{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VECYECVKMM3N4QYKROAIG33XNX","short_pith_number":"pith:VECYECVK","canonical_record":{"source":{"id":"2506.01710","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-02T14:18:09Z","cross_cats_sorted":[],"title_canon_sha256":"fcc064c4251008b3a716af1c5343d0db3829400a1e288c9306461d80f8e6002b","abstract_canon_sha256":"0ff795a6ec3a9d71a3ba52e107f8570f9e25871da77e42525351a8cf2a0fa1d2"},"schema_version":"1.0"},"canonical_sha256":"a905820aaa6336de430a8b80836f776de65428c5b7871f94c55cb9dc7b13b0ce","source":{"kind":"arxiv","id":"2506.01710","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.01710","created_at":"2026-07-05T11:14:18Z"},{"alias_kind":"arxiv_version","alias_value":"2506.01710v1","created_at":"2026-07-05T11:14:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01710","created_at":"2026-07-05T11:14:18Z"},{"alias_kind":"pith_short_12","alias_value":"VECYECVKMM3N","created_at":"2026-07-05T11:14:18Z"},{"alias_kind":"pith_short_16","alias_value":"VECYECVKMM3N4QYK","created_at":"2026-07-05T11:14:18Z"},{"alias_kind":"pith_short_8","alias_value":"VECYECVK","created_at":"2026-07-05T11:14:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VECYECVKMM3N4QYKROAIG33XNX","target":"record","payload":{"canonical_record":{"source":{"id":"2506.01710","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-02T14:18:09Z","cross_cats_sorted":[],"title_canon_sha256":"fcc064c4251008b3a716af1c5343d0db3829400a1e288c9306461d80f8e6002b","abstract_canon_sha256":"0ff795a6ec3a9d71a3ba52e107f8570f9e25871da77e42525351a8cf2a0fa1d2"},"schema_version":"1.0"},"canonical_sha256":"a905820aaa6336de430a8b80836f776de65428c5b7871f94c55cb9dc7b13b0ce","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:14:18.190933Z","signature_b64":"GwFYn3rlyC5l+YAZ7z6CMEHkDQ3uinipD2NFA/O1hXvdC+WJOVwTRpDQWlar6Xd5zYY9Y+y1okXY/nkIW94jAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a905820aaa6336de430a8b80836f776de65428c5b7871f94c55cb9dc7b13b0ce","last_reissued_at":"2026-07-05T11:14:18.190468Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:14:18.190468Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.01710","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":"2026-07-05T11:14:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dj6WGfxVygaJBCi/VWEM6mLgUec4vojRUVHfjZ9yqim4n7cCShg9aiVv5IpZSk5GOyVHltn6N/bG1mo9WHLQDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T14:00:11.785326Z"},"content_sha256":"be51ec8673d0a16b8b2863f36ef9ebd30402462535ff3419949d65fee7ea1bab","schema_version":"1.0","event_id":"sha256:be51ec8673d0a16b8b2863f36ef9ebd30402462535ff3419949d65fee7ea1bab"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VECYECVKMM3N4QYKROAIG33XNX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Reasoning-Table: Exploring Reinforcement Learning for Table Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Fangyu Lei, Jinxiang Meng, Jun Zhao, Kang Liu, Shizhu He, Tinghong Chen, Yiming Huang, Yun Zhang","submitted_at":"2025-06-02T14:18:09Z","abstract_excerpt":"Table reasoning, encompassing tasks such as table question answering, fact verification, and text-to-SQL, requires precise understanding of structured tabular data, coupled with numerical computation and code manipulation for effective inference. Supervised fine-tuning (SFT) approaches have achieved notable success but often struggle with generalization and robustness due to biases inherent in imitative learning. We introduce Reasoning-Table, the first application of reinforcement learning (RL) to table reasoning, achieving state-of-the-art performance. Through rigorous data preprocessing, rew"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01710","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/2506.01710/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":"2026-07-05T11:14:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IXanEmlSTjA+MVc9Rp8MBsrTxXZHtI/XaoIT6sucevRA4k/jI4IWEWk7bu5lCs4EKEOPU5tz1Z/ADyM8EcXJDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T14:00:11.785817Z"},"content_sha256":"bfb9d249b7f9a28f27668ce824a043564fbcd2c121c5a63843255ca3f6cf5458","schema_version":"1.0","event_id":"sha256:bfb9d249b7f9a28f27668ce824a043564fbcd2c121c5a63843255ca3f6cf5458"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VECYECVKMM3N4QYKROAIG33XNX/bundle.json","state_url":"https