{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:CSVCIX3SGYE4YE24EJACS2LOIR","short_pith_number":"pith:CSVCIX3S","schema_version":"1.0","canonical_sha256":"14aa245f723609cc135c224029696e44401ae143bbb8d1199029fce556d11d02","source":{"kind":"arxiv","id":"2603.08462","version":2},"attestation_state":"computed","paper":{"title":"Reasoning as Compression: Unifying Budget Forcing via the Conditional Information Bottleneck","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Andrey Kuzmin, Arash Behboodi, Fabio Valerio Massoli","submitted_at":"2026-03-09T14:56:57Z","abstract_excerpt":"\\ac{CoT} prompting improves LLM accuracy on complex tasks but often increases token usage and inference cost. Existing ``Budget Forcing'' methods reduce cost via fine-tuning with heuristic length penalties, suppressing both essential reasoning and redundant filler. We recast efficient reasoning as a lossy compression problem under the \\ac{IB} principle, and identify a key theoretical gap when applying naive \\ac{IB} to transformers: attention violates the Markov property between prompt, reasoning trace, and response. To resolve this issue, we model \\ac{CoT} generation under the \\ac{CIB} princip"},"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":"2603.08462","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-03-09T14:56:57Z","cross_cats_sorted":[],"title_canon_sha256":"4297b4e2dc42ac7c9465fea987d01a836cc8e8acad77ed2f338b46e2b17418ca","abstract_canon_sha256":"5d0e2b500785959110a968f3eb231e50d0956c31ea8886ca3891e59e2cfd8715"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:05:42.950064Z","signature_b64":"Rg1EZ4qhZz0a6k6PHKwneoum7llZYqG1MZmj23jdDpcpwvpXN97uJMJNBrOonh+62vzLNu45GDbo++Fq0eybBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"14aa245f723609cc135c224029696e44401ae143bbb8d1199029fce556d11d02","last_reissued_at":"2026-05-20T00:05:42.949553Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:05:42.949553Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Reasoning as Compression: Unifying Budget Forcing via the Conditional Information Bottleneck","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Andrey Kuzmin, Arash Behboodi, Fabio Valerio Massoli","submitted_at":"2026-03-09T14:56:57Z","abstract_excerpt":"\\ac{CoT} prompting improves LLM accuracy on complex tasks but often increases token usage and inference cost. Existing ``Budget Forcing'' methods reduce cost via fine-tuning with heuristic length penalties, suppressing both essential reasoning and redundant filler. We recast efficient reasoning as a lossy compression problem under the \\ac{IB} principle, and identify a key theoretical gap when applying naive \\ac{IB} to transformers: attention violates the Markov property between prompt, reasoning trace, and response. To resolve this issue, we model \\ac{CoT} generation under the \\ac{CIB} princip"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.08462","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/2603.08462/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":"2603.08462","created_at":"2026-05-20T00:05:42.949614+00:00"},{"alias_kind":"arxiv_version","alias_value":"2603.08462v2","created_at":"2026-05-20T00:05:42.949614+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.08462","created_at":"2026-05-20T00:05:42.949614+00:00"},{"alias_kind":"pith_short_12","alias_value":"CSVCIX3SGYE4","created_at":"2026-05-20T00:05:42.949614+00:00"},{"alias_kind":"pith_short_16","alias_value":"CSVCIX3SGYE4YE24","created_at":"2026-05-20T00:05:42.949614+00:00"},{"alias_kind":"pith_short_8","alias_value":"CSVCIX3S","created_at":"2026-05-20T00:05:42.949614+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/CSVCIX3SGYE4YE24EJACS2LOIR","json":"https://pith.science/pith/CSVCIX3SGYE4YE24EJACS2LOIR.json","graph_json":"https://pith.science/api/pith-number/CSVCIX3SGYE4YE24EJACS2LOIR/graph.json","events_json":"https://pith.science/api/pith-number/CSVCIX3SGYE4YE24EJACS2LOIR/events.json","paper":"https://pith.science/paper/CSVCIX3S"},"agent_actions":{"view_html":"https://pith.science/pith/CSVCIX3SGYE4YE24EJACS2LOIR","download_json":"https://pith.science/pith/CSVCIX3SGYE4YE24EJACS2LOIR.json","view_paper":"https://pith.science/paper/CSVCIX3S","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2603.08462&json=true","fetch_graph":"https://pith.science/api/pith-number/CSVCIX3SGYE4YE24EJACS2LOIR/graph.json","fetch_events":"https://pith.science/api/pith-number/CSVCIX3SGYE4YE24EJACS2LOIR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CSVCIX3SGYE4YE24EJACS2LOIR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CSVCIX3SGYE4YE24EJACS2LOIR/action/storage_attestation","attest_author":"https://pith.science/pith/CSVCIX3SGYE4YE24EJACS2LOIR/action/author_attestation","sign_citation":"https://pith.science/pith/CSVCIX3SGYE4YE24EJACS2LOIR/action/citation_signature","submit_replication":"https://pith.science/pith/CSVCIX3SGYE4YE24EJACS2LOIR/action/replication_record"}},"created_at":"2026-05-20T00:05:42.949614+00:00","updated_at":"2026-05-20T00:05:42.949614+00:00"}