{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SDTXAZBQENP6MVYBDDYIDSZQ7Z","short_pith_number":"pith:SDTXAZBQ","canonical_record":{"source":{"id":"2505.04260","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-05-07T09:10:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1679effd9827dfec0294aabf75e6e85e961b9309b17684eb6ce172e8d33561f7","abstract_canon_sha256":"ccae3ccc4981ce09e0730f343426b428bd9d946acdca85b693f24f02ee745700"},"schema_version":"1.0"},"canonical_sha256":"90e7706430235fe6570118f081cb30fe461e69f7330ed86978616714c9257f1e","source":{"kind":"arxiv","id":"2505.04260","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.04260","created_at":"2026-07-05T11:02:43Z"},{"alias_kind":"arxiv_version","alias_value":"2505.04260v2","created_at":"2026-07-05T11:02:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.04260","created_at":"2026-07-05T11:02:43Z"},{"alias_kind":"pith_short_12","alias_value":"SDTXAZBQENP6","created_at":"2026-07-05T11:02:43Z"},{"alias_kind":"pith_short_16","alias_value":"SDTXAZBQENP6MVYB","created_at":"2026-07-05T11:02:43Z"},{"alias_kind":"pith_short_8","alias_value":"SDTXAZBQ","created_at":"2026-07-05T11:02:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SDTXAZBQENP6MVYBDDYIDSZQ7Z","target":"record","payload":{"canonical_record":{"source":{"id":"2505.04260","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-05-07T09:10:51Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1679effd9827dfec0294aabf75e6e85e961b9309b17684eb6ce172e8d33561f7","abstract_canon_sha256":"ccae3ccc4981ce09e0730f343426b428bd9d946acdca85b693f24f02ee745700"},"schema_version":"1.0"},"canonical_sha256":"90e7706430235fe6570118f081cb30fe461e69f7330ed86978616714c9257f1e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:02:43.564575Z","signature_b64":"gtdSsFkabnMm9w681wNKEb5p5DDNEimq5uIu4dyXz0Ot1/NSXluq6xCc23JQQQ9UrWM2ig+LjMgLfFkGo94BBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"90e7706430235fe6570118f081cb30fe461e69f7330ed86978616714c9257f1e","last_reissued_at":"2026-07-05T11:02:43.564086Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:02:43.564086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.04260","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:02:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Zq98ADcLDkaIsYQBf8zd2wRyDVZ4vp9PV9peWfSgKwI+TV8SG+vAoC8+rxQox2PF/ZSVc/TOTuwHl8nmMr37BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:48:34.097295Z"},"content_sha256":"589803a10ca2beaea651e95865722a4df350565dec1e19d2edec7284da1ad43e","schema_version":"1.0","event_id":"sha256:589803a10ca2beaea651e95865722a4df350565dec1e19d2edec7284da1ad43e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SDTXAZBQENP6MVYBDDYIDSZQ7Z","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Steerable Chatbots: Personalizing LLMs with Preference-Based Activation Steering","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.HC","authors_text":"Achin Kulshrestha, D Shin, Ishan Chatterjee, Jessica Y. Bo, Katrina Passarella-Ward, Tianyu Xu","submitted_at":"2025-05-07T09:10:51Z","abstract_excerpt":"As large language models (LLMs) improve in their capacity to serve as personal AI assistants, their ability to output uniquely tailored, personalized responses that align with the soft preferences of their users is essential for enhancing user satisfaction and retention. However, untrained lay users have poor prompt specification abilities and often struggle with conveying their latent preferences to AI assistants. To address this, we leverage activation steering to guide LLMs to align with interpretable preference dimensions during inference. In contrast to memory-based personalization method"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.04260","kind":"arxiv","version":2},"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/2505.04260/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":"2026-07-05T11:02:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Rbj7gxUBlOHfQBS8wmYXY6SQK5z9hDShzLqJTC96zy3z2JOS4NsGPf80DxoTEzMfyw6/OJ/Dd6sJATOISZD2Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T08:48:34.097815Z"},"content_sha256":"c0cfd6d1a729782d3c5f4aa3a74ef529a2d52dff315eff36a99ede53825a004f","schema_version":"1.0","event_id":"sha256:c0cfd6d1a729782d3c5f4aa3a74ef529a2d52dff315eff36a99ede53825a004f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SDTXAZBQENP6MVYBDDYIDSZQ7Z/bundle.json","state_url":"https://pith