{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:EQVTBAFHOU2XPHVQ5WCEUOELF3","short_pith_number":"pith:EQVTBAFH","canonical_record":{"source":{"id":"2601.06431","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-01-10T05:11:38Z","cross_cats_sorted":[],"title_canon_sha256":"7ab0048d18f23c4459de1b11aad3a02a7f49011b78304b1f962b98877be16f74","abstract_canon_sha256":"52416339693cd3e9dfa01a026d348ef36e9989009ebaf5c0b0c5209713594eb1"},"schema_version":"1.0"},"canonical_sha256":"242b3080a77535779eb0ed844a388b2ef19443b08aba16c026245167a8ae8327","source":{"kind":"arxiv","id":"2601.06431","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.06431","created_at":"2026-05-29T01:05:01Z"},{"alias_kind":"arxiv_version","alias_value":"2601.06431v3","created_at":"2026-05-29T01:05:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.06431","created_at":"2026-05-29T01:05:01Z"},{"alias_kind":"pith_short_12","alias_value":"EQVTBAFHOU2X","created_at":"2026-05-29T01:05:01Z"},{"alias_kind":"pith_short_16","alias_value":"EQVTBAFHOU2XPHVQ","created_at":"2026-05-29T01:05:01Z"},{"alias_kind":"pith_short_8","alias_value":"EQVTBAFH","created_at":"2026-05-29T01:05:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:EQVTBAFHOU2XPHVQ5WCEUOELF3","target":"record","payload":{"canonical_record":{"source":{"id":"2601.06431","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-01-10T05:11:38Z","cross_cats_sorted":[],"title_canon_sha256":"7ab0048d18f23c4459de1b11aad3a02a7f49011b78304b1f962b98877be16f74","abstract_canon_sha256":"52416339693cd3e9dfa01a026d348ef36e9989009ebaf5c0b0c5209713594eb1"},"schema_version":"1.0"},"canonical_sha256":"242b3080a77535779eb0ed844a388b2ef19443b08aba16c026245167a8ae8327","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T01:05:01.696171Z","signature_b64":"O6K7wWOiyb0DbZWtQej9OsngpkbSXoYOtOzLY9VobC0mtG2QDDxN1jOyuOyPVC1qsP8fjL2+tixlwR7fddbJBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"242b3080a77535779eb0ed844a388b2ef19443b08aba16c026245167a8ae8327","last_reissued_at":"2026-05-29T01:05:01.695263Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T01:05:01.695263Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2601.06431","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-29T01:05:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"W001cqLhb29Lnbp+Ds+JyywAjQGQOaDe8mlWBqEyHqmS4hqlRfpFfqgMpNxj9lmOdCxbl9LIHnWpY4xssb16DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T23:31:14.120403Z"},"content_sha256":"d4785f74a73e822e790904a17dcd2ead067393b3691f74ab01191ab0b5901f87","schema_version":"1.0","event_id":"sha256:d4785f74a73e822e790904a17dcd2ead067393b3691f74ab01191ab0b5901f87"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:EQVTBAFHOU2XPHVQ5WCEUOELF3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"LsrIF: Enhancing Logic-Structured Instruction Following of Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Fei Yu, Geng Zhang, Han Xia, Jiajie Zhu, Jiaqing Liang, Jingwen Chang, Qianyu He, Qingyu Ren, Xingzhou Chen, Yanghua Xiao, Zeye Sun, Zhuofei Shi","submitted_at":"2026-01-10T05:11:38Z","abstract_excerpt":"Instruction following is critical for large language models, yet real-world instructions often involve multiple constraints with logical structures, such as parallel composition, sequential dependencies, and conditional branching. Existing methods typically construct data by simply combining constraints and aggregate rewards by averaging individual constraint scores during training, overlooking logical dependencies and introducing noisy signals. We propose LsrIF, a training framework for logic-structured instruction following. LsrIF constructs data by organizing atomic constraints into paralle"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.06431","kind":"arxiv","version":3},"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/2601.06431/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":"2026-05-29T01:05:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hn+BMj3coS01GKVK9yGObGf0awdgfq+6v88N2cAJUgAGXSSGTzgD+uxTPJXjtQ2c7LaOZQhkH5es398A5lpMBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-30T23:31:14.121235Z"},"content_sha256":"a7b5a47784a2850070c76c50c599b36a12990d8145cb9632942b131e587660dc","schema_version":"1.0","event_id":"sha256:a7b5a47784a2850070c76c50c599b36a12990d8145cb9632942b131e587660dc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EQVTBAFHOU2XPHVQ5WCEUOELF3/bundle.json","state_url":"https://pith.science/pith