{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:COZEYJL4JX6N2TZGSCMEULF2DB","short_pith_number":"pith:COZEYJL4","canonical_record":{"source":{"id":"2504.15604","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-22T05:52:55Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a3c62db4d990bf064e65d1c11ad0e51cea4ca1cb23fe16300c95e737ee2c499b","abstract_canon_sha256":"6b5a4bad4814aa118e4565eaa1e27890a3c2dc7e650be315bf5dc2ae5f9de5c1"},"schema_version":"1.0"},"canonical_sha256":"13b24c257c4dfcdd4f2690984a2cba18454186c4e2aeadf09b6d4b320b0f6390","source":{"kind":"arxiv","id":"2504.15604","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.15604","created_at":"2026-07-05T10:52:27Z"},{"alias_kind":"arxiv_version","alias_value":"2504.15604v1","created_at":"2026-07-05T10:52:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.15604","created_at":"2026-07-05T10:52:27Z"},{"alias_kind":"pith_short_12","alias_value":"COZEYJL4JX6N","created_at":"2026-07-05T10:52:27Z"},{"alias_kind":"pith_short_16","alias_value":"COZEYJL4JX6N2TZG","created_at":"2026-07-05T10:52:27Z"},{"alias_kind":"pith_short_8","alias_value":"COZEYJL4","created_at":"2026-07-05T10:52:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:COZEYJL4JX6N2TZGSCMEULF2DB","target":"record","payload":{"canonical_record":{"source":{"id":"2504.15604","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-22T05:52:55Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a3c62db4d990bf064e65d1c11ad0e51cea4ca1cb23fe16300c95e737ee2c499b","abstract_canon_sha256":"6b5a4bad4814aa118e4565eaa1e27890a3c2dc7e650be315bf5dc2ae5f9de5c1"},"schema_version":"1.0"},"canonical_sha256":"13b24c257c4dfcdd4f2690984a2cba18454186c4e2aeadf09b6d4b320b0f6390","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:52:27.264248Z","signature_b64":"uWFslgLawA6qpa4LeFCE62RbrQUwhtE3KpVUnI6Ih/UbovOScvcq4hEqXT001zJNqQuxk6ayoi8qw1nD7OwwCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"13b24c257c4dfcdd4f2690984a2cba18454186c4e2aeadf09b6d4b320b0f6390","last_reissued_at":"2026-07-05T10:52:27.263735Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:52:27.263735Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.15604","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":"2026-07-05T10:52:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"75hL3OFIXT8LaQEmmi4cjXxsuK7Ll1O324HBr1Be4aH+ebH/VCcj6tR+xG1zQpuqwFIMQ/DH8jmZzXfJW4mAAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T10:12:39.840856Z"},"content_sha256":"a4f5b1a5ce718492b4cfd7921e6c62e57674f1f666621490c412d9bb6cd09763","schema_version":"1.0","event_id":"sha256:a4f5b1a5ce718492b4cfd7921e6c62e57674f1f666621490c412d9bb6cd09763"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:COZEYJL4JX6N2TZGSCMEULF2DB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploring Next Token Prediction in Theory of Mind (ToM) Tasks: Comparative Experiments with GPT-2 and LLaMA-2 AI Models","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Krishna Shinde, Lokesh B. Ramegowda, Nikhil Khandalkar, Pavan Yadav, Rajarshi Das","submitted_at":"2025-04-22T05:52:55Z","abstract_excerpt":"Language models have made significant progress in generating coherent text and predicting next tokens based on input prompts. This study compares the next-token prediction performance of two well-known models: OpenAI's GPT-2 and Meta's Llama-2-7b-chat-hf on Theory of Mind (ToM) tasks. To evaluate their capabilities, we built a dataset from 10 short stories sourced from the Explore ToM Dataset. We enhanced these stories by programmatically inserting additional sentences (infills) using GPT-4, creating variations that introduce different levels of contextual complexity. This setup enables analys"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.15604","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/2504.15604/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":"2026-07-05T10:52:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1EEzAeaX5uzKAMjyusV+erfxI5gwxg4xexQcBeSHlLW3BnT72EWVD0/LrqbNedxsOr4+UADdsUTcU9GHz4SwAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T10:12:39.841424Z"},"content_sha256":"0651958d9416fc8660fe5f43c0e176189b50f02c3c66ed0db9fe98ebb54280f2","schema_version":"1.0","event_id":"sha256:0651958d9416fc8660fe5f43c0e176189b50f02c3c66ed0db9fe98ebb54280f2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/COZEYJL4JX6N2TZGSCMEULF2DB/bundle.json","state_url":"https