://pith.science/pith/VECYECVKMM3N4QYKROAIG33XNX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VECYECVKMM3N4QYKROAIG33XNX/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":"2026-08-08T14:00:11Z","links":{"resolver":"https://pith.science/pith/VECYECVKMM3N4QYKROAIG33XNX","bundle":"https://pith.science/pith/VECYECVKMM3N4QYKROAIG33XNX/bundle.json","state":"https://pith.science/pith/VECYECVKMM3N4QYKROAIG33XNX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VECYECVKMM3N4QYKROAIG33XNX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VECYECVKMM3N4QYKROAIG33XNX","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":"0ff795a6ec3a9d71a3ba52e107f8570f9e25871da77e42525351a8cf2a0fa1d2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-02T14:18:09Z","title_canon_sha256":"fcc064c4251008b3a716af1c5343d0db3829400a1e288c9306461d80f8e6002b"},"schema_version":"1.0","source":{"id":"2506.01710","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.01710","created_at":"2026-07-05T11:14:18Z"},{"alias_kind":"arxiv_version","alias_value":"2506.01710v1","created_at":"2026-07-05T11:14:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.01710","created_at":"2026-07-05T11:14:18Z"},{"alias_kind":"pith_short_12","alias_value":"VECYECVKMM3N","created_at":"2026-07-05T11:14:18Z"},{"alias_kind":"pith_short_16","alias_value":"VECYECVKMM3N4QYK","created_at":"2026-07-05T11:14:18Z"},{"alias_kind":"pith_short_8","alias_value":"VECYECVK","created_at":"2026-07-05T11:14:18Z"}],"graph_snapshots":[{"event_id":"sha256:bfb9d249b7f9a28f27668ce824a043564fbcd2c121c5a63843255ca3f6cf5458","target":"graph","created_at":"2026-07-05T11:14:18Z","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/2506.01710/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Table reasoning, encompassing tasks such as table question answering, fact verification, and text-to-SQL, requires precise understanding of structured tabular data, coupled with numerical computation and code manipulation for effective inference. Supervised fine-tuning (SFT) approaches have achieved notable success but often struggle with generalization and robustness due to biases inherent in imitative learning. We introduce Reasoning-Table, the first application of reinforcement learning (RL) to table reasoning, achieving state-of-the-art performance. Through rigorous data preprocessing, rew","authors_text":"Fangyu Lei, Jinxiang Meng, Jun Zhao, Kang Liu, Shizhu He, Tinghong Chen, Yiming Huang, Yun Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-02T14:18:09Z","title":"Reasoning-Table: Exploring Reinforcement Learning for Table Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.01710","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:be51ec8673d0a16b8b2863f36ef9ebd30402462535ff3419949d65fee7ea1bab","target":"record","created_at":"2026-07-05T11:14:18Z","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":"0ff795a6ec3a9d71a3ba52e107f8570f9e25871da77e42525351a8cf2a0fa1d2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-02T14:18:09Z","title_canon_sha256":"fcc064c4251008b3a716af1c5343d0db3829400a1e288c9306461d80f8e6002b"},"schema_version":"1.0","source":{"id":"2506.01710","kind":"arxiv","version":1}},"canonical_sha256":"a905820aaa6336de430a8b80836f776de65428c5b7871f94c55cb9dc7b13b0ce","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a905820aaa6336de430a8b80836f776de65428c5b7871f94c55cb9dc7b13b0ce","first_computed_at":"2026-07-05T11:14:18.190468Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:14:18.190468Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GwFYn3rlyC5l+YAZ7z6CMEHkDQ3uinipD2NFA/O1hXvdC+WJOVwTRpDQWlar6Xd5zYY9Y+y1okXY/nkIW94jAg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:14:18.190933Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.01710","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:be51ec8673d0a16b8b2863f36ef9ebd30402462535ff3419949d65fee7ea1bab","sha256:bfb9d249b7f9a28f27668ce824a043564fbcd2c121c5a63843255ca3f6cf5458"],"state_sha256":"971929fde49d7e313bce7a334309472bd5d8469841464a14c2084d669c4430c8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dbo4yCEgaKrElmZp0pzgUz8rr/wVA4blmHIGOfIhTZWB7DTfeo38wsMaOnNiA7MMlfhFf0lXg2f57g4KOII+AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T14:00:11.789124Z","bundle_sha256":"71bccada4f0df29f5e9830b00df69c3f521915df3a1e850001b9ae302a8c9192"}}