{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:DO2XBQFGOQ2T7G2TOOUHFTR45I","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":"3139a466dce2fd44693ad5dd5743096571edabeebedb7f53a1a628979453e440","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-02T12:55:51Z","title_canon_sha256":"ff4459995a98fec513de5866f57f8bc8724a629325b639f4ef9d2141c950c097"},"schema_version":"1.0","source":{"id":"2506.01615","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.01615","created_at":"2026-07-05T11:15:01Z"},{"alias_kind":"arxiv_version","alias_value":"2506.01615v2","created_at":"2026-07-05T11:15:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01615","created_at":"2026-07-05T11:15:01Z"},{"alias_kind":"pith_short_12","alias_value":"DO2XBQFGOQ2T","created_at":"2026-07-05T11:15:01Z"},{"alias_kind":"pith_short_16","alias_value":"DO2XBQFGOQ2T7G2T","created_at":"2026-07-05T11:15:01Z"},{"alias_kind":"pith_short_8","alias_value":"DO2XBQFG","created_at":"2026-07-05T11:15:01Z"}],"graph_snapshots":[{"event_id":"sha256:d8fe5e80bf9910e692efc78f6630b00fb5b25fa492a0ba02becdf6c9d864c5dd","target":"graph","created_at":"2026-07-05T11:15:01Z","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/2506.01615/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Retrieval-Augmented Generation (RAG) systems enable language models to access relevant information and generate accurate, well-grounded, and contextually informed responses. However, for Indian languages, the development of high-quality RAG systems is hindered by the lack of two critical resources: (1) evaluation benchmarks for retrieval and generation tasks, and (2) large-scale training datasets for multilingual retrieval. Most existing benchmarks and datasets are centered around English or high-resource languages, making it difficult to extend RAG capabilities to the diverse linguistic lands","authors_text":"Anoop Kunchukuttan, Pasunuti Prasanjith, Prathmesh B More, Raj Dabre","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-02T12:55:51Z","title":"IndicRAGSuite: Large-Scale Datasets and a Benchmark for Indian Language RAG Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01615","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":"sha256:801ffff20f6a0d858edde24a8037d1e80be12cf3f002c1033589e0374e359c74","target":"record","created_at":"2026-07-05T11:15:01Z","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":"3139a466dce2fd44693ad5dd5743096571edabeebedb7f53a1a628979453e440","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-02T12:55:51Z","title_canon_sha256":"ff4459995a98fec513de5866f57f8bc8724a629325b639f4ef9d2141c950c097"},"schema_version":"1.0","source":{"id":"2506.01615","kind":"arxiv","version":2}},"canonical_sha256":"1bb570c0a674353f9b5373a872ce3cea19675aa1b5c26745fb19cd1bb3293ea9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1bb570c0a674353f9b5373a872ce3cea19675aa1b5c26745fb19cd1bb3293ea9","first_computed_at":"2026-07-05T11:15:01.609825Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:15:01.609825Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"G+4wB61VWa8/zO7TSqlKSm7u2PxXI34zpedQbYAc6DqN+h+t+af97ID/9rp3dlU1FPFRphmmfzGa4haAFHtNCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:15:01.610347Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.01615","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:801ffff20f6a0d858edde24a8037d1e80be12cf3f002c1033589e0374e359c74","sha256:d8fe5e80bf9910e692efc78f6630b00fb5b25fa492a0ba02becdf6c9d864c5dd"],"state_sha256":"7e85257142ca63ac6bd94207c1efb62aace6d805717ef0cb92dd329e545ba580"}