{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:FWPY3FKEEVLPJ52VBBU2BVJSWT","short_pith_number":"pith:FWPY3FKE","canonical_record":{"source":{"id":"2304.07995","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-04-17T05:29:42Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d88c7bd9e758b649f5691897ac8ed555e59f365dc542334aadf53fa939802019","abstract_canon_sha256":"707b1005d7939361c848f5acb3cff0729ea8cd19fec0b9538804f393f4d26a91"},"schema_version":"1.0"},"canonical_sha256":"2d9f8d95442556f4f7550869a0d532b4e33d9f3163aa8b850ca5eb838d1a075d","source":{"kind":"arxiv","id":"2304.07995","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.07995","created_at":"2026-07-05T06:01:27Z"},{"alias_kind":"arxiv_version","alias_value":"2304.07995v1","created_at":"2026-07-05T06:01:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.07995","created_at":"2026-07-05T06:01:27Z"},{"alias_kind":"pith_short_12","alias_value":"FWPY3FKEEVLP","created_at":"2026-07-05T06:01:27Z"},{"alias_kind":"pith_short_16","alias_value":"FWPY3FKEEVLPJ52V","created_at":"2026-07-05T06:01:27Z"},{"alias_kind":"pith_short_8","alias_value":"FWPY3FKE","created_at":"2026-07-05T06:01:27Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:FWPY3FKEEVLPJ52VBBU2BVJSWT","target":"record","payload":{"canonical_record":{"source":{"id":"2304.07995","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-04-17T05:29:42Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"d88c7bd9e758b649f5691897ac8ed555e59f365dc542334aadf53fa939802019","abstract_canon_sha256":"707b1005d7939361c848f5acb3cff0729ea8cd19fec0b9538804f393f4d26a91"},"schema_version":"1.0"},"canonical_sha256":"2d9f8d95442556f4f7550869a0d532b4e33d9f3163aa8b850ca5eb838d1a075d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:01:27.590990Z","signature_b64":"pcUi1PkFYF9+cLCazkDGBqeHS2IAjYo0kg0ea4RDLVuochQWDPd+qj5l5scRAqS7IEAbxNvBM+PC478ct6r3CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2d9f8d95442556f4f7550869a0d532b4e33d9f3163aa8b850ca5eb838d1a075d","last_reissued_at":"2026-07-05T06:01:27.590547Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:01:27.590547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.07995","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":"2026-07-05T06:01:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"txdXAr58pvHaa5YVlSrDVugaE+tiXmhKFCtt5nEDru8+I4HeCYFaseXuEuvbBFYs91ZVkY2eAA4g6BsXi0EfAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:08:20.706724Z"},"content_sha256":"edfce14b8cec0b90512dca043e468bb20f5692ada7368e51973261680330ce64","schema_version":"1.0","event_id":"sha256:edfce14b8cec0b90512dca043e468bb20f5692ada7368e51973261680330ce64"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:FWPY3FKEEVLPJ52VBBU2BVJSWT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Fan Zhou, Longxu Dou, Min Lin, Qian Liu, Zhengbao Jiang","submitted_at":"2023-04-17T05:29:42Z","abstract_excerpt":"Fine-tuning language models on tasks with instructions has demonstrated potential in facilitating zero-shot generalization to unseen tasks. In this paper, we introduce a straightforward yet effective method for enhancing instruction tuning by employing symbolic tasks. Compared to crowdsourced human tasks or model-generated tasks, symbolic tasks present a unique advantage as they can be easily generated in vast quantities, theoretically providing an infinite supply of high-quality training instances. To explore the potential of symbolic tasks, we carry out an extensive case study on the represe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.07995","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/2304.07995/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":"2026-07-05T06:01:27Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q+TKaYZyTbu56AYlmj17uFtD4OJrlvkPA0ktx3VAGHRylEdIj+KkO2dFwU2u+YWCboeF8pdQ4/psMzO3F08aDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T18:08:20.707098Z"},"content_sha256":"96c696deb0d348a668716b0372b89023b88493d3a2179e6dd62a1deddcb77ad2","schema_version":"1.0","event_id":"sha256:96c696deb0d348a668716b0372b89023b88493d3a2179e6dd62a1deddcb77ad2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FWPY3FKEEVLPJ52VBBU2BVJSWT/bundle.json","state_url":"https://pith.science/pith/FWPY3FKEEVLPJ52VBBU2BVJSWT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FWPY3FKEEVLPJ52VBBU2BVJSWT/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":"2026-07-06T18:08:20Z","links":{"resolver":"https://pith.science/pith/FWPY3FKEEVLPJ52VBBU2BVJSWT","bundle":"https://pith.science/pith/FWPY3FKEEVLPJ52VBBU2BVJSWT/bundle.json","state":"https://pith.science/pith/FWPY3FKEEVLPJ52VBBU2BVJSWT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FWPY3FKEEVLPJ52VBBU2BVJSWT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:FWPY3FKEEVLPJ52VBBU2BVJSWT","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":"707b1005d7939361c848f5acb3cff0729ea8cd19fec0b9538804f393f4d26a91","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-04-17T05:29:42Z","title_canon_sha256":"d88c7bd9e758b649f5691897ac8ed555e59f365dc542334aadf53fa939802019"},"schema_version":"1.0","source":{"id":"2304.07995","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.07995","created_at":"2026-07-05T06:01:27Z"},{"alias_kind":"arxiv_version","alias_value":"2304.07995v1","created_at":"2026-07-05T06:01:27Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.07995","created_at":"2026-07-05T06:01:27Z"},{"alias_kind":"pith_short_12","alias_value":"FWPY3FKEEVLP","created_at":"2026-07-05T06:01:27Z"},{"alias_kind":"pith_short_16","alias_value":"FWPY3FKEEVLPJ52V","created_at":"2026-07-05T06:01:27Z"},{"alias_kind":"pith_short_8","alias_value":"FWPY3FKE","created_at":"2026-07-05T06:01:27Z"}],"graph_snapshots":[{"event_id":"sha256:96c696deb0d348a668716b0372b89023b88493d3a2179e6dd62a1deddcb77ad2","target":"graph","created_at":"2026-07-05T06:01:27Z","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/2304.07995/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fine-tuning language models on tasks with instructions has demonstrated potential in facilitating zero-shot generalization to unseen tasks. In this paper, we introduce a straightforward yet effective method for enhancing instruction tuning by employing symbolic tasks. Compared to crowdsourced human tasks or model-generated tasks, symbolic tasks present a unique advantage as they can be easily generated in vast quantities, theoretically providing an infinite supply of high-quality training instances. To explore the potential of symbolic tasks, we carry out an extensive case study on the represe","authors_text":"Fan Zhou, Longxu Dou, Min Lin, Qian Liu, Zhengbao Jiang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-04-17T05:29:42Z","title":"From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.07995","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:edfce14b8cec0b90512dca043e468bb20f5692ada7368e51973261680330ce64","target":"record","created_at":"2026-07-05T06:01:27Z","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":"707b1005d7939361c848f5acb3cff0729ea8cd19fec0b9538804f393f4d26a91","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-04-17T05:29:42Z","title_canon_sha256":"d88c7bd9e758b649f5691897ac8ed555e59f365dc542334aadf53fa939802019"},"schema_version":"1.0","source":{"id":"2304.07995","kind":"arxiv","version":1}},"canonical_sha256":"2d9f8d95442556f4f7550869a0d532b4e33d9f3163aa8b850ca5eb838d1a075d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2d9f8d95442556f4f7550869a0d532b4e33d9f3163aa8b850ca5eb838d1a075d","first_computed_at":"2026-07-05T06:01:27.590547Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:01:27.590547Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pcUi1PkFYF9+cLCazkDGBqeHS2IAjYo0kg0ea4RDLVuochQWDPd+qj5l5scRAqS7IEAbxNvBM+PC478ct6r3CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T06:01:27.590990Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.07995","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:edfce14b8cec0b90512dca043e468bb20f5692ada7368e51973261680330ce64","sha256:96c696deb0d348a668716b0372b89023b88493d3a2179e6dd62a1deddcb77ad2"],"state_sha256":"15ffefd87509b9c69fc683e1bbb363cac67dabc4e41a0e5cab4e4a8012bf3dce"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"20X9ZrtYhNlX4Xa5OOpEQcXLRbjOA4qNt2bFONT2xI+nlMDSxMmUACxFfvwhsyB4RfPQIZnr+/yK1fapAzoUCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T18:08:20.709081Z","bundle_sha256":"0f75535667f3f43ff3cff7fa95e122a91d8558104bb695a4d079c52f46198edc"}}