{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:F7QRAIODMRDLV5P5YBVCVRIMPJ","short_pith_number":"pith:F7QRAIOD","canonical_record":{"source":{"id":"2304.01083","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-03T15:39:35Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"e77debf1c6c6946e0ca500a54a25f283f8fb17d69c0d19fd2d4bf3e186afb60e","abstract_canon_sha256":"60c2eb91096cb319dd787f09f6e8c4e7a117cc308bb9a3c94ae4c67b2ff417ac"},"schema_version":"1.0"},"canonical_sha256":"2fe11021c36446baf5fdc06a2ac50c7a75b17468e96aa9ed0c5dc4d521b74b1e","source":{"kind":"arxiv","id":"2304.01083","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.01083","created_at":"2026-07-05T05:57:26Z"},{"alias_kind":"arxiv_version","alias_value":"2304.01083v1","created_at":"2026-07-05T05:57:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.01083","created_at":"2026-07-05T05:57:26Z"},{"alias_kind":"pith_short_12","alias_value":"F7QRAIODMRDL","created_at":"2026-07-05T05:57:26Z"},{"alias_kind":"pith_short_16","alias_value":"F7QRAIODMRDLV5P5","created_at":"2026-07-05T05:57:26Z"},{"alias_kind":"pith_short_8","alias_value":"F7QRAIOD","created_at":"2026-07-05T05:57:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:F7QRAIODMRDLV5P5YBVCVRIMPJ","target":"record","payload":{"canonical_record":{"source":{"id":"2304.01083","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-03T15:39:35Z","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"title_canon_sha256":"e77debf1c6c6946e0ca500a54a25f283f8fb17d69c0d19fd2d4bf3e186afb60e","abstract_canon_sha256":"60c2eb91096cb319dd787f09f6e8c4e7a117cc308bb9a3c94ae4c67b2ff417ac"},"schema_version":"1.0"},"canonical_sha256":"2fe11021c36446baf5fdc06a2ac50c7a75b17468e96aa9ed0c5dc4d521b74b1e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:57:26.425432Z","signature_b64":"cgO8X6Yhr0u2z6N3rLoDI9QLnufApCTzGvO+ffpdM9HQRm3KX1mOIijnQVjbT9Afjl48tJpHSiV7nI/YZOK4CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2fe11021c36446baf5fdc06a2ac50c7a75b17468e96aa9ed0c5dc4d521b74b1e","last_reissued_at":"2026-07-05T05:57:26.425003Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:57:26.425003Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.01083","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":"2026-07-05T05:57:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"emX+LCHO4H1/Vx6KfhjopQOTclNybNbKRILNC0gpy6b+mm0NAhMd03TvhkbrhR8kkomDXLD/8y5yEQwLXwUeBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T22:37:47.902987Z"},"content_sha256":"9bb2380729cfd5d8e73560ac70ef4e96bfd8b49c9f1ed772c31a236e6c76e042","schema_version":"1.0","event_id":"sha256:9bb2380729cfd5d8e73560ac70ef4e96bfd8b49c9f1ed772c31a236e6c76e042"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:F7QRAIODMRDLV5P5YBVCVRIMPJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Can the Inference Logic of Large Language Models be Disentangled into Symbolic Concepts?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV","cs.LG"],"primary_cat":"cs.CL","authors_text":"Lei Cheng, Mingjie Li, Quanshi Zhang, Wen Shen, Yuxiao Yang","submitted_at":"2023-04-03T15:39:35Z","abstract_excerpt":"In this paper, we explain the inference logic of large language models (LLMs) as a set of symbolic concepts. Many recent studies have discovered that traditional DNNs usually encode sparse symbolic concepts. However, because an LLM has much more parameters than traditional DNNs, whether the LLM also encodes sparse symbolic concepts is still an open problem. Therefore, in this paper, we propose to disentangle the inference score of LLMs for dialogue tasks into a small number of symbolic concepts. We verify that we can use those sparse concepts to well estimate all inference scores of the LLM on"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.01083","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/2304.01083/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":"2026-07-05T05:57:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mz9do+0oGYkDzlr58suceAIniKs5lOf/sE7ptXPEKRQwEZ3oEVsMwZGllN2W4p+568i2ybPR7BdJ1Ks17sMDCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T22:37:47.904027Z"},"content_sha256":"46680c365fe39ac5703a5428cb3f9e54dd53fad0b1e91c6aafc82a7a194b869c","schema_version":"1.0","event_id":"sha256:46680c365fe39ac5703a5428cb3f9e54dd53fad0b1e91c6aafc82a7a194b869c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/F7QRAIODMRDLV5P5YBVCVRIMPJ/bundle.json","state_url":