.science/pith/SDTXAZBQENP6MVYBDDYIDSZQ7Z/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SDTXAZBQENP6MVYBDDYIDSZQ7Z/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":"2026-08-04T08:48:34Z","links":{"resolver":"https://pith.science/pith/SDTXAZBQENP6MVYBDDYIDSZQ7Z","bundle":"https://pith.science/pith/SDTXAZBQENP6MVYBDDYIDSZQ7Z/bundle.json","state":"https://pith.science/pith/SDTXAZBQENP6MVYBDDYIDSZQ7Z/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SDTXAZBQENP6MVYBDDYIDSZQ7Z/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SDTXAZBQENP6MVYBDDYIDSZQ7Z","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":"ccae3ccc4981ce09e0730f343426b428bd9d946acdca85b693f24f02ee745700","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-05-07T09:10:51Z","title_canon_sha256":"1679effd9827dfec0294aabf75e6e85e961b9309b17684eb6ce172e8d33561f7"},"schema_version":"1.0","source":{"id":"2505.04260","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.04260","created_at":"2026-07-05T11:02:43Z"},{"alias_kind":"arxiv_version","alias_value":"2505.04260v2","created_at":"2026-07-05T11:02:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.04260","created_at":"2026-07-05T11:02:43Z"},{"alias_kind":"pith_short_12","alias_value":"SDTXAZBQENP6","created_at":"2026-07-05T11:02:43Z"},{"alias_kind":"pith_short_16","alias_value":"SDTXAZBQENP6MVYB","created_at":"2026-07-05T11:02:43Z"},{"alias_kind":"pith_short_8","alias_value":"SDTXAZBQ","created_at":"2026-07-05T11:02:43Z"}],"graph_snapshots":[{"event_id":"sha256:c0cfd6d1a729782d3c5f4aa3a74ef529a2d52dff315eff36a99ede53825a004f","target":"graph","created_at":"2026-07-05T11:02:43Z","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/2505.04260/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As large language models (LLMs) improve in their capacity to serve as personal AI assistants, their ability to output uniquely tailored, personalized responses that align with the soft preferences of their users is essential for enhancing user satisfaction and retention. However, untrained lay users have poor prompt specification abilities and often struggle with conveying their latent preferences to AI assistants. To address this, we leverage activation steering to guide LLMs to align with interpretable preference dimensions during inference. In contrast to memory-based personalization method","authors_text":"Achin Kulshrestha, D Shin, Ishan Chatterjee, Jessica Y. Bo, Katrina Passarella-Ward, Tianyu Xu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-05-07T09:10:51Z","title":"Steerable Chatbots: Personalizing LLMs with Preference-Based Activation Steering"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.04260","kind":"arxiv","version":2},"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":"sha256:589803a10ca2beaea651e95865722a4df350565dec1e19d2edec7284da1ad43e","target":"record","created_at":"2026-07-05T11:02:43Z","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":"ccae3ccc4981ce09e0730f343426b428bd9d946acdca85b693f24f02ee745700","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-05-07T09:10:51Z","title_canon_sha256":"1679effd9827dfec0294aabf75e6e85e961b9309b17684eb6ce172e8d33561f7"},"schema_version":"1.0","source":{"id":"2505.04260","kind":"arxiv","version":2}},"canonical_sha256":"90e7706430235fe6570118f081cb30fe461e69f7330ed86978616714c9257f1e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"90e7706430235fe6570118f081cb30fe461e69f7330ed86978616714c9257f1e","first_computed_at":"2026-07-05T11:02:43.564086Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:02:43.564086Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gtdSsFkabnMm9w681wNKEb5p5DDNEimq5uIu4dyXz0Ot1/NSXluq6xCc23JQQQ9UrWM2ig+LjMgLfFkGo94BBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:02:43.564575Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.04260","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:589803a10ca2beaea651e95865722a4df350565dec1e19d2edec7284da1ad43e","sha256:c0cfd6d1a729782d3c5f4aa3a74ef529a2d52dff315eff36a99ede53825a004f"],"state_sha256":"b88863119bf47d5063f01fafcbea3465aa6addc0b390bc51e50586ce44fdcd55"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QD9n4WDZUzv5xEneKzyF8CzTJ1nM8JgZ6+dENKuGMCV87ueXlOoGN362diIh+KTG16MFHHy8lPYn3CRIMvzaDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T08:48:34.101880Z","bundle_sha256":"454d0866a48f46e26af87901823914aa8087b1271f7ca6525fe520720bee792c"}}