{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OIBPN3WS6FT5FEQEKMY7KDQZZM","short_pith_number":"pith:OIBPN3WS","canonical_record":{"source":{"id":"2402.10979","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-15T20:26:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e331c7a5f69539fee5846c5f9f4807e0b4b98a66c246659e2d36eaad0c7037c8","abstract_canon_sha256":"49863659409f790f2aa57809d87525fba001bd6fe3a509f68f5605995478dea8"},"schema_version":"1.0"},"canonical_sha256":"7202f6eed2f167d292045331f50e19cb119837adf934e33234e79494038f6919","source":{"kind":"arxiv","id":"2402.10979","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.10979","created_at":"2026-07-05T08:32:36Z"},{"alias_kind":"arxiv_version","alias_value":"2402.10979v2","created_at":"2026-07-05T08:32:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.10979","created_at":"2026-07-05T08:32:36Z"},{"alias_kind":"pith_short_12","alias_value":"OIBPN3WS6FT5","created_at":"2026-07-05T08:32:36Z"},{"alias_kind":"pith_short_16","alias_value":"OIBPN3WS6FT5FEQE","created_at":"2026-07-05T08:32:36Z"},{"alias_kind":"pith_short_8","alias_value":"OIBPN3WS","created_at":"2026-07-05T08:32:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OIBPN3WS6FT5FEQEKMY7KDQZZM","target":"record","payload":{"canonical_record":{"source":{"id":"2402.10979","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-15T20:26:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e331c7a5f69539fee5846c5f9f4807e0b4b98a66c246659e2d36eaad0c7037c8","abstract_canon_sha256":"49863659409f790f2aa57809d87525fba001bd6fe3a509f68f5605995478dea8"},"schema_version":"1.0"},"canonical_sha256":"7202f6eed2f167d292045331f50e19cb119837adf934e33234e79494038f6919","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:32:36.936119Z","signature_b64":"9rOES9r41KDSTJwvfJ2B2ho6xtanIrxwHbBzJWFLDHA+qhyzdwL8DNtcwVdWBC0fIv2EWq9RGuaUzziSejKnDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7202f6eed2f167d292045331f50e19cb119837adf934e33234e79494038f6919","last_reissued_at":"2026-07-05T08:32:36.935630Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:32:36.935630Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.10979","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":"2026-07-05T08:32:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cfzd7jYh39zo2+ulkV6E3XHG6YK0phK5bvA9UyPBR3Tt4PKlhZaPDgkolEZSCm+w5ndYuLZ389USJ3HLVFI3DQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:50:44.381351Z"},"content_sha256":"e207ace1d5fc9309b334f913d07096fa5136caf55e346aae55d6e3a00d1e4bb4","schema_version":"1.0","event_id":"sha256:e207ace1d5fc9309b334f913d07096fa5136caf55e346aae55d6e3a00d1e4bb4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OIBPN3WS6FT5FEQEKMY7KDQZZM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SportsMetrics: Blending Text and Numerical Data to Understand Information Fusion in LLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Dong Yu, Fei Liu, Hassan Foroosh, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Yebowen Hu","submitted_at":"2024-02-15T20:26:07Z","abstract_excerpt":"Large language models hold significant potential for integrating various data types, such as text documents and database records, for advanced analytics. However, blending text and numerical data presents substantial challenges. LLMs need to process and cross-reference entities and numbers, handle data inconsistencies and redundancies, and develop planning capabilities such as building a working memory for managing complex data queries. In this paper, we introduce four novel tasks centered around sports data analytics to evaluate the numerical reasoning and information fusion capabilities of L"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.10979","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/2402.10979/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":"2026-07-05T08:32:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9cDO1AjVP/zuCZTvMkPD1SSAb2oeHWLAg0Wc/EaBC2Z7hsrMIp3x8V1MFX/UJEncyPuYEAkuiT4Am0qpg24ZBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:50:44.381918Z"},"content_sha256":"56702eedf28e264e1fd0a7a641c8b1072b7d3e8eef14c14875caf3dec819ac9d","schema_version":"1.0","event_id":"sha256:56702eedf28e264e1fd0a7a641c8b1072b7d3e8eef14c14875caf3dec819ac9d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OIBPN3WS6FT5FEQEKMY7KDQZZM/bundle.json","state_url":"https