/EQVTBAFHOU2XPHVQ5WCEUOELF3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EQVTBAFHOU2XPHVQ5WCEUOELF3/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":"2026-05-30T23:31:14Z","links":{"resolver":"https://pith.science/pith/EQVTBAFHOU2XPHVQ5WCEUOELF3","bundle":"https://pith.science/pith/EQVTBAFHOU2XPHVQ5WCEUOELF3/bundle.json","state":"https://pith.science/pith/EQVTBAFHOU2XPHVQ5WCEUOELF3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EQVTBAFHOU2XPHVQ5WCEUOELF3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:EQVTBAFHOU2XPHVQ5WCEUOELF3","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":"52416339693cd3e9dfa01a026d348ef36e9989009ebaf5c0b0c5209713594eb1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-01-10T05:11:38Z","title_canon_sha256":"7ab0048d18f23c4459de1b11aad3a02a7f49011b78304b1f962b98877be16f74"},"schema_version":"1.0","source":{"id":"2601.06431","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2601.06431","created_at":"2026-05-29T01:05:01Z"},{"alias_kind":"arxiv_version","alias_value":"2601.06431v3","created_at":"2026-05-29T01:05:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2601.06431","created_at":"2026-05-29T01:05:01Z"},{"alias_kind":"pith_short_12","alias_value":"EQVTBAFHOU2X","created_at":"2026-05-29T01:05:01Z"},{"alias_kind":"pith_short_16","alias_value":"EQVTBAFHOU2XPHVQ","created_at":"2026-05-29T01:05:01Z"},{"alias_kind":"pith_short_8","alias_value":"EQVTBAFH","created_at":"2026-05-29T01:05:01Z"}],"graph_snapshots":[{"event_id":"sha256:a7b5a47784a2850070c76c50c599b36a12990d8145cb9632942b131e587660dc","target":"graph","created_at":"2026-05-29T01:05:01Z","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/2601.06431/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Instruction following is critical for large language models, yet real-world instructions often involve multiple constraints with logical structures, such as parallel composition, sequential dependencies, and conditional branching. Existing methods typically construct data by simply combining constraints and aggregate rewards by averaging individual constraint scores during training, overlooking logical dependencies and introducing noisy signals. We propose LsrIF, a training framework for logic-structured instruction following. LsrIF constructs data by organizing atomic constraints into paralle","authors_text":"Fei Yu, Geng Zhang, Han Xia, Jiajie Zhu, Jiaqing Liang, Jingwen Chang, Qianyu He, Qingyu Ren, Xingzhou Chen, Yanghua Xiao, Zeye Sun, Zhuofei Shi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-01-10T05:11:38Z","title":"LsrIF: Enhancing Logic-Structured Instruction Following of Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2601.06431","kind":"arxiv","version":3},"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:d4785f74a73e822e790904a17dcd2ead067393b3691f74ab01191ab0b5901f87","target":"record","created_at":"2026-05-29T01:05:01Z","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":"52416339693cd3e9dfa01a026d348ef36e9989009ebaf5c0b0c5209713594eb1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-01-10T05:11:38Z","title_canon_sha256":"7ab0048d18f23c4459de1b11aad3a02a7f49011b78304b1f962b98877be16f74"},"schema_version":"1.0","source":{"id":"2601.06431","kind":"arxiv","version":3}},"canonical_sha256":"242b3080a77535779eb0ed844a388b2ef19443b08aba16c026245167a8ae8327","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"242b3080a77535779eb0ed844a388b2ef19443b08aba16c026245167a8ae8327","first_computed_at":"2026-05-29T01:05:01.695263Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T01:05:01.695263Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"O6K7wWOiyb0DbZWtQej9OsngpkbSXoYOtOzLY9VobC0mtG2QDDxN1jOyuOyPVC1qsP8fjL2+tixlwR7fddbJBw==","signature_status":"signed_v1","signed_at":"2026-05-29T01:05:01.696171Z","signed_message":"canonical_sha256_bytes"},"source_id":"2601.06431","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d4785f74a73e822e790904a17dcd2ead067393b3691f74ab01191ab0b5901f87","sha256:a7b5a47784a2850070c76c50c599b36a12990d8145cb9632942b131e587660dc"],"state_sha256":"cc078cc7ee7fa775338e0e5c4f52b7d23413bb55b14ec638e92d178d9afd4730"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z2/HHT4Ec1a46/bmQ2A3LKh/WElwXWp4atKr2jYCNrnmE34TreTfTSR4hHLAqMFF/chDjDy9EZMv7xQ0Uxn4DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-30T23:31:14.125488Z","bundle_sha256":"b357bc7295d552fda10a7015b398424c3f92a1f3d5a44126019bc0ab9f1103a4"}}