{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:WMFR2SZTGCXNIVAHZSSCE5FQSW","short_pith_number":"pith:WMFR2SZT","canonical_record":{"source":{"id":"2603.17310","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-03-18T03:11:36Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"961ae8c4813cf5ad432fede6895339f77ae2b9d85e383cec36360c03e5dc2bc5","abstract_canon_sha256":"4de1a2e6ec244873d3564def2944ab9816d78d1bcaa4665a137b27c0186e4867"},"schema_version":"1.0"},"canonical_sha256":"b30b1d4b3330aed45407cca42274b0958e455bc42295206e4a23d07c01f2a64c","source":{"kind":"arxiv","id":"2603.17310","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.17310","created_at":"2026-06-05T01:14:36Z"},{"alias_kind":"arxiv_version","alias_value":"2603.17310v2","created_at":"2026-06-05T01:14:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.17310","created_at":"2026-06-05T01:14:36Z"},{"alias_kind":"pith_short_12","alias_value":"WMFR2SZTGCXN","created_at":"2026-06-05T01:14:36Z"},{"alias_kind":"pith_short_16","alias_value":"WMFR2SZTGCXNIVAH","created_at":"2026-06-05T01:14:36Z"},{"alias_kind":"pith_short_8","alias_value":"WMFR2SZT","created_at":"2026-06-05T01:14:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:WMFR2SZTGCXNIVAHZSSCE5FQSW","target":"record","payload":{"canonical_record":{"source":{"id":"2603.17310","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-03-18T03:11:36Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"961ae8c4813cf5ad432fede6895339f77ae2b9d85e383cec36360c03e5dc2bc5","abstract_canon_sha256":"4de1a2e6ec244873d3564def2944ab9816d78d1bcaa4665a137b27c0186e4867"},"schema_version":"1.0"},"canonical_sha256":"b30b1d4b3330aed45407cca42274b0958e455bc42295206e4a23d07c01f2a64c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-05T01:14:36.900435Z","signature_b64":"eUrZjqtE1VxQ1j3FWOg96pBCYynfrlIBtsr+of11gfBYLHTr9FWKm4xz5jVjM0a94ECa/W/3ORd3DGFs94PUBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b30b1d4b3330aed45407cca42274b0958e455bc42295206e4a23d07c01f2a64c","last_reissued_at":"2026-06-05T01:14:36.899546Z","signature_status":"signed_v1","first_computed_at":"2026-06-05T01:14:36.899546Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2603.17310","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":"2026-06-05T01:14:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n7nl2oWrdtf7Jp5jP8UrEJXvCvX/5udtmxNQK85zCZCO3tjjsAeDGgldkuaDMDv1ZqZo/x92mD/DfroNyKqFAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T07:55:22.740295Z"},"content_sha256":"0f8dd9f4354ba4cc70ec6c1dd3b6ecfc814d5188abcce26f726bf6f3d3261239","schema_version":"1.0","event_id":"sha256:0f8dd9f4354ba4cc70ec6c1dd3b6ecfc814d5188abcce26f726bf6f3d3261239"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:WMFR2SZTGCXNIVAHZSSCE5FQSW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"InfoDensity: Rewarding Information-Dense Traces for Efficient Reasoning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Chengwei Wei, Jung-jae Kim, Longyin Zhang, Nancy F. Chen, Shengkai Chen","submitted_at":"2026-03-18T03:11:36Z","abstract_excerpt":"Large Language Models (LLMs) with extended reasoning capabilities often generate verbose and redundant reasoning traces, incurring unnecessary computational cost. While existing reinforcement learning approaches address this by optimizing final response length, they neglect the quality of intermediate reasoning steps, leaving models vulnerable to reward hacking. We argue that verbosity is not merely a length problem, but a symptom of poor intermediate reasoning quality. To investigate this, we conduct an empirical study tracking the per-token predictive entropy of large reasoning models across"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.17310","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/2603.17310/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":"2026-06-05T01:14:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cPu1Jpwlmactrmrfbmx0PyFer72rP5FE/+RTwCRGhkaOejmmHohejIHqetE5zlpcYAbNkEygEhbCNvggD30TCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-03T07:55:22.740688Z"},"content_sha256":"48ec0dbc1de4e5c18c99d102648e60f14f7dbeef38b165ff27e6386b435b9452","schema_version":"1.0","event_id":"sha256:48ec0dbc1de4e5c18c99d102648e60f14f7dbeef38b165ff27e6386b435b9452"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WMFR2SZTGCXNIVAHZSSCE5FQSW/bundle.json","state_url":"https://pith.science