{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:XSJOPABRUAP4NFYTXSISOZYMSE","short_pith_number":"pith:XSJOPABR","canonical_record":{"source":{"id":"2501.15747","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-01-27T03:19:03Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"eb50a3c734c7defe1a608e51aac46ed409d4c74e35c4a7476ca9fa30ab1dd372","abstract_canon_sha256":"b6f7b0b7978619be704a52b35fc3dfade7255c9941913e6d8ffe9fd2f7738b44"},"schema_version":"1.0"},"canonical_sha256":"bc92e78031a01fc69713bc9127670c913674f67571a8d57b41a3125e8391c1f0","source":{"kind":"arxiv","id":"2501.15747","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.15747","created_at":"2026-07-05T10:06:11Z"},{"alias_kind":"arxiv_version","alias_value":"2501.15747v2","created_at":"2026-07-05T10:06:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.15747","created_at":"2026-07-05T10:06:11Z"},{"alias_kind":"pith_short_12","alias_value":"XSJOPABRUAP4","created_at":"2026-07-05T10:06:11Z"},{"alias_kind":"pith_short_16","alias_value":"XSJOPABRUAP4NFYT","created_at":"2026-07-05T10:06:11Z"},{"alias_kind":"pith_short_8","alias_value":"XSJOPABR","created_at":"2026-07-05T10:06:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:XSJOPABRUAP4NFYTXSISOZYMSE","target":"record","payload":{"canonical_record":{"source":{"id":"2501.15747","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-01-27T03:19:03Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"eb50a3c734c7defe1a608e51aac46ed409d4c74e35c4a7476ca9fa30ab1dd372","abstract_canon_sha256":"b6f7b0b7978619be704a52b35fc3dfade7255c9941913e6d8ffe9fd2f7738b44"},"schema_version":"1.0"},"canonical_sha256":"bc92e78031a01fc69713bc9127670c913674f67571a8d57b41a3125e8391c1f0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:06:11.155088Z","signature_b64":"UOhAd8IHYrolyk0X7r1SKo5uxQWnbDSj0ze1pPv0CVTJy5taASFSK8uC3HYpFBzqEjYeDojsZQVvDjKSYCu1Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc92e78031a01fc69713bc9127670c913674f67571a8d57b41a3125e8391c1f0","last_reissued_at":"2026-07-05T10:06:11.154601Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:06:11.154601Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.15747","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":"2026-07-05T10:06:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nYZxLp/5VPDiOWuKnBR9Bq/IHdGfqKjOAWH4u6rse2puiZmgjUAJxkBi/V+1T1G47kmuSaXTgux+rUL1JhSZBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T01:28:46.888022Z"},"content_sha256":"ab73a3224f9961d317b9d020334bbaf8e69916b17f5d3fdd5f8f1fc2148e57b4","schema_version":"1.0","event_id":"sha256:ab73a3224f9961d317b9d020334bbaf8e69916b17f5d3fdd5f8f1fc2148e57b4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:XSJOPABRUAP4NFYTXSISOZYMSE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"IndicMMLU-Pro: Benchmarking Indic Large Language Models on Multi-Task Language Understanding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Aman Chadha, Ashutosh Kumar, Laxmaan Balaji, Nikunj Kotecha, Sankalp KJ, Sreyoshi Bhaduri, Vinija Jain","submitted_at":"2025-01-27T03:19:03Z","abstract_excerpt":"Known by more than 1.5 billion people in the Indian subcontinent, Indic languages present unique challenges and opportunities for natural language processing (NLP) research due to their rich cultural heritage, linguistic diversity, and complex structures. IndicMMLU-Pro is a comprehensive benchmark designed to evaluate Large Language Models (LLMs) across Indic languages, building upon the MMLU Pro (Massive Multitask Language Understanding) framework. Covering major languages such as Hindi, Bengali, Gujarati, Marathi, Kannada, Punjabi, Tamil, Telugu, and Urdu, our benchmark addresses the unique "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.15747","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/2501.15747/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":"2026-07-05T10:06:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8n5eFqla4IMJs04vBANETa8xSnNtQimNMGcluCHkxlJTh/j6Q6owRbNwiHBVFa2MtQ7MRn3p4TJY6kybusntBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T01:28:46.889110Z"},"content_sha256":"035cec81b84ad9f530df02b43032bae9aa4a0974e730a6d0e7bcca565b67a8f7","schema_version":"1.0","event_id":"sha256:035cec81b84ad9f530df02b43032bae9aa4a0974e730a6d0e7bcca565b67a8f7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XSJOPABRUAP4NFYTXSISOZYMSE/bundle.json","state_url":"https://