://pith.science/pith/COZEYJL4JX6N2TZGSCMEULF2DB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/COZEYJL4JX6N2TZGSCMEULF2DB/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":"2026-08-23T10:12:39Z","links":{"resolver":"https://pith.science/pith/COZEYJL4JX6N2TZGSCMEULF2DB","bundle":"https://pith.science/pith/COZEYJL4JX6N2TZGSCMEULF2DB/bundle.json","state":"https://pith.science/pith/COZEYJL4JX6N2TZGSCMEULF2DB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/COZEYJL4JX6N2TZGSCMEULF2DB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:COZEYJL4JX6N2TZGSCMEULF2DB","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":"6b5a4bad4814aa118e4565eaa1e27890a3c2dc7e650be315bf5dc2ae5f9de5c1","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-22T05:52:55Z","title_canon_sha256":"a3c62db4d990bf064e65d1c11ad0e51cea4ca1cb23fe16300c95e737ee2c499b"},"schema_version":"1.0","source":{"id":"2504.15604","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.15604","created_at":"2026-07-05T10:52:27Z"},{"alias_kind":"arxiv_version","alias_value":"2504.15604v1","created_at":"2026-07-05T10:52:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.15604","created_at":"2026-07-05T10:52:27Z"},{"alias_kind":"pith_short_12","alias_value":"COZEYJL4JX6N","created_at":"2026-07-05T10:52:27Z"},{"alias_kind":"pith_short_16","alias_value":"COZEYJL4JX6N2TZG","created_at":"2026-07-05T10:52:27Z"},{"alias_kind":"pith_short_8","alias_value":"COZEYJL4","created_at":"2026-07-05T10:52:27Z"}],"graph_snapshots":[{"event_id":"sha256:0651958d9416fc8660fe5f43c0e176189b50f02c3c66ed0db9fe98ebb54280f2","target":"graph","created_at":"2026-07-05T10:52:27Z","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/2504.15604/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Language models have made significant progress in generating coherent text and predicting next tokens based on input prompts. This study compares the next-token prediction performance of two well-known models: OpenAI's GPT-2 and Meta's Llama-2-7b-chat-hf on Theory of Mind (ToM) tasks. To evaluate their capabilities, we built a dataset from 10 short stories sourced from the Explore ToM Dataset. We enhanced these stories by programmatically inserting additional sentences (infills) using GPT-4, creating variations that introduce different levels of contextual complexity. This setup enables analys","authors_text":"Krishna Shinde, Lokesh B. Ramegowda, Nikhil Khandalkar, Pavan Yadav, Rajarshi Das","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-22T05:52:55Z","title":"Exploring Next Token Prediction in Theory of Mind (ToM) Tasks: Comparative Experiments with GPT-2 and LLaMA-2 AI Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.15604","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:a4f5b1a5ce718492b4cfd7921e6c62e57674f1f666621490c412d9bb6cd09763","target":"record","created_at":"2026-07-05T10:52:27Z","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":"6b5a4bad4814aa118e4565eaa1e27890a3c2dc7e650be315bf5dc2ae5f9de5c1","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-04-22T05:52:55Z","title_canon_sha256":"a3c62db4d990bf064e65d1c11ad0e51cea4ca1cb23fe16300c95e737ee2c499b"},"schema_version":"1.0","source":{"id":"2504.15604","kind":"arxiv","version":1}},"canonical_sha256":"13b24c257c4dfcdd4f2690984a2cba18454186c4e2aeadf09b6d4b320b0f6390","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"13b24c257c4dfcdd4f2690984a2cba18454186c4e2aeadf09b6d4b320b0f6390","first_computed_at":"2026-07-05T10:52:27.263735Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:52:27.263735Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uWFslgLawA6qpa4LeFCE62RbrQUwhtE3KpVUnI6Ih/UbovOScvcq4hEqXT001zJNqQuxk6ayoi8qw1nD7OwwCA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:52:27.264248Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.15604","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a4f5b1a5ce718492b4cfd7921e6c62e57674f1f666621490c412d9bb6cd09763","sha256:0651958d9416fc8660fe5f43c0e176189b50f02c3c66ed0db9fe98ebb54280f2"],"state_sha256":"3e69b79a64ebabab33f7dce103133ac5547e4595cde0b636f4c8c32dcb5bbcc4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mo1+YWIBae88cQk4vRlV6MGDVH/lhw0sc5JDrZXc6DbEsKhRf8+7w57jCo5bs8OdFSaMjxVpVCn02c4aNRRdAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T10:12:39.845788Z","bundle_sha256":"1263921c0098f6090a23b3980dcd96aaeb6e13a4097276631deaefe7b376b6f0"}}