{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:RE7UMXDY5ZNHKUYNETEGNHZS7S","short_pith_number":"pith:RE7UMXDY","canonical_record":{"source":{"id":"2407.10899","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-07-15T16:49:26Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"81c5e2fc1f23215eba9bd2164ed9a12e9a6a5ee0f7aa862354eb74e96ed9fa20","abstract_canon_sha256":"8e8d8050d088c616ea5957495fca3ad736eef49b4369b2f984fc2bac0d5eff5e"},"schema_version":"1.0"},"canonical_sha256":"893f465c78ee5a75530d24c8669f32fc96b344b5917fa207df086c9ab4596743","source":{"kind":"arxiv","id":"2407.10899","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.10899","created_at":"2026-07-05T08:44:05Z"},{"alias_kind":"arxiv_version","alias_value":"2407.10899v1","created_at":"2026-07-05T08:44:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.10899","created_at":"2026-07-05T08:44:05Z"},{"alias_kind":"pith_short_12","alias_value":"RE7UMXDY5ZNH","created_at":"2026-07-05T08:44:05Z"},{"alias_kind":"pith_short_16","alias_value":"RE7UMXDY5ZNHKUYN","created_at":"2026-07-05T08:44:05Z"},{"alias_kind":"pith_short_8","alias_value":"RE7UMXDY","created_at":"2026-07-05T08:44:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:RE7UMXDY5ZNHKUYNETEGNHZS7S","target":"record","payload":{"canonical_record":{"source":{"id":"2407.10899","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-07-15T16:49:26Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"81c5e2fc1f23215eba9bd2164ed9a12e9a6a5ee0f7aa862354eb74e96ed9fa20","abstract_canon_sha256":"8e8d8050d088c616ea5957495fca3ad736eef49b4369b2f984fc2bac0d5eff5e"},"schema_version":"1.0"},"canonical_sha256":"893f465c78ee5a75530d24c8669f32fc96b344b5917fa207df086c9ab4596743","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:44:05.712472Z","signature_b64":"P+cA8BPy0NgNT/2c6J2AKp+efUajhQIL4cvN9HawKcl3nFCVF+1zjZQRzwlNlUCgU8X5rLrAwiiNGFjOeWp4AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"893f465c78ee5a75530d24c8669f32fc96b344b5917fa207df086c9ab4596743","last_reissued_at":"2026-07-05T08:44:05.711991Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:44:05.711991Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2407.10899","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":"2026-07-05T08:44:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DQgKfP4e9vmdOU7P2m8HpH1ZG49uFTQnFKHFaTqDK5DOyLExLtfLIIy2qybjnAgvXThrXGfPU2CgIwwy2Mo0Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T18:44:42.978751Z"},"content_sha256":"427d199ecfe8f57e9bdbe6dbdbfe9c7c5c0368cafcac68fae49f646165f7bdaf","schema_version":"1.0","event_id":"sha256:427d199ecfe8f57e9bdbe6dbdbfe9c7c5c0368cafcac68fae49f646165f7bdaf"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:RE7UMXDY5ZNHKUYNETEGNHZS7S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Leveraging LLM-Respondents for Item Evaluation: a Psychometric Analysis","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.CY","authors_text":"Shreya Bhandari, Yunting Liu, Zachary A. Pardos","submitted_at":"2024-07-15T16:49:26Z","abstract_excerpt":"Effective educational measurement relies heavily on the curation of well-designed item pools (i.e., possessing the right psychometric properties). However, item calibration is time-consuming and costly, requiring a sufficient number of respondents for the response process. We explore using six different LLMs (GPT-3.5, GPT-4, Llama 2, Llama 3, Gemini-Pro, and Cohere Command R Plus) and various combinations of them using sampling methods to produce responses with psychometric properties similar to human answers. Results show that some LLMs have comparable or higher proficiency in College Algebra"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.10899","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/2407.10899/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":"2026-07-05T08:44:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eVtSofeerCLgZmn3zMKwo8czb19qfTe3AOB/lLwgtAkoyBdC4JBdzQxmfvjswUXZxZnFjWjAL0M8Y6KZmpPzCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T18:44:42.979200Z"},"content_sha256":"282b9337d62d7bdbf38d6540762ef6d8c862174c9ee05dbcba76ab454c6b9c9a","schema_version":"1.0","event_id":"sha256:282b9337d62d7bdbf38d6540762ef6d8c862174c9ee05dbcba76ab454c6b9c9a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RE7UMXDY5ZNHKUYNETEGNHZS7S/bundle.json","state_url":"https