{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:VLBFLJ5VBQQ5WEYOTYYGLVDY3C","short_pith_number":"pith:VLBFLJ5V","schema_version":"1.0","canonical_sha256":"aac255a7b50c21db130e9e3065d478d88dd07b913c83d01f9aa719d5bf712139","source":{"kind":"arxiv","id":"2606.11599","version":1},"attestation_state":"computed","paper":{"title":"When is Your LLM Steerable?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Chenrui Fan, Ming Li, Soheil Feizi, Tianyi Zhou, Yize Cheng","submitted_at":"2026-06-10T02:55:34Z","abstract_excerpt":"Activation steering offers a lightweight approach to control language models' behavior at inference time, but whether it succeeds or fails heavily depends on the prompt, concept, model, and steering configuration. Finding the regime and boundaries of successful steering typically requires expensive grid searches and post-hoc evaluation of full autoregressive rollouts. In this work, we investigate whether steerability can be predicted from the model's internal states at the beginning of the generation process, e.g., after generating the first few tokens, and how to leverage such a predictor to "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2606.11599","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-06-10T02:55:34Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"2ca50729dd38853d3e8968507cbf5bbabb7746701dcff260edfed7a97b64c1f6","abstract_canon_sha256":"447401ff377a8e88f948628eb5f9a497e77786e33355508f436b29ba12b321bb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-11T01:09:58.411083Z","signature_b64":"ZmJshekKH8qYJh0RyL0aCt1f8spc4lHoSE3wPokT8kDQPk77qJkCsqR0RmwzkgRP8vLQwwBcBwujhCN/FrReBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aac255a7b50c21db130e9e3065d478d88dd07b913c83d01f9aa719d5bf712139","last_reissued_at":"2026-06-11T01:09:58.410085Z","signature_status":"signed_v1","first_computed_at":"2026-06-11T01:09:58.410085Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"When is Your LLM Steerable?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Chenrui Fan, Ming Li, Soheil Feizi, Tianyi Zhou, Yize Cheng","submitted_at":"2026-06-10T02:55:34Z","abstract_excerpt":"Activation steering offers a lightweight approach to control language models' behavior at inference time, but whether it succeeds or fails heavily depends on the prompt, concept, model, and steering configuration. Finding the regime and boundaries of successful steering typically requires expensive grid searches and post-hoc evaluation of full autoregressive rollouts. In this work, we investigate whether steerability can be predicted from the model's internal states at the beginning of the generation process, e.g., after generating the first few tokens, and how to leverage such a predictor to "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.11599","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/2606.11599/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2606.11599","created_at":"2026-06-11T01:09:58.410211+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.11599v1","created_at":"2026-06-11T01:09:58.410211+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.11599","created_at":"2026-06-11T01:09:58.410211+00:00"},{"alias_kind":"pith_short_12","alias_value":"VLBFLJ5VBQQ5","created_at":"2026-06-11T01:09:58.410211+00:00"},{"alias_kind":"pith_short_16","alias_value":"VLBFLJ5VBQQ5WEYO","created_at":"2026-06-11T01:09:58.410211+00:00"},{"alias_kind":"pith_short_8","alias_value":"VLBFLJ5V","created_at":"2026-06-11T01:09:58.410211+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/VLBFLJ5VBQQ5WEYOTYYGLVDY3C","json":"https://pith.science/pith/VLBFLJ5VBQQ5WEYOTYYGLVDY3C.json","graph_json":"https://pith.science/api/pith-number/VLBFLJ5VBQQ5WEYOTYYGLVDY3C/graph.json","events_json":"https://pith.science/api/pith-number/VLBFLJ5VBQQ5WEYOTYYGLVDY3C/events.json","paper":"https://pith.science/paper/VLBFLJ5V"},"agent_actions":{"view_html":"https://pith.science/pith/VLBFLJ5VBQQ5WEYOTYYGLVDY3C","download_json":"https://pith.science/pith/VLBFLJ5VBQQ5WEYOTYYGLVDY3C.json","view_paper":"https://pith.science/paper/VLBFLJ5V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.11599&json=true","fetch_graph":"https://pith.science/api/pith-number/VLBFLJ5VBQQ5WEYOTYYGLVDY3C/graph.json","fetch_events":"https://pith.science/api/pith-number/VLBFLJ5VBQQ5WEYOTYYGLVDY3C/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/VLBFLJ5VBQQ5WEYOTYYGLVDY3C/action/timestamp_anchor","attest_storage":"https://pith.science/pith/VLBFLJ5VBQQ5WEYOTYYGLVDY3C/action/storage_attestation","attest_author":"https://pith.science/pith/VLBFLJ5VBQQ5WEYOTYYGLVDY3C/action/author_attestation","sign_citation":"https://pith.science/pith/VLBFLJ5VBQQ5WEYOTYYGLVDY3C/action/citation_signature","submit_replication":"https://pith.science/pith/VLBFLJ5VBQQ5WEYOTYYGLVDY3C/action/replication_record"}},"created_at":"2026-06-11T01:09:58.410211+00:00","updated_at":"2026-06-11T01:09:58.410211+00:00"}