pith.science/pith/XSJOPABRUAP4NFYTXSISOZYMSE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XSJOPABRUAP4NFYTXSISOZYMSE/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":"2026-08-11T01:28:46Z","links":{"resolver":"https://pith.science/pith/XSJOPABRUAP4NFYTXSISOZYMSE","bundle":"https://pith.science/pith/XSJOPABRUAP4NFYTXSISOZYMSE/bundle.json","state":"https://pith.science/pith/XSJOPABRUAP4NFYTXSISOZYMSE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XSJOPABRUAP4NFYTXSISOZYMSE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XSJOPABRUAP4NFYTXSISOZYMSE","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":"b6f7b0b7978619be704a52b35fc3dfade7255c9941913e6d8ffe9fd2f7738b44","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-01-27T03:19:03Z","title_canon_sha256":"eb50a3c734c7defe1a608e51aac46ed409d4c74e35c4a7476ca9fa30ab1dd372"},"schema_version":"1.0","source":{"id":"2501.15747","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.15747","created_at":"2026-07-05T10:06:11Z"},{"alias_kind":"arxiv_version","alias_value":"2501.15747v2","created_at":"2026-07-05T10:06:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.15747","created_at":"2026-07-05T10:06:11Z"},{"alias_kind":"pith_short_12","alias_value":"XSJOPABRUAP4","created_at":"2026-07-05T10:06:11Z"},{"alias_kind":"pith_short_16","alias_value":"XSJOPABRUAP4NFYT","created_at":"2026-07-05T10:06:11Z"},{"alias_kind":"pith_short_8","alias_value":"XSJOPABR","created_at":"2026-07-05T10:06:11Z"}],"graph_snapshots":[{"event_id":"sha256:035cec81b84ad9f530df02b43032bae9aa4a0974e730a6d0e7bcca565b67a8f7","target":"graph","created_at":"2026-07-05T10:06:11Z","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/2501.15747/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Known by more than 1.5 billion people in the Indian subcontinent, Indic languages present unique challenges and opportunities for natural language processing (NLP) research due to their rich cultural heritage, linguistic diversity, and complex structures. IndicMMLU-Pro is a comprehensive benchmark designed to evaluate Large Language Models (LLMs) across Indic languages, building upon the MMLU Pro (Massive Multitask Language Understanding) framework. Covering major languages such as Hindi, Bengali, Gujarati, Marathi, Kannada, Punjabi, Tamil, Telugu, and Urdu, our benchmark addresses the unique ","authors_text":"Aman Chadha, Ashutosh Kumar, Laxmaan Balaji, Nikunj Kotecha, Sankalp KJ, Sreyoshi Bhaduri, Vinija Jain","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-01-27T03:19:03Z","title":"IndicMMLU-Pro: Benchmarking Indic Large Language Models on Multi-Task Language Understanding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.15747","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:ab73a3224f9961d317b9d020334bbaf8e69916b17f5d3fdd5f8f1fc2148e57b4","target":"record","created_at":"2026-07-05T10:06:11Z","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":"b6f7b0b7978619be704a52b35fc3dfade7255c9941913e6d8ffe9fd2f7738b44","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-01-27T03:19:03Z","title_canon_sha256":"eb50a3c734c7defe1a608e51aac46ed409d4c74e35c4a7476ca9fa30ab1dd372"},"schema_version":"1.0","source":{"id":"2501.15747","kind":"arxiv","version":2}},"canonical_sha256":"bc92e78031a01fc69713bc9127670c913674f67571a8d57b41a3125e8391c1f0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc92e78031a01fc69713bc9127670c913674f67571a8d57b41a3125e8391c1f0","first_computed_at":"2026-07-05T10:06:11.154601Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:06:11.154601Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UOhAd8IHYrolyk0X7r1SKo5uxQWnbDSj0ze1pPv0CVTJy5taASFSK8uC3HYpFBzqEjYeDojsZQVvDjKSYCu1Cg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:06:11.155088Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.15747","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ab73a3224f9961d317b9d020334bbaf8e69916b17f5d3fdd5f8f1fc2148e57b4","sha256:035cec81b84ad9f530df02b43032bae9aa4a0974e730a6d0e7bcca565b67a8f7"],"state_sha256":"71a0ec35721574c3fc674e0f27e8feff8f6033df893409c4b6a0707d7e3b716c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v9Bi3qxmsaCkN+Fa4rvrteUa5vo8zzCdDr5TyvRZk/84OBWrCID4RFSBSck3O6BwYEec4hOsMMeMU+plC8+0BQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T01:28:46.896758Z","bundle_sha256":"0bca8439c40ad13e8975b1e9b59a5bf12b3cb971f8a1fad50fedac4e8ad6d15b"}}