{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:AUQHLRP2I4SVMLPU6Y6OMVO5N4","short_pith_number":"pith:AUQHLRP2","canonical_record":{"source":{"id":"2503.18792","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-03-24T15:39:25Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CY"],"title_canon_sha256":"73de74650607d5426d978652f1177b165f869113ba369cb646c1db6bddc6f26d","abstract_canon_sha256":"f608201a144e4d40b64c8d605f37ada1545c3385f36898e99be76bc3249a0316"},"schema_version":"1.0"},"canonical_sha256":"052075c5fa4725562df4f63ce655dd6f05595f12abecc362cac404f54d81f6e6","source":{"kind":"arxiv","id":"2503.18792","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.18792","created_at":"2026-07-05T11:13:23Z"},{"alias_kind":"arxiv_version","alias_value":"2503.18792v2","created_at":"2026-07-05T11:13:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.18792","created_at":"2026-07-05T11:13:23Z"},{"alias_kind":"pith_short_12","alias_value":"AUQHLRP2I4SV","created_at":"2026-07-05T11:13:23Z"},{"alias_kind":"pith_short_16","alias_value":"AUQHLRP2I4SVMLPU","created_at":"2026-07-05T11:13:23Z"},{"alias_kind":"pith_short_8","alias_value":"AUQHLRP2","created_at":"2026-07-05T11:13:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:AUQHLRP2I4SVMLPU6Y6OMVO5N4","target":"record","payload":{"canonical_record":{"source":{"id":"2503.18792","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-03-24T15:39:25Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CY"],"title_canon_sha256":"73de74650607d5426d978652f1177b165f869113ba369cb646c1db6bddc6f26d","abstract_canon_sha256":"f608201a144e4d40b64c8d605f37ada1545c3385f36898e99be76bc3249a0316"},"schema_version":"1.0"},"canonical_sha256":"052075c5fa4725562df4f63ce655dd6f05595f12abecc362cac404f54d81f6e6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:13:23.021066Z","signature_b64":"ZB7t1XLwMgyY+lPfg+M+zGcQLcJgK7ydawS0e/xHZlAp1spf7nTlDn75Lhf51hJNvvojoU5K+cKoOtZ4FF9yBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"052075c5fa4725562df4f63ce655dd6f05595f12abecc362cac404f54d81f6e6","last_reissued_at":"2026-07-05T11:13:23.020627Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:13:23.020627Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.18792","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":"2026-07-05T11:13:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gqDxby6zXElQwUwzWKG9zSuuE5JQFQzCTRQFiGa6TCuonBnAqOc/U/HY3RhOwI5eUjihxxPb/ePpI/CCcDsoCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T11:12:11.211723Z"},"content_sha256":"85adfd9f53be87a92f069a5f60d9f430f107ae42cf9789ee497730f3e2612ae0","schema_version":"1.0","event_id":"sha256:85adfd9f53be87a92f069a5f60d9f430f107ae42cf9789ee497730f3e2612ae0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:AUQHLRP2I4SVMLPU6Y6OMVO5N4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"REALM: A Dataset of Real-World LLM Use Cases","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.CY"],"primary_cat":"cs.HC","authors_text":"Fei Fang, Hong Shen, Jingwen Cheng, Kshitish Ghate, Wenyue Hua, William Yang Wang","submitted_at":"2025-03-24T15:39:25Z","abstract_excerpt":"Large Language Models (LLMs), such as the GPT series, have driven significant industrial applications, leading to economic and societal transformations. However, a comprehensive understanding of their real-world applications remains limited. To address this, we introduce REALM, a dataset of over 94,000 LLM use cases collected from Reddit and news articles. REALM captures two key dimensions: the diverse applications of LLMs and the demographics of their users. It categorizes LLM applications and explores how users' occupations relate to the types of applications they use. By integrating real-wo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.18792","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/2503.18792/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":"2026-07-05T11:13:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6x8Oqsz8EOQ2y0GrLe2Fz73GKoty2RJAjIGFbHC80PSLRgAroK7/t7kfvs3Rr8nFNJ1v6eZxl/EiovCkyCT0DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T11:12:11.212678Z"},"content_sha256":"18b06b4d6470fc6f54c30c1e57e935f1492add9fe9e4b98bded2a01534f983f8","schema_version":"1.0","event_id":"sha256:18b06b4d6470fc6f54c30c1e57e935f1492add9fe9e4b98bded2a01534f983f8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AUQHLRP2I4SVMLPU6Y6OMVO5N4/bundle.json","state_url":"https