e8188d037855c8909f3e7a4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:31:29.779084Z","signature_b64":"LRo8XSZmvJ/jD9nwryfmv2WBiDFV1RDn+pjJCk6WgTMU/hKjYUr6g191aR5dGbmo0esXNiDvLTJJ5m7kCSysDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5dedb06a6a0546bf7f7bf832a0eec7acf590c97a4e8188d037855c8909f3e7a4","last_reissued_at":"2026-07-05T02:31:29.778659Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:31:29.778659Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2104.06182","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":"2026-07-05T02:31:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6zcnz5m/z5bQpOs9xpf7AQfcJIKf0qNFLqD9lJq+2GaFoQjopMMqdxFlhqZLN5p+7L4lnCUazBJ2VEoSkZZ3CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:20:51.281947Z"},"content_sha256":"bf028540841e881f4a35525612abbaf1b4273857c7fc983c74a24ab76912f19b","schema_version":"1.0","event_id":"sha256:bf028540841e881f4a35525612abbaf1b4273857c7fc983c74a24ab76912f19b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:LXW3A2TKAVDL67337AZKB3WHVT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Understanding Transformers for Bot Detection in Twitter","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Andres Garcia-Silva, Cristian Berrio, Jose Manuel Gomez-Perez","submitted_at":"2021-04-13T13:32:55Z","abstract_excerpt":"In this paper we shed light on the impact of fine-tuning over social media data in the internal representations of neural language models. We focus on bot detection in Twitter, a key task to mitigate and counteract the automatic spreading of disinformation and bias in social media. We investigate the use of pre-trained language models to tackle the detection of tweets generated by a bot or a human account based exclusively on its content. Unlike the general trend in benchmarks like GLUE, where BERT generally outperforms generative transformers like GPT and GPT-2 for most classification tasks o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.06182","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/2104.06182/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":"2026-07-05T02:31:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Nut8ptGTaB+kfQlWoRj72TIl9NhizOF3rlUk0pqZP7x3pTpcewlljWcagJOMqRwpE4fdjs13/FYyD2ypR/hxDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T16:20:51.282906Z"},"content_sha256":"b9aa3143104078fb86f192a3a1a69fc5c1bf6715ef5ff420a288b7d1b5fc1244","schema_version":"1.0","event_id":"sha256:b9aa3143104078fb86f192a3a1a69fc5c1bf6715ef5ff420a288b7d1b5fc1244"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LXW3A2TKAVDL67337AZKB3WHVT/bundle.json","state_url":"https://pith.science/pith/LXW3A2TKAVDL67337AZKB3WHVT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LXW3A2TKAVDL67337AZKB3WHVT/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":"2026-08-09T16:20:51Z","links":{"resolver":"https://pith.science/pith/LXW3A2TKAVDL67337AZKB3WHVT","bundle":"https://pith.science/pith/LXW3A2TKAVDL67337AZKB3WHVT/bundle.json","state":"https://pith.science/pith/LXW3A2TKAVDL67337AZKB3WHVT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LXW3A2TKAVDL67337AZKB3WHVT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:LXW3A2TKAVDL67337AZKB3WHVT","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":"e65c4b3ef1a609ceccea9b8f5fb18d79e49c0ffe391a38ff3c71384afb63cfac","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-13T13:32:55Z","title_canon_sha256":"a05f4b04953dce3ef8b4dfd26834387749bcb21ca21cb9ab344ab14fee6afe5f"},"schema_version":"1.0","source":{"id":"2104.06182","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2104.06182","created_at":"2026-07-05T02:31:29Z"},{"alias_kind":"arxiv_version","alias_value":"2104.06182v1","created_at":"2026-07-05T02:31:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2104.06182","created_at":"2026-07-05T02:31:29Z"},{"alias_kind":"pith_short_12","alias_value":"LXW3A2TKAVDL","created_at":"2026-07-05T02:31:29Z"},{"alias_kind":"pith_short_16","alias_value":"LXW3A2TKAVDL6733","created_at":"2026-07-05T02:31:29Z"},{"alias_kind":"pith_short_8","alias_value":"LXW3A2TK","created_at":"2026-07-05T02:31:29Z"}],"graph_snapshots":[{"event_id":"sha256:b9aa3143104078fb86f192a3a1a69fc5c1bf6715ef5ff420a288b7d1b5fc1244","target":"graph","created_at":"2026-07-05T02:31:29Z","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/2104.06182/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper we shed light on the impact of fine-tuning over social media data in the internal representations of neural language models. We focus on bot detection in Twitter, a key task to mitigate and counteract the automatic spreading of disinformation and bias in social media. We investigate the use of pre-trained language models to tackle the detection of tweets generated by a bot or a human account based exclusively on its content. Unlike the general trend in benchmarks like GLUE, where BERT generally outperforms generative transformers like GPT and GPT-2 for most classification tasks o","authors_text":"Andres Garcia-Silva, Cristian Berrio, Jose Manuel Gomez-Perez","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-13T13:32:55Z","title":"Understanding Transformers for Bot Detection in Twitter"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2104.06182","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:bf028540841e881f4a35525612abbaf1b4273857c7fc983c74a24ab76912f19b","target":"record","created_at":"2026-07-05T02:31:29Z","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":"e65c4b3ef1a609ceccea9b8f5fb18d79e49c0ffe391a38ff3c71384afb63cfac","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2021-04-13T13:32:55Z","title_canon_sha256":"a05f4b04953dce3ef8b4dfd26834387749bcb21ca21cb9ab344ab14fee6afe5f"},"schema_version":"1.0","source":{"id":"2104.06182","kind":"arxiv","version":1}},"canonical_sha256":"5dedb06a6a0546bf7f7bf832a0eec7acf590c97a4e8188d037855c8909f3e7a4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5dedb06a6a0546bf7f7bf832a0eec7acf590c97a4e8188d037855c8909f3e7a4","first_computed_at":"2026-07-05T02:31:29.778659Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:31:29.778659Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LRo8XSZmvJ/jD9nwryfmv2WBiDFV1RDn+pjJCk6WgTMU/hKjYUr6g191aR5dGbmo0esXNiDvLTJJ5m7kCSysDA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:31:29.779084Z","signed_message":"canonical_sha256_bytes"},"source_id":"2104.06182","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:bf028540841e881f4a35525612abbaf1b4273857c7fc983c74a24ab76912f19b","sha256:b9aa3143104078fb86f192a3a1a69fc5c1bf6715ef5ff420a288b7d1b5fc1244"],"state_sha256":"b0562213c9102576e4dcad1e87f290a98ccd6482cfb52941492c75f10152c479"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yp8dO+gebaLsdmQ4FHxJgcUi7qYZv5LtGXkO2BLVgguC7sUhKW16M+65Ql9SdHBgtdQ7RsO5DI+jlxK6icUaDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T16:20:51.288474Z","bundle_sha256":"7844a633397e03aa4de1cf9a33b26ac442e55326437909568ffb276ecf06d690"}}