://pith.science/pith/OIBPN3WS6FT5FEQEKMY7KDQZZM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OIBPN3WS6FT5FEQEKMY7KDQZZM/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":"2026-08-09T05:50:44Z","links":{"resolver":"https://pith.science/pith/OIBPN3WS6FT5FEQEKMY7KDQZZM","bundle":"https://pith.science/pith/OIBPN3WS6FT5FEQEKMY7KDQZZM/bundle.json","state":"https://pith.science/pith/OIBPN3WS6FT5FEQEKMY7KDQZZM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OIBPN3WS6FT5FEQEKMY7KDQZZM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OIBPN3WS6FT5FEQEKMY7KDQZZM","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":"49863659409f790f2aa57809d87525fba001bd6fe3a509f68f5605995478dea8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-15T20:26:07Z","title_canon_sha256":"e331c7a5f69539fee5846c5f9f4807e0b4b98a66c246659e2d36eaad0c7037c8"},"schema_version":"1.0","source":{"id":"2402.10979","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.10979","created_at":"2026-07-05T08:32:36Z"},{"alias_kind":"arxiv_version","alias_value":"2402.10979v2","created_at":"2026-07-05T08:32:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.10979","created_at":"2026-07-05T08:32:36Z"},{"alias_kind":"pith_short_12","alias_value":"OIBPN3WS6FT5","created_at":"2026-07-05T08:32:36Z"},{"alias_kind":"pith_short_16","alias_value":"OIBPN3WS6FT5FEQE","created_at":"2026-07-05T08:32:36Z"},{"alias_kind":"pith_short_8","alias_value":"OIBPN3WS","created_at":"2026-07-05T08:32:36Z"}],"graph_snapshots":[{"event_id":"sha256:56702eedf28e264e1fd0a7a641c8b1072b7d3e8eef14c14875caf3dec819ac9d","target":"graph","created_at":"2026-07-05T08:32:36Z","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/2402.10979/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models hold significant potential for integrating various data types, such as text documents and database records, for advanced analytics. However, blending text and numerical data presents substantial challenges. LLMs need to process and cross-reference entities and numbers, handle data inconsistencies and redundancies, and develop planning capabilities such as building a working memory for managing complex data queries. In this paper, we introduce four novel tasks centered around sports data analytics to evaluate the numerical reasoning and information fusion capabilities of L","authors_text":"Dong Yu, Fei Liu, Hassan Foroosh, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Yebowen Hu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-15T20:26:07Z","title":"SportsMetrics: Blending Text and Numerical Data to Understand Information Fusion in LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.10979","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:e207ace1d5fc9309b334f913d07096fa5136caf55e346aae55d6e3a00d1e4bb4","target":"record","created_at":"2026-07-05T08:32:36Z","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":"49863659409f790f2aa57809d87525fba001bd6fe3a509f68f5605995478dea8","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-15T20:26:07Z","title_canon_sha256":"e331c7a5f69539fee5846c5f9f4807e0b4b98a66c246659e2d36eaad0c7037c8"},"schema_version":"1.0","source":{"id":"2402.10979","kind":"arxiv","version":2}},"canonical_sha256":"7202f6eed2f167d292045331f50e19cb119837adf934e33234e79494038f6919","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7202f6eed2f167d292045331f50e19cb119837adf934e33234e79494038f6919","first_computed_at":"2026-07-05T08:32:36.935630Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:32:36.935630Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9rOES9r41KDSTJwvfJ2B2ho6xtanIrxwHbBzJWFLDHA+qhyzdwL8DNtcwVdWBC0fIv2EWq9RGuaUzziSejKnDw==","signature_status":"signed_v1","signed_at":"2026-07-05T08:32:36.936119Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.10979","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e207ace1d5fc9309b334f913d07096fa5136caf55e346aae55d6e3a00d1e4bb4","sha256:56702eedf28e264e1fd0a7a641c8b1072b7d3e8eef14c14875caf3dec819ac9d"],"state_sha256":"55a2c6988883da4fc70d24ab51f6038edf7637a2e59bd181aee0cfd07276a876"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oZ1as09cSR+XBE/CYdJP3D8abyTPgvlvIdbd66p2Dr5kMI1Hzud8S6wEAW/EzPxJG2LGOK13oUF7/q49P2ZFCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T05:50:44.386082Z","bundle_sha256":"0f648ab2b144fbbb00ac7a25c706f391bb7f75e61f03ab8fa3225cd09f36ebf8"}}