://pith.science/pith/AUQHLRP2I4SVMLPU6Y6OMVO5N4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AUQHLRP2I4SVMLPU6Y6OMVO5N4/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":"2026-08-14T11:12:11Z","links":{"resolver":"https://pith.science/pith/AUQHLRP2I4SVMLPU6Y6OMVO5N4","bundle":"https://pith.science/pith/AUQHLRP2I4SVMLPU6Y6OMVO5N4/bundle.json","state":"https://pith.science/pith/AUQHLRP2I4SVMLPU6Y6OMVO5N4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AUQHLRP2I4SVMLPU6Y6OMVO5N4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:AUQHLRP2I4SVMLPU6Y6OMVO5N4","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":"f608201a144e4d40b64c8d605f37ada1545c3385f36898e99be76bc3249a0316","cross_cats_sorted":["cs.AI","cs.CL","cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-03-24T15:39:25Z","title_canon_sha256":"73de74650607d5426d978652f1177b165f869113ba369cb646c1db6bddc6f26d"},"schema_version":"1.0","source":{"id":"2503.18792","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.18792","created_at":"2026-07-05T11:13:23Z"},{"alias_kind":"arxiv_version","alias_value":"2503.18792v2","created_at":"2026-07-05T11:13:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.18792","created_at":"2026-07-05T11:13:23Z"},{"alias_kind":"pith_short_12","alias_value":"AUQHLRP2I4SV","created_at":"2026-07-05T11:13:23Z"},{"alias_kind":"pith_short_16","alias_value":"AUQHLRP2I4SVMLPU","created_at":"2026-07-05T11:13:23Z"},{"alias_kind":"pith_short_8","alias_value":"AUQHLRP2","created_at":"2026-07-05T11:13:23Z"}],"graph_snapshots":[{"event_id":"sha256:18b06b4d6470fc6f54c30c1e57e935f1492add9fe9e4b98bded2a01534f983f8","target":"graph","created_at":"2026-07-05T11:13:23Z","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/2503.18792/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs), such as the GPT series, have driven significant industrial applications, leading to economic and societal transformations. However, a comprehensive understanding of their real-world applications remains limited. To address this, we introduce REALM, a dataset of over 94,000 LLM use cases collected from Reddit and news articles. REALM captures two key dimensions: the diverse applications of LLMs and the demographics of their users. It categorizes LLM applications and explores how users' occupations relate to the types of applications they use. By integrating real-wo","authors_text":"Fei Fang, Hong Shen, Jingwen Cheng, Kshitish Ghate, Wenyue Hua, William Yang Wang","cross_cats":["cs.AI","cs.CL","cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-03-24T15:39:25Z","title":"REALM: A Dataset of Real-World LLM Use Cases"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.18792","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":"sha256:85adfd9f53be87a92f069a5f60d9f430f107ae42cf9789ee497730f3e2612ae0","target":"record","created_at":"2026-07-05T11:13:23Z","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":"f608201a144e4d40b64c8d605f37ada1545c3385f36898e99be76bc3249a0316","cross_cats_sorted":["cs.AI","cs.CL","cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-03-24T15:39:25Z","title_canon_sha256":"73de74650607d5426d978652f1177b165f869113ba369cb646c1db6bddc6f26d"},"schema_version":"1.0","source":{"id":"2503.18792","kind":"arxiv","version":2}},"canonical_sha256":"052075c5fa4725562df4f63ce655dd6f05595f12abecc362cac404f54d81f6e6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"052075c5fa4725562df4f63ce655dd6f05595f12abecc362cac404f54d81f6e6","first_computed_at":"2026-07-05T11:13:23.020627Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:13:23.020627Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZB7t1XLwMgyY+lPfg+M+zGcQLcJgK7ydawS0e/xHZlAp1spf7nTlDn75Lhf51hJNvvojoU5K+cKoOtZ4FF9yBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:13:23.021066Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.18792","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:85adfd9f53be87a92f069a5f60d9f430f107ae42cf9789ee497730f3e2612ae0","sha256:18b06b4d6470fc6f54c30c1e57e935f1492add9fe9e4b98bded2a01534f983f8"],"state_sha256":"ecc0568d59c36b2ce39dbd9ad28d094a82bdf65359f3761130f75c50b2082d04"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dg5RT73ozPZHqoLUTQf9OKHtShV4AiOAzEG+IRMySobjyPRWwoq4wvX4iOTrzM67L+BIEg3yYj6ue5cY0yrTDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T11:12:11.234708Z","bundle_sha256":"0b9ea988219afa5fd4fb80627778fbc32999242472f6267f96c01e89449abd02"}}