://pith.science/pith/RE7UMXDY5ZNHKUYNETEGNHZS7S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RE7UMXDY5ZNHKUYNETEGNHZS7S/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":"2026-08-22T18:44:42Z","links":{"resolver":"https://pith.science/pith/RE7UMXDY5ZNHKUYNETEGNHZS7S","bundle":"https://pith.science/pith/RE7UMXDY5ZNHKUYNETEGNHZS7S/bundle.json","state":"https://pith.science/pith/RE7UMXDY5ZNHKUYNETEGNHZS7S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RE7UMXDY5ZNHKUYNETEGNHZS7S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:RE7UMXDY5ZNHKUYNETEGNHZS7S","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":"8e8d8050d088c616ea5957495fca3ad736eef49b4369b2f984fc2bac0d5eff5e","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-07-15T16:49:26Z","title_canon_sha256":"81c5e2fc1f23215eba9bd2164ed9a12e9a6a5ee0f7aa862354eb74e96ed9fa20"},"schema_version":"1.0","source":{"id":"2407.10899","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.10899","created_at":"2026-07-05T08:44:05Z"},{"alias_kind":"arxiv_version","alias_value":"2407.10899v1","created_at":"2026-07-05T08:44:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.10899","created_at":"2026-07-05T08:44:05Z"},{"alias_kind":"pith_short_12","alias_value":"RE7UMXDY5ZNH","created_at":"2026-07-05T08:44:05Z"},{"alias_kind":"pith_short_16","alias_value":"RE7UMXDY5ZNHKUYN","created_at":"2026-07-05T08:44:05Z"},{"alias_kind":"pith_short_8","alias_value":"RE7UMXDY","created_at":"2026-07-05T08:44:05Z"}],"graph_snapshots":[{"event_id":"sha256:282b9337d62d7bdbf38d6540762ef6d8c862174c9ee05dbcba76ab454c6b9c9a","target":"graph","created_at":"2026-07-05T08:44:05Z","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/2407.10899/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Effective educational measurement relies heavily on the curation of well-designed item pools (i.e., possessing the right psychometric properties). However, item calibration is time-consuming and costly, requiring a sufficient number of respondents for the response process. We explore using six different LLMs (GPT-3.5, GPT-4, Llama 2, Llama 3, Gemini-Pro, and Cohere Command R Plus) and various combinations of them using sampling methods to produce responses with psychometric properties similar to human answers. Results show that some LLMs have comparable or higher proficiency in College Algebra","authors_text":"Shreya Bhandari, Yunting Liu, Zachary A. Pardos","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-07-15T16:49:26Z","title":"Leveraging LLM-Respondents for Item Evaluation: a Psychometric Analysis"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.10899","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":"sha256:427d199ecfe8f57e9bdbe6dbdbfe9c7c5c0368cafcac68fae49f646165f7bdaf","target":"record","created_at":"2026-07-05T08:44:05Z","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":"8e8d8050d088c616ea5957495fca3ad736eef49b4369b2f984fc2bac0d5eff5e","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2024-07-15T16:49:26Z","title_canon_sha256":"81c5e2fc1f23215eba9bd2164ed9a12e9a6a5ee0f7aa862354eb74e96ed9fa20"},"schema_version":"1.0","source":{"id":"2407.10899","kind":"arxiv","version":1}},"canonical_sha256":"893f465c78ee5a75530d24c8669f32fc96b344b5917fa207df086c9ab4596743","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"893f465c78ee5a75530d24c8669f32fc96b344b5917fa207df086c9ab4596743","first_computed_at":"2026-07-05T08:44:05.711991Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:44:05.711991Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"P+cA8BPy0NgNT/2c6J2AKp+efUajhQIL4cvN9HawKcl3nFCVF+1zjZQRzwlNlUCgU8X5rLrAwiiNGFjOeWp4AQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:44:05.712472Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.10899","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:427d199ecfe8f57e9bdbe6dbdbfe9c7c5c0368cafcac68fae49f646165f7bdaf","sha256:282b9337d62d7bdbf38d6540762ef6d8c862174c9ee05dbcba76ab454c6b9c9a"],"state_sha256":"26bf0c1c49998b3e53b1b838389e1dadb065b9bfac87831c943fea03a9e9c406"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eJoOUv4oBLeSPd3mo4kkiu5Nmk4uo+pR4Rk+lMIofbzMkQQVmu9S9kj+2U6U3z9oICnmKZmL0tnS3NU/KnxSBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T18:44:42.982093Z","bundle_sha256":"88c21f8bb9deefd7a3ab8a40e9882e2a0ec1e682e7323407bc7ab8071651b221"}}