{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:TPFZW6SVAJZUTJS7ZATYGTWBYY","short_pith_number":"pith:TPFZW6SV","canonical_record":{"source":{"id":"1908.02282","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-05T18:14:06Z","cross_cats_sorted":["cs.AI","cs.HC","cs.LG"],"title_canon_sha256":"04d310b1d345cdc1c95eada0d1982400ed23335c46b0808e9b31df12007cfaa3","abstract_canon_sha256":"b683c93369437c488dbeb3b6933ea3f8f231ad62e46d3fcb989c67f3b1c1e53c"},"schema_version":"1.0"},"canonical_sha256":"9bcb9b7a55027349a65fc827834ec1c633b3c8786d16b69b76805ff034a4bace","source":{"kind":"arxiv","id":"1908.02282","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.02282","created_at":"2026-07-04T23:56:49Z"},{"alias_kind":"arxiv_version","alias_value":"1908.02282v1","created_at":"2026-07-04T23:56:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.02282","created_at":"2026-07-04T23:56:49Z"},{"alias_kind":"pith_short_12","alias_value":"TPFZW6SVAJZU","created_at":"2026-07-04T23:56:49Z"},{"alias_kind":"pith_short_16","alias_value":"TPFZW6SVAJZUTJS7","created_at":"2026-07-04T23:56:49Z"},{"alias_kind":"pith_short_8","alias_value":"TPFZW6SV","created_at":"2026-07-04T23:56:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:TPFZW6SVAJZUTJS7ZATYGTWBYY","target":"record","payload":{"canonical_record":{"source":{"id":"1908.02282","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-05T18:14:06Z","cross_cats_sorted":["cs.AI","cs.HC","cs.LG"],"title_canon_sha256":"04d310b1d345cdc1c95eada0d1982400ed23335c46b0808e9b31df12007cfaa3","abstract_canon_sha256":"b683c93369437c488dbeb3b6933ea3f8f231ad62e46d3fcb989c67f3b1c1e53c"},"schema_version":"1.0"},"canonical_sha256":"9bcb9b7a55027349a65fc827834ec1c633b3c8786d16b69b76805ff034a4bace","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-04T23:56:49.389566Z","signature_b64":"RznpdJ+okmxMDN3ZgtkW7ZPPwmiGs09/p8WlLghh/z8qcnUrh0aVnxDHi/sPa9IG3d/XO6ck9Eup+xgB6JgVDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9bcb9b7a55027349a65fc827834ec1c633b3c8786d16b69b76805ff034a4bace","last_reissued_at":"2026-07-04T23:56:49.389151Z","signature_status":"signed_v1","first_computed_at":"2026-07-04T23:56:49.389151Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1908.02282","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":"2026-07-04T23:56:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7heRgqYaAKuRHOodpBijzeGl+YIezYQVnX+nkPKjsLz3JVX8YByAtOMxKq03WLPw9AHkv0iQBWMGEBYyLfagBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T21:23:08.460170Z"},"content_sha256":"d145069cc61a0246d0473f168229f4f503de3017cdc66b1c4c850add38bd48b1","schema_version":"1.0","event_id":"sha256:d145069cc61a0246d0473f168229f4f503de3017cdc66b1c4c850add38bd48b1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:TPFZW6SVAJZUTJS7ZATYGTWBYY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Weakly-Supervised Attention-based Visualization Tool for Assessing Political Affiliation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.HC","cs.LG"],"primary_cat":"cs.CL","authors_text":"Alana Romanella, Amit Ramesh, Srijith Rajamohan","submitted_at":"2019-08-05T18:14:06Z","abstract_excerpt":"In this work, we seek to finetune a weakly-supervised expert-guided Deep Neural Network (DNN) for the purpose of determining political affiliations. In this context, stance detection is used for determining political affiliation or ideology which is framed in the form of relative proximities between entities in a low-dimensional space. An attention-based mechanism is used to provide model interpretability. A Deep Neural Network for Natural Language Understanding (NLU) using static and contextual embeddings is trained and evaluated. Various techniques to visualize the projections generated from"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.02282","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/1908.02282/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":"2026-07-04T23:56:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9UWtMIJMvdSxE+9Vn2cQxF2I+xfNRol3L2qCtgftfSnD92RUfMF5GZDN8CUxltTJ4y6CJe2aioJtEiDSpqJmDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T21:23:08.460483Z"},"content_sha256":"063217d6334818c03130e9377a21886a627cbfd98b6061675278dead35a219cb","schema_version":"1.0","event_id":"sha256:063217d6334818c03130e9377a21886a627cbfd98b6061675278dead35a219cb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TPFZW6SVAJZUTJS7ZATYGTWBYY/bundle.json","state_url":"https