{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:5PQVFZD7FUYINLILOUCPJGWDA2","short_pith_number":"pith:5PQVFZD7","canonical_record":{"source":{"id":"2310.12800","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-19T14:55:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"04657e93f096159147b475c685dd3ed2a557aa49006c5af7390868d8777dffdb","abstract_canon_sha256":"07e08ee30a8f2b333a0479f99576217f46be8be647363920323c316596734b27"},"schema_version":"1.0"},"canonical_sha256":"ebe152e47f2d3086ad0b7504f49ac306afbc9fd91ecb6a1d94c9c96128739e57","source":{"kind":"arxiv","id":"2310.12800","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.12800","created_at":"2026-07-05T07:02:42Z"},{"alias_kind":"arxiv_version","alias_value":"2310.12800v1","created_at":"2026-07-05T07:02:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.12800","created_at":"2026-07-05T07:02:42Z"},{"alias_kind":"pith_short_12","alias_value":"5PQVFZD7FUYI","created_at":"2026-07-05T07:02:42Z"},{"alias_kind":"pith_short_16","alias_value":"5PQVFZD7FUYINLIL","created_at":"2026-07-05T07:02:42Z"},{"alias_kind":"pith_short_8","alias_value":"5PQVFZD7","created_at":"2026-07-05T07:02:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:5PQVFZD7FUYINLILOUCPJGWDA2","target":"record","payload":{"canonical_record":{"source":{"id":"2310.12800","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-19T14:55:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"04657e93f096159147b475c685dd3ed2a557aa49006c5af7390868d8777dffdb","abstract_canon_sha256":"07e08ee30a8f2b333a0479f99576217f46be8be647363920323c316596734b27"},"schema_version":"1.0"},"canonical_sha256":"ebe152e47f2d3086ad0b7504f49ac306afbc9fd91ecb6a1d94c9c96128739e57","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:02:42.875096Z","signature_b64":"FKxcJ2e8wlDqDXJoi+P1dwuuwoVFvDgxWkqPJWCCvopAxV2J6E/rglmDoIApObJE9zYq5j9RxLIZ5HE0K0+RAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ebe152e47f2d3086ad0b7504f49ac306afbc9fd91ecb6a1d94c9c96128739e57","last_reissued_at":"2026-07-05T07:02:42.874233Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:02:42.874233Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.12800","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":"2026-07-05T07:02:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1lpZcDPq+5tfDzWZW0pfq76VwSpSXAWqepNRWYkMwlqI3d6RrRPSwN5TPEQOwFciPbq3ssXZF5xVILqZ1mIbCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T18:12:20.022499Z"},"content_sha256":"0da33f3531cf0d72489a7aecb4d77cb7074ddd961dc1644936f298f612bd67c2","schema_version":"1.0","event_id":"sha256:0da33f3531cf0d72489a7aecb4d77cb7074ddd961dc1644936f298f612bd67c2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:5PQVFZD7FUYINLILOUCPJGWDA2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploring Graph Neural Networks for Indian Legal Judgment Prediction","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Mann Khatri, Mirza Yusuf, Ponnurangam Kumaraguru, Rajiv Ratn Shah, Yaman Kumar","submitted_at":"2023-10-19T14:55:51Z","abstract_excerpt":"The burdensome impact of a skewed judges-to-cases ratio on the judicial system manifests in an overwhelming backlog of pending cases alongside an ongoing influx of new ones. To tackle this issue and expedite the judicial process, the proposition of an automated system capable of suggesting case outcomes based on factual evidence and precedent from past cases gains significance. This research paper centres on developing a graph neural network-based model to address the Legal Judgment Prediction (LJP) problem, recognizing the intrinsic graph structure of judicial cases and making it a binary nod"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.12800","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/2310.12800/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":"2026-07-05T07:02:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IOKNmvEy69cuGv5g5yGxPZXoZ0U0VfJLOxcJsdcGv9f7wImbyUrSmWYgkSYqP5V60AyZriUGHyrRZFSzyJ8DDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T18:12:20.023425Z"},"content_sha256":"df2f1a7baa37a50e159fea6192cdf6dd2ae353610dca3ccd7ec982b219dbcec8","schema_version":"1.0","event_id":"sha256:df2f1a7baa37a50e159fea6192cdf6dd2ae353610dca3ccd7ec982b219dbcec8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5PQVFZD7FUYINLILOUCPJGWDA2/bundle.json","state_url":"https://pith.science/pith/5PQVFZD7FUYINLILOUCPJGWDA2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5PQVFZD7FUYINLILOUCPJGWDA2/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":"2026-08-19T18:12:20Z","links":{"resolver":"https://pith.science/pith/5PQVFZD7FUYINLILOUCPJGWDA2","bundle":"https://pith.science/pith/5PQVFZD7FUYINLILOUCPJGWDA2/bundle.json","state":"https://pith.science/pith/5PQVFZD7FUYINLILOUCPJGWDA2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5PQVFZD7FUYINLILOUCPJGWDA2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5PQVFZD7FUYINLILOUCPJGWDA2","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":"07e08ee30a8f2b333a0479f99576217f46be8be647363920323c316596734b27","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-19T14:55:51Z","title_canon_sha256":"04657e93f096159147b475c685dd3ed2a557aa49006c5af7390868d8777dffdb"},"schema_version":"1.0","source":{"id":"2310.12800","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.12800","created_at":"2026-07-05T07:02:42Z"},{"alias_kind":"arxiv_version","alias_value":"2310.12800v1","created_at":"2026-07-05T07:02:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.12800","created_at":"2026-07-05T07:02:42Z"},{"alias_kind":"pith_short_12","alias_value":"5PQVFZD7FUYI","created_at":"2026-07-05T07:02:42Z"},{"alias_kind":"pith_short_16","alias_value":"5PQVFZD7FUYINLIL","created_at":"2026-07-05T07:02:42Z"},{"alias_kind":"pith_short_8","alias_value":"5PQVFZD7","created_at":"2026-07-05T07:02:42Z"}],"graph_snapshots":[{"event_id":"sha256:df2f1a7baa37a50e159fea6192cdf6dd2ae353610dca3ccd7ec982b219dbcec8","target":"graph","created_at":"2026-07-05T07:02:42Z","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/2310.12800/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The burdensome impact of a skewed judges-to-cases ratio on the judicial system manifests in an overwhelming backlog of pending cases alongside an ongoing influx of new ones. To tackle this issue and expedite the judicial process, the proposition of an automated system capable of suggesting case outcomes based on factual evidence and precedent from past cases gains significance. This research paper centres on developing a graph neural network-based model to address the Legal Judgment Prediction (LJP) problem, recognizing the intrinsic graph structure of judicial cases and making it a binary nod","authors_text":"Mann Khatri, Mirza Yusuf, Ponnurangam Kumaraguru, Rajiv Ratn Shah, Yaman Kumar","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-19T14:55:51Z","title":"Exploring Graph Neural Networks for Indian Legal Judgment Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.12800","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":"sha256:0da33f3531cf0d72489a7aecb4d77cb7074ddd961dc1644936f298f612bd67c2","target":"record","created_at":"2026-07-05T07:02:42Z","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":"07e08ee30a8f2b333a0479f99576217f46be8be647363920323c316596734b27","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-19T14:55:51Z","title_canon_sha256":"04657e93f096159147b475c685dd3ed2a557aa49006c5af7390868d8777dffdb"},"schema_version":"1.0","source":{"id":"2310.12800","kind":"arxiv","version":1}},"canonical_sha256":"ebe152e47f2d3086ad0b7504f49ac306afbc9fd91ecb6a1d94c9c96128739e57","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ebe152e47f2d3086ad0b7504f49ac306afbc9fd91ecb6a1d94c9c96128739e57","first_computed_at":"2026-07-05T07:02:42.874233Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:02:42.874233Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FKxcJ2e8wlDqDXJoi+P1dwuuwoVFvDgxWkqPJWCCvopAxV2J6E/rglmDoIApObJE9zYq5j9RxLIZ5HE0K0+RAg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:02:42.875096Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.12800","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0da33f3531cf0d72489a7aecb4d77cb7074ddd961dc1644936f298f612bd67c2","sha256:df2f1a7baa37a50e159fea6192cdf6dd2ae353610dca3ccd7ec982b219dbcec8"],"state_sha256":"067a0b7222a34588f2cd47567d5b78c5db3da02fb08cc8d7a6d9573fbc128fd3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WZbfEilJKN2zh3d8IQI5iivboIwd7U0iX626zpJbamLQVoU5mqvwbfLWZ8ztYJUpg01iI6VaN03RtBxEZ8TIBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T18:12:20.029676Z","bundle_sha256":"e3ccfb8842fda40627848cb1b54ae9e92de1f52ec69ee71e50b489e7e421a2b8"}}