{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SBNFQ5YKA6LD67NR7ZQFTBBA6T","short_pith_number":"pith:SBNFQ5YK","canonical_record":{"source":{"id":"2412.20834","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-30T09:58:31Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5735d9941a830cfddb7cf55fe9093f1bbc7bf03a2a0fbbd820513102af12dead","abstract_canon_sha256":"a750ff5f9d31f17b999625f2e19bdd0f954e9baa85fba06b5f06bf0569ebc770"},"schema_version":"1.0"},"canonical_sha256":"905a58770a07963f7db1fe60598420f4d1dacdda9159ab7524569d3f27f25e7e","source":{"kind":"arxiv","id":"2412.20834","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.20834","created_at":"2026-07-05T09:55:23Z"},{"alias_kind":"arxiv_version","alias_value":"2412.20834v1","created_at":"2026-07-05T09:55:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.20834","created_at":"2026-07-05T09:55:23Z"},{"alias_kind":"pith_short_12","alias_value":"SBNFQ5YKA6LD","created_at":"2026-07-05T09:55:23Z"},{"alias_kind":"pith_short_16","alias_value":"SBNFQ5YKA6LD67NR","created_at":"2026-07-05T09:55:23Z"},{"alias_kind":"pith_short_8","alias_value":"SBNFQ5YK","created_at":"2026-07-05T09:55:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SBNFQ5YKA6LD67NR7ZQFTBBA6T","target":"record","payload":{"canonical_record":{"source":{"id":"2412.20834","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-30T09:58:31Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5735d9941a830cfddb7cf55fe9093f1bbc7bf03a2a0fbbd820513102af12dead","abstract_canon_sha256":"a750ff5f9d31f17b999625f2e19bdd0f954e9baa85fba06b5f06bf0569ebc770"},"schema_version":"1.0"},"canonical_sha256":"905a58770a07963f7db1fe60598420f4d1dacdda9159ab7524569d3f27f25e7e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:55:23.226865Z","signature_b64":"t9FqXnB+JLnssP0/Y/qMC2ob7NyxvEZcY0OWnrKOc1qGTovRMrFgYMhFdX1oDb4/tMtrzl9xicH4b5H5gKsWCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"905a58770a07963f7db1fe60598420f4d1dacdda9159ab7524569d3f27f25e7e","last_reissued_at":"2026-07-05T09:55:23.226443Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:55:23.226443Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.20834","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":"2026-07-05T09:55:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Dnlt4toCK3xQ0k8r00WAmz9vQgYY1/lbMQ4WMDizBVvP7uYQFCURcJPg9z5BA7eDYCdU+qm9MszIQVnYzTOdDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T12:25:30.175774Z"},"content_sha256":"63381e433dbb92d796fe96b38c9f11397c633a4cd83d8f3e08144755213941c9","schema_version":"1.0","event_id":"sha256:63381e433dbb92d796fe96b38c9f11397c633a4cd83d8f3e08144755213941c9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SBNFQ5YKA6LD67NR7ZQFTBBA6T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Disentangling Preference Representation and Text Generation for Efficient Individual Preference Alignment","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Bei Li, Chenghua Lin, Jianfei Zhang, Jun Bai, Rumei Li, Wenge Rong, Yanmeng Wang","submitted_at":"2024-12-30T09:58:31Z","abstract_excerpt":"Aligning Large Language Models (LLMs) with general human preferences has been proved crucial in improving the interaction quality between LLMs and human. However, human values are inherently diverse among different individuals, making it insufficient to align LLMs solely with general preferences. To address this, personalizing LLMs according to individual feedback emerges as a promising solution. Nonetheless, this approach presents challenges in terms of the efficiency of alignment algorithms. In this work, we introduce a flexible paradigm for individual preference alignment. Our method fundam"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.20834","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/2412.20834/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":"2026-07-05T09:55:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZMWnqaaF6AJ/JcMYcOZxDhdab2Fs8uCqKEqdRJSWT2iYXU/jVoFA067Q7A9jK7ljBAzNYblpmoe8RjB4vSvqDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T12:25:30.176141Z"},"content_sha256":"e5e254c06e959b1c13beff1f240a64b91e0d88d5c2ef572a3c11f86b6d32e5b4","schema_version":"1.0","event_id":"sha256:e5e254c06e959b1c13beff1f240a64b91e0d88d5c2ef572a3c11f86b6d32e5b4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SBNFQ5YKA6LD67NR7ZQFTBBA6T/bundle.json","state_url":"https://pith.science/pith/SBNFQ5YKA6LD67NR7ZQFTBBA6T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SBNFQ5YKA6LD67NR7ZQFTBBA6T/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":"2026-07-07T12:25:30Z","links":{"resolver":"https://pith.science/pith/SBNFQ5YKA6LD67NR7ZQFTBBA6T","bundle":"https://pith.science/pith/SBNFQ5YKA6LD67NR7ZQFTBBA6T/bundle.json","state":"https://pith.science/pith/SBNFQ5YKA6LD67NR7ZQFTBBA6T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SBNFQ5YKA6LD67NR7ZQFTBBA6T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SBNFQ5YKA6LD67NR7ZQFTBBA6T","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":"a750ff5f9d31f17b999625f2e19bdd0f954e9baa85fba06b5f06bf0569ebc770","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-30T09:58:31Z","title_canon_sha256":"5735d9941a830cfddb7cf55fe9093f1bbc7bf03a2a0fbbd820513102af12dead"},"schema_version":"1.0","source":{"id":"2412.20834","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.20834","created_at":"2026-07-05T09:55:23Z"},{"alias_kind":"arxiv_version","alias_value":"2412.20834v1","created_at":"2026-07-05T09:55:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.20834","created_at":"2026-07-05T09:55:23Z"},{"alias_kind":"pith_short_12","alias_value":"SBNFQ5YKA6LD","created_at":"2026-07-05T09:55:23Z"},{"alias_kind":"pith_short_16","alias_value":"SBNFQ5YKA6LD67NR","created_at":"2026-07-05T09:55:23Z"},{"alias_kind":"pith_short_8","alias_value":"SBNFQ5YK","created_at":"2026-07-05T09:55:23Z"}],"graph_snapshots":[{"event_id":"sha256:e5e254c06e959b1c13beff1f240a64b91e0d88d5c2ef572a3c11f86b6d32e5b4","target":"graph","created_at":"2026-07-05T09:55:23Z","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/2412.20834/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Aligning Large Language Models (LLMs) with general human preferences has been proved crucial in improving the interaction quality between LLMs and human. However, human values are inherently diverse among different individuals, making it insufficient to align LLMs solely with general preferences. To address this, personalizing LLMs according to individual feedback emerges as a promising solution. Nonetheless, this approach presents challenges in terms of the efficiency of alignment algorithms. In this work, we introduce a flexible paradigm for individual preference alignment. Our method fundam","authors_text":"Bei Li, Chenghua Lin, Jianfei Zhang, Jun Bai, Rumei Li, Wenge Rong, Yanmeng Wang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-30T09:58:31Z","title":"Disentangling Preference Representation and Text Generation for Efficient Individual Preference Alignment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.20834","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":"sha256:63381e433dbb92d796fe96b38c9f11397c633a4cd83d8f3e08144755213941c9","target":"record","created_at":"2026-07-05T09:55:23Z","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":"a750ff5f9d31f17b999625f2e19bdd0f954e9baa85fba06b5f06bf0569ebc770","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-30T09:58:31Z","title_canon_sha256":"5735d9941a830cfddb7cf55fe9093f1bbc7bf03a2a0fbbd820513102af12dead"},"schema_version":"1.0","source":{"id":"2412.20834","kind":"arxiv","version":1}},"canonical_sha256":"905a58770a07963f7db1fe60598420f4d1dacdda9159ab7524569d3f27f25e7e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"905a58770a07963f7db1fe60598420f4d1dacdda9159ab7524569d3f27f25e7e","first_computed_at":"2026-07-05T09:55:23.226443Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:55:23.226443Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"t9FqXnB+JLnssP0/Y/qMC2ob7NyxvEZcY0OWnrKOc1qGTovRMrFgYMhFdX1oDb4/tMtrzl9xicH4b5H5gKsWCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:55:23.226865Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.20834","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:63381e433dbb92d796fe96b38c9f11397c633a4cd83d8f3e08144755213941c9","sha256:e5e254c06e959b1c13beff1f240a64b91e0d88d5c2ef572a3c11f86b6d32e5b4"],"state_sha256":"0f088c6274d36643f28388fef74300a93caad3b294d237db60831174448ebf02"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NNzpiDICCHnhQiIePpbjwH1NFIeY1F+o3wbeNncR8E/YuPixolhhP6jw0clH7wAvd8vHTwoQ0AGbmh7WFc9BBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T12:25:30.178102Z","bundle_sha256":"76d0bdb3842905e3dcaa2d2786813f061e8f65b883cca7adc0126af83365131b"}}