{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:PQCP7GAWJNV3CEWWKKUVFAVRWQ","short_pith_number":"pith:PQCP7GAW","canonical_record":{"source":{"id":"2605.30051","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-28T15:02:51Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"852944c7b93655d5f5bcb03bf0ccb394a50e6955c708bcb0c9bf3ed2037b18d9","abstract_canon_sha256":"758c0fcdd31734d5b52725659aae094b47737a356e5999717502fb2c43ce8243"},"schema_version":"1.0"},"canonical_sha256":"7c04ff98164b6bb112d652a95282b1b42fc51c8ebe5f043cc68e28db072de5da","source":{"kind":"arxiv","id":"2605.30051","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30051","created_at":"2026-05-29T02:06:08Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30051v1","created_at":"2026-05-29T02:06:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30051","created_at":"2026-05-29T02:06:08Z"},{"alias_kind":"pith_short_12","alias_value":"PQCP7GAWJNV3","created_at":"2026-05-29T02:06:08Z"},{"alias_kind":"pith_short_16","alias_value":"PQCP7GAWJNV3CEWW","created_at":"2026-05-29T02:06:08Z"},{"alias_kind":"pith_short_8","alias_value":"PQCP7GAW","created_at":"2026-05-29T02:06:08Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:PQCP7GAWJNV3CEWWKKUVFAVRWQ","target":"record","payload":{"canonical_record":{"source":{"id":"2605.30051","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-28T15:02:51Z","cross_cats_sorted":["cs.CY"],"title_canon_sha256":"852944c7b93655d5f5bcb03bf0ccb394a50e6955c708bcb0c9bf3ed2037b18d9","abstract_canon_sha256":"758c0fcdd31734d5b52725659aae094b47737a356e5999717502fb2c43ce8243"},"schema_version":"1.0"},"canonical_sha256":"7c04ff98164b6bb112d652a95282b1b42fc51c8ebe5f043cc68e28db072de5da","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T02:06:08.587456Z","signature_b64":"AoeE6JPvFaD0hxkaCYig+9AsfBBClEXnmwAuVWNOuHpU/AdtdD5Xiiyny6Mhaw+bcZZ+twfmC4eT/u4frj7NAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7c04ff98164b6bb112d652a95282b1b42fc51c8ebe5f043cc68e28db072de5da","last_reissued_at":"2026-05-29T02:06:08.587035Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T02:06:08.587035Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.30051","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":"2026-05-29T02:06:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vhJshX2iyJSO6raBPM76RljDc+oaKxUATLBRgOrzqzGjJiiYfbMXGr6GuYXd8CI0doKevixdBrel1rkp+jI0AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T14:28:36.709670Z"},"content_sha256":"3ff4c17881b0501f61e751ba8fc22fde37e2ca8ed4ccea71d095aa447d31f9dd","schema_version":"1.0","event_id":"sha256:3ff4c17881b0501f61e751ba8fc22fde37e2ca8ed4ccea71d095aa447d31f9dd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:PQCP7GAWJNV3CEWWKKUVFAVRWQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Who Am I? History-Aware Profiles for Student Simulation in Tutoring Dialogues","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CY"],"primary_cat":"cs.CL","authors_text":"Alexander Scarlatos, Andrew Lan, Jaewook Lee, Shuyan Huang, Simon Woodhead, Zhangqi Duan","submitted_at":"2026-05-28T15:02:51Z","abstract_excerpt":"A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students, which can facilitate tutor model evaluation and training. Existing work mostly focuses on within-dialogue simulation, which lacks context on student knowledge and behavior, partly due to not grounding in past student question-answering or dialogue interactions. In this work, we introduce the task of history-conditioned student simulation, where the goal is to accurately predict student dialogue turns by leveraging information in the student's l"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30051","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/2605.30051/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":"2026-05-29T02:06:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yaJCtOpRq+HQy/h+0JTf8kqpHih+JEiNpgyZktKQMR2D/sXH9gM7BH7IQy84prGcp5+fFvwp76UfBQN7BNsoBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T14:28:36.710331Z"},"content_sha256":"485b03af3b53139d8eb0e6c688f42f6c5fa158bf04fd76ba20a7593d195430ce","schema_version":"1.0","event_id":"sha256:485b03af3b53139d8eb0e6c688f42f6c5fa158bf04fd76ba20a7593d195430ce"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PQCP7GAWJNV3CEWWKKUVFAVRWQ/bundle.json","state_url":"https://pith.science/pith/PQCP7GAWJNV3CEWWKKUVFAVRWQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PQCP7GAWJNV3CEWWKKUVFAVRWQ/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":"2026-06-02T14:28:36Z","links":{"resolver":"https://pith.science/pith/PQCP7GAWJNV3CEWWKKUVFAVRWQ","bundle":"https://pith.science/pith/PQCP7GAWJNV3CEWWKKUVFAVRWQ/bundle.json","state":"https://pith.science/pith/PQCP7GAWJNV3CEWWKKUVFAVRWQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PQCP7GAWJNV3CEWWKKUVFAVRWQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:PQCP7GAWJNV3CEWWKKUVFAVRWQ","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":"758c0fcdd31734d5b52725659aae094b47737a356e5999717502fb2c43ce8243","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-28T15:02:51Z","title_canon_sha256":"852944c7b93655d5f5bcb03bf0ccb394a50e6955c708bcb0c9bf3ed2037b18d9"},"schema_version":"1.0","source":{"id":"2605.30051","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30051","created_at":"2026-05-29T02:06:08Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30051v1","created_at":"2026-05-29T02:06:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30051","created_at":"2026-05-29T02:06:08Z"},{"alias_kind":"pith_short_12","alias_value":"PQCP7GAWJNV3","created_at":"2026-05-29T02:06:08Z"},{"alias_kind":"pith_short_16","alias_value":"PQCP7GAWJNV3CEWW","created_at":"2026-05-29T02:06:08Z"},{"alias_kind":"pith_short_8","alias_value":"PQCP7GAW","created_at":"2026-05-29T02:06:08Z"}],"graph_snapshots":[{"event_id":"sha256:485b03af3b53139d8eb0e6c688f42f6c5fa158bf04fd76ba20a7593d195430ce","target":"graph","created_at":"2026-05-29T02:06:08Z","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/2605.30051/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A key part of developing large language model (LLM)-powered, automated tutoring tools is student simulation, i.e., using LLMs to role-play as students, which can facilitate tutor model evaluation and training. Existing work mostly focuses on within-dialogue simulation, which lacks context on student knowledge and behavior, partly due to not grounding in past student question-answering or dialogue interactions. In this work, we introduce the task of history-conditioned student simulation, where the goal is to accurately predict student dialogue turns by leveraging information in the student's l","authors_text":"Alexander Scarlatos, Andrew Lan, Jaewook Lee, Shuyan Huang, Simon Woodhead, Zhangqi Duan","cross_cats":["cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-28T15:02:51Z","title":"Who Am I? History-Aware Profiles for Student Simulation in Tutoring Dialogues"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30051","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":"sha256:3ff4c17881b0501f61e751ba8fc22fde37e2ca8ed4ccea71d095aa447d31f9dd","target":"record","created_at":"2026-05-29T02:06:08Z","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":"758c0fcdd31734d5b52725659aae094b47737a356e5999717502fb2c43ce8243","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-05-28T15:02:51Z","title_canon_sha256":"852944c7b93655d5f5bcb03bf0ccb394a50e6955c708bcb0c9bf3ed2037b18d9"},"schema_version":"1.0","source":{"id":"2605.30051","kind":"arxiv","version":1}},"canonical_sha256":"7c04ff98164b6bb112d652a95282b1b42fc51c8ebe5f043cc68e28db072de5da","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7c04ff98164b6bb112d652a95282b1b42fc51c8ebe5f043cc68e28db072de5da","first_computed_at":"2026-05-29T02:06:08.587035Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T02:06:08.587035Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AoeE6JPvFaD0hxkaCYig+9AsfBBClEXnmwAuVWNOuHpU/AdtdD5Xiiyny6Mhaw+bcZZ+twfmC4eT/u4frj7NAw==","signature_status":"signed_v1","signed_at":"2026-05-29T02:06:08.587456Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.30051","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3ff4c17881b0501f61e751ba8fc22fde37e2ca8ed4ccea71d095aa447d31f9dd","sha256:485b03af3b53139d8eb0e6c688f42f6c5fa158bf04fd76ba20a7593d195430ce"],"state_sha256":"013d43f716cb47230107ebc5ec88b77a13731a5887248c3c26a9ba5911be1944"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y/mlJUbXxUmrj7dvl/+0xqZLJxqfeXPmrxh3lcQnWXU79E4iBoOuM4XsgEKnhPbdTOo1MRhgmDYK7ZTHCo7HAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T14:28:36.713333Z","bundle_sha256":"ba69d2833b57f0c425043b1a2d93212df22d273ca490f7ff4a50c1ce09bb7783"}}