/pith/WMFR2SZTGCXNIVAHZSSCE5FQSW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WMFR2SZTGCXNIVAHZSSCE5FQSW/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":"2026-07-03T07:55:22Z","links":{"resolver":"https://pith.science/pith/WMFR2SZTGCXNIVAHZSSCE5FQSW","bundle":"https://pith.science/pith/WMFR2SZTGCXNIVAHZSSCE5FQSW/bundle.json","state":"https://pith.science/pith/WMFR2SZTGCXNIVAHZSSCE5FQSW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WMFR2SZTGCXNIVAHZSSCE5FQSW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WMFR2SZTGCXNIVAHZSSCE5FQSW","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":"4de1a2e6ec244873d3564def2944ab9816d78d1bcaa4665a137b27c0186e4867","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-03-18T03:11:36Z","title_canon_sha256":"961ae8c4813cf5ad432fede6895339f77ae2b9d85e383cec36360c03e5dc2bc5"},"schema_version":"1.0","source":{"id":"2603.17310","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2603.17310","created_at":"2026-06-05T01:14:36Z"},{"alias_kind":"arxiv_version","alias_value":"2603.17310v2","created_at":"2026-06-05T01:14:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2603.17310","created_at":"2026-06-05T01:14:36Z"},{"alias_kind":"pith_short_12","alias_value":"WMFR2SZTGCXN","created_at":"2026-06-05T01:14:36Z"},{"alias_kind":"pith_short_16","alias_value":"WMFR2SZTGCXNIVAH","created_at":"2026-06-05T01:14:36Z"},{"alias_kind":"pith_short_8","alias_value":"WMFR2SZT","created_at":"2026-06-05T01:14:36Z"}],"graph_snapshots":[{"event_id":"sha256:48ec0dbc1de4e5c18c99d102648e60f14f7dbeef38b165ff27e6386b435b9452","target":"graph","created_at":"2026-06-05T01:14:36Z","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/2603.17310/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) with extended reasoning capabilities often generate verbose and redundant reasoning traces, incurring unnecessary computational cost. While existing reinforcement learning approaches address this by optimizing final response length, they neglect the quality of intermediate reasoning steps, leaving models vulnerable to reward hacking. We argue that verbosity is not merely a length problem, but a symptom of poor intermediate reasoning quality. To investigate this, we conduct an empirical study tracking the per-token predictive entropy of large reasoning models across","authors_text":"Chengwei Wei, Jung-jae Kim, Longyin Zhang, Nancy F. Chen, Shengkai Chen","cross_cats":["cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-03-18T03:11:36Z","title":"InfoDensity: Rewarding Information-Dense Traces for Efficient Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2603.17310","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":"sha256:0f8dd9f4354ba4cc70ec6c1dd3b6ecfc814d5188abcce26f726bf6f3d3261239","target":"record","created_at":"2026-06-05T01:14:36Z","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":"4de1a2e6ec244873d3564def2944ab9816d78d1bcaa4665a137b27c0186e4867","cross_cats_sorted":["cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-03-18T03:11:36Z","title_canon_sha256":"961ae8c4813cf5ad432fede6895339f77ae2b9d85e383cec36360c03e5dc2bc5"},"schema_version":"1.0","source":{"id":"2603.17310","kind":"arxiv","version":2}},"canonical_sha256":"b30b1d4b3330aed45407cca42274b0958e455bc42295206e4a23d07c01f2a64c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b30b1d4b3330aed45407cca42274b0958e455bc42295206e4a23d07c01f2a64c","first_computed_at":"2026-06-05T01:14:36.899546Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-05T01:14:36.899546Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eUrZjqtE1VxQ1j3FWOg96pBCYynfrlIBtsr+of11gfBYLHTr9FWKm4xz5jVjM0a94ECa/W/3ORd3DGFs94PUBw==","signature_status":"signed_v1","signed_at":"2026-06-05T01:14:36.900435Z","signed_message":"canonical_sha256_bytes"},"source_id":"2603.17310","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0f8dd9f4354ba4cc70ec6c1dd3b6ecfc814d5188abcce26f726bf6f3d3261239","sha256:48ec0dbc1de4e5c18c99d102648e60f14f7dbeef38b165ff27e6386b435b9452"],"state_sha256":"c5620265ee88b3e857676f26222b0391d04578d02d1099a4c8779511ee3f9a5e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VvpnQDXBp/vi/ApK0sCVmjR1kPALkz94vJMAXrB9UI4I8f5ozhqhah4GU1+4BnGBfEmfVyQLxTIQGQ1xt1wzBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-03T07:55:22.742704Z","bundle_sha256":"db75ff0fb840717c81c292482342c5387a12134eb0c97bfacf50ae4a01c7950a"}}