"https://pith.science/pith/F7QRAIODMRDLV5P5YBVCVRIMPJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/F7QRAIODMRDLV5P5YBVCVRIMPJ/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":"2026-08-09T22:37:47Z","links":{"resolver":"https://pith.science/pith/F7QRAIODMRDLV5P5YBVCVRIMPJ","bundle":"https://pith.science/pith/F7QRAIODMRDLV5P5YBVCVRIMPJ/bundle.json","state":"https://pith.science/pith/F7QRAIODMRDLV5P5YBVCVRIMPJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/F7QRAIODMRDLV5P5YBVCVRIMPJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:F7QRAIODMRDLV5P5YBVCVRIMPJ","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":"60c2eb91096cb319dd787f09f6e8c4e7a117cc308bb9a3c94ae4c67b2ff417ac","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-03T15:39:35Z","title_canon_sha256":"e77debf1c6c6946e0ca500a54a25f283f8fb17d69c0d19fd2d4bf3e186afb60e"},"schema_version":"1.0","source":{"id":"2304.01083","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.01083","created_at":"2026-07-05T05:57:26Z"},{"alias_kind":"arxiv_version","alias_value":"2304.01083v1","created_at":"2026-07-05T05:57:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.01083","created_at":"2026-07-05T05:57:26Z"},{"alias_kind":"pith_short_12","alias_value":"F7QRAIODMRDL","created_at":"2026-07-05T05:57:26Z"},{"alias_kind":"pith_short_16","alias_value":"F7QRAIODMRDLV5P5","created_at":"2026-07-05T05:57:26Z"},{"alias_kind":"pith_short_8","alias_value":"F7QRAIOD","created_at":"2026-07-05T05:57:26Z"}],"graph_snapshots":[{"event_id":"sha256:46680c365fe39ac5703a5428cb3f9e54dd53fad0b1e91c6aafc82a7a194b869c","target":"graph","created_at":"2026-07-05T05:57:26Z","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/2304.01083/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we explain the inference logic of large language models (LLMs) as a set of symbolic concepts. Many recent studies have discovered that traditional DNNs usually encode sparse symbolic concepts. However, because an LLM has much more parameters than traditional DNNs, whether the LLM also encodes sparse symbolic concepts is still an open problem. Therefore, in this paper, we propose to disentangle the inference score of LLMs for dialogue tasks into a small number of symbolic concepts. We verify that we can use those sparse concepts to well estimate all inference scores of the LLM on","authors_text":"Lei Cheng, Mingjie Li, Quanshi Zhang, Wen Shen, Yuxiao Yang","cross_cats":["cs.AI","cs.CV","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-03T15:39:35Z","title":"Can the Inference Logic of Large Language Models be Disentangled into Symbolic Concepts?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.01083","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":"sha256:9bb2380729cfd5d8e73560ac70ef4e96bfd8b49c9f1ed772c31a236e6c76e042","target":"record","created_at":"2026-07-05T05:57:26Z","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":"60c2eb91096cb319dd787f09f6e8c4e7a117cc308bb9a3c94ae4c67b2ff417ac","cross_cats_sorted":["cs.AI","cs.CV","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-04-03T15:39:35Z","title_canon_sha256":"e77debf1c6c6946e0ca500a54a25f283f8fb17d69c0d19fd2d4bf3e186afb60e"},"schema_version":"1.0","source":{"id":"2304.01083","kind":"arxiv","version":1}},"canonical_sha256":"2fe11021c36446baf5fdc06a2ac50c7a75b17468e96aa9ed0c5dc4d521b74b1e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2fe11021c36446baf5fdc06a2ac50c7a75b17468e96aa9ed0c5dc4d521b74b1e","first_computed_at":"2026-07-05T05:57:26.425003Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:57:26.425003Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cgO8X6Yhr0u2z6N3rLoDI9QLnufApCTzGvO+ffpdM9HQRm3KX1mOIijnQVjbT9Afjl48tJpHSiV7nI/YZOK4CA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:57:26.425432Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.01083","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9bb2380729cfd5d8e73560ac70ef4e96bfd8b49c9f1ed772c31a236e6c76e042","sha256:46680c365fe39ac5703a5428cb3f9e54dd53fad0b1e91c6aafc82a7a194b869c"],"state_sha256":"c920502c685b8f94729730e4528f6f98463e1d14e29f2961682e31b270286cc6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VHGGcN1NrQYa9b3vg8PF4jyS6wGRUXsZsB0HFyFeozAKEMlA5j9gTwIFRL0L3ccnXqnPY/PAB5iYG1uFVvT4Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T22:37:47.910790Z","bundle_sha256":"f446f386710f0b3fb4607502b7560c962ea2773af85709fc445d3d10632aadca"}}