://pith.science/pith/TPFZW6SVAJZUTJS7ZATYGTWBYY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TPFZW6SVAJZUTJS7ZATYGTWBYY/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":"2026-08-14T21:23:08Z","links":{"resolver":"https://pith.science/pith/TPFZW6SVAJZUTJS7ZATYGTWBYY","bundle":"https://pith.science/pith/TPFZW6SVAJZUTJS7ZATYGTWBYY/bundle.json","state":"https://pith.science/pith/TPFZW6SVAJZUTJS7ZATYGTWBYY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TPFZW6SVAJZUTJS7ZATYGTWBYY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:TPFZW6SVAJZUTJS7ZATYGTWBYY","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":"b683c93369437c488dbeb3b6933ea3f8f231ad62e46d3fcb989c67f3b1c1e53c","cross_cats_sorted":["cs.AI","cs.HC","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-05T18:14:06Z","title_canon_sha256":"04d310b1d345cdc1c95eada0d1982400ed23335c46b0808e9b31df12007cfaa3"},"schema_version":"1.0","source":{"id":"1908.02282","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.02282","created_at":"2026-07-04T23:56:49Z"},{"alias_kind":"arxiv_version","alias_value":"1908.02282v1","created_at":"2026-07-04T23:56:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.02282","created_at":"2026-07-04T23:56:49Z"},{"alias_kind":"pith_short_12","alias_value":"TPFZW6SVAJZU","created_at":"2026-07-04T23:56:49Z"},{"alias_kind":"pith_short_16","alias_value":"TPFZW6SVAJZUTJS7","created_at":"2026-07-04T23:56:49Z"},{"alias_kind":"pith_short_8","alias_value":"TPFZW6SV","created_at":"2026-07-04T23:56:49Z"}],"graph_snapshots":[{"event_id":"sha256:063217d6334818c03130e9377a21886a627cbfd98b6061675278dead35a219cb","target":"graph","created_at":"2026-07-04T23:56:49Z","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/1908.02282/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, we seek to finetune a weakly-supervised expert-guided Deep Neural Network (DNN) for the purpose of determining political affiliations. In this context, stance detection is used for determining political affiliation or ideology which is framed in the form of relative proximities between entities in a low-dimensional space. An attention-based mechanism is used to provide model interpretability. A Deep Neural Network for Natural Language Understanding (NLU) using static and contextual embeddings is trained and evaluated. Various techniques to visualize the projections generated from","authors_text":"Alana Romanella, Amit Ramesh, Srijith Rajamohan","cross_cats":["cs.AI","cs.HC","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-05T18:14:06Z","title":"A Weakly-Supervised Attention-based Visualization Tool for Assessing Political Affiliation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.02282","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:d145069cc61a0246d0473f168229f4f503de3017cdc66b1c4c850add38bd48b1","target":"record","created_at":"2026-07-04T23:56:49Z","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":"b683c93369437c488dbeb3b6933ea3f8f231ad62e46d3fcb989c67f3b1c1e53c","cross_cats_sorted":["cs.AI","cs.HC","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-08-05T18:14:06Z","title_canon_sha256":"04d310b1d345cdc1c95eada0d1982400ed23335c46b0808e9b31df12007cfaa3"},"schema_version":"1.0","source":{"id":"1908.02282","kind":"arxiv","version":1}},"canonical_sha256":"9bcb9b7a55027349a65fc827834ec1c633b3c8786d16b69b76805ff034a4bace","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9bcb9b7a55027349a65fc827834ec1c633b3c8786d16b69b76805ff034a4bace","first_computed_at":"2026-07-04T23:56:49.389151Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:56:49.389151Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RznpdJ+okmxMDN3ZgtkW7ZPPwmiGs09/p8WlLghh/z8qcnUrh0aVnxDHi/sPa9IG3d/XO6ck9Eup+xgB6JgVDg==","signature_status":"signed_v1","signed_at":"2026-07-04T23:56:49.389566Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.02282","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d145069cc61a0246d0473f168229f4f503de3017cdc66b1c4c850add38bd48b1","sha256:063217d6334818c03130e9377a21886a627cbfd98b6061675278dead35a219cb"],"state_sha256":"a4ce3edd97680bec0a90dcc9a851d9225783bbd1479da7718df1c4452e80911d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3IV+CE3xokLjFcWf7NgGH/VzCmIkRWSM5eAewyx7eV6F1kXLjj9RsUshMY2e7COcFG39AVuA8S2ReZBxtl+rCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T21:23:08.464383Z","bundle_sha256":"508395e646bc647e42b33b7440579f61c04fbf2d1a713a80b2e4686d1750d9d1"}}