{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:BVQMEQTSGZQ5HG45I7FUTURXMO","short_pith_number":"pith:BVQMEQTS","canonical_record":{"source":{"id":"2506.10716","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-12T14:05:09Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"a481055435e4f76865a5f2f4714cf9bd4514c9d7f6d8bc8b431b9d45c134765e","abstract_canon_sha256":"ecb3b006e302b4b2510466aa847012d67b22f37921d57d14c627d872e23220ed"},"schema_version":"1.0"},"canonical_sha256":"0d60c242723661d39b9d47cb49d23763a892afea0a5162a120e4c6224626b2f2","source":{"kind":"arxiv","id":"2506.10716","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.10716","created_at":"2026-07-05T11:20:29Z"},{"alias_kind":"arxiv_version","alias_value":"2506.10716v1","created_at":"2026-07-05T11:20:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.10716","created_at":"2026-07-05T11:20:29Z"},{"alias_kind":"pith_short_12","alias_value":"BVQMEQTSGZQ5","created_at":"2026-07-05T11:20:29Z"},{"alias_kind":"pith_short_16","alias_value":"BVQMEQTSGZQ5HG45","created_at":"2026-07-05T11:20:29Z"},{"alias_kind":"pith_short_8","alias_value":"BVQMEQTS","created_at":"2026-07-05T11:20:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:BVQMEQTSGZQ5HG45I7FUTURXMO","target":"record","payload":{"canonical_record":{"source":{"id":"2506.10716","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-12T14:05:09Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"a481055435e4f76865a5f2f4714cf9bd4514c9d7f6d8bc8b431b9d45c134765e","abstract_canon_sha256":"ecb3b006e302b4b2510466aa847012d67b22f37921d57d14c627d872e23220ed"},"schema_version":"1.0"},"canonical_sha256":"0d60c242723661d39b9d47cb49d23763a892afea0a5162a120e4c6224626b2f2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:20:29.080666Z","signature_b64":"zaboMUig3RCWH9nqY/Sd+YzdiEaTki45l3bfO+jrenrLFtEev0eElRA2GRukFNbamNfJwi+V5vLDqtUvASvBBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0d60c242723661d39b9d47cb49d23763a892afea0a5162a120e4c6224626b2f2","last_reissued_at":"2026-07-05T11:20:29.080041Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:20:29.080041Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.10716","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":"2026-07-05T11:20:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WSmMtANZ/uNxx4vh/UdSHgb5xF4f0vfExeNcf5E7BvU+01Jyf5Zb/QQ71zZL65RQQNu8kzaU9jSzQDORXLVTBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T17:04:02.512290Z"},"content_sha256":"eca16a657ad198b18ef2e659c6561aeaa9669d45bc6c9c0258457744aa36cf12","schema_version":"1.0","event_id":"sha256:eca16a657ad198b18ef2e659c6561aeaa9669d45bc6c9c0258457744aa36cf12"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:BVQMEQTSGZQ5HG45I7FUTURXMO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PREMISE: Scalable and Strategic Prompt Optimization for Efficient Mathematical Reasoning in Large Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Haohan Wang, Yaoning Yu, Ye Yu","submitted_at":"2025-06-12T14:05:09Z","abstract_excerpt":"Large reasoning models (LRMs) such as Claude 3.7 Sonnet and OpenAI o1 achieve strong performance on mathematical benchmarks using lengthy chain-of-thought (CoT) reasoning, but the resulting traces are often unnecessarily verbose. This inflates token usage and cost, limiting deployment in latency-sensitive or API-constrained settings. We introduce PREMISE (PRompt-based Efficient Mathematical Inference with Strategic Evaluation), a prompt-only framework that reduces reasoning overhead without modifying model weights. PREMISE combines trace-level diagnostics with gradient-inspired prompt optimiza"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.10716","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/2506.10716/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":"2026-07-05T11:20:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XjuoOCVkmwg2CdLUZgBMqXdZEk9Ik4WQpGvyK+ry3USYeCvg9Ai5B/4IGN7DEA2p0cOX5eUKf8mhuyulSV9cAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T17:04:02.513213Z"},"content_sha256":"962f7cd22f9e2a66e563189e049a677492f1f4beea3a0804da9b980c7c1d6bac","schema_version":"1.0","event_id":"sha256:962f7cd22f9e2a66e563189e049a677492f1f4beea3a0804da9b980c7c1d6bac"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BVQMEQTSGZQ5HG45I7FUTURXMO/bundle.json","state_url":"https://pith.science/pith/BVQMEQTSGZQ5HG45I7FUTURXMO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BVQMEQTSGZQ5HG45I7FUTURXMO/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":"2026-08-09T17:04:02Z","links":{"resolver":"https://pith.science/pith/BVQMEQTSGZQ5HG45I7FUTURXMO","bundle":"https://pith.science/pith/BVQMEQTSGZQ5HG45I7FUTURXMO/bundle.json","state":"https://pith.science/pith/BVQMEQTSGZQ5HG45I7FUTURXMO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BVQMEQTSGZQ5HG45I7FUTURXMO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:BVQMEQTSGZQ5HG45I7FUTURXMO","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":"ecb3b006e302b4b2510466aa847012d67b22f37921d57d14c627d872e23220ed","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-12T14:05:09Z","title_canon_sha256":"a481055435e4f76865a5f2f4714cf9bd4514c9d7f6d8bc8b431b9d45c134765e"},"schema_version":"1.0","source":{"id":"2506.10716","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.10716","created_at":"2026-07-05T11:20:29Z"},{"alias_kind":"arxiv_version","alias_value":"2506.10716v1","created_at":"2026-07-05T11:20:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.10716","created_at":"2026-07-05T11:20:29Z"},{"alias_kind":"pith_short_12","alias_value":"BVQMEQTSGZQ5","created_at":"2026-07-05T11:20:29Z"},{"alias_kind":"pith_short_16","alias_value":"BVQMEQTSGZQ5HG45","created_at":"2026-07-05T11:20:29Z"},{"alias_kind":"pith_short_8","alias_value":"BVQMEQTS","created_at":"2026-07-05T11:20:29Z"}],"graph_snapshots":[{"event_id":"sha256:962f7cd22f9e2a66e563189e049a677492f1f4beea3a0804da9b980c7c1d6bac","target":"graph","created_at":"2026-07-05T11:20:29Z","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/2506.10716/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large reasoning models (LRMs) such as Claude 3.7 Sonnet and OpenAI o1 achieve strong performance on mathematical benchmarks using lengthy chain-of-thought (CoT) reasoning, but the resulting traces are often unnecessarily verbose. This inflates token usage and cost, limiting deployment in latency-sensitive or API-constrained settings. We introduce PREMISE (PRompt-based Efficient Mathematical Inference with Strategic Evaluation), a prompt-only framework that reduces reasoning overhead without modifying model weights. PREMISE combines trace-level diagnostics with gradient-inspired prompt optimiza","authors_text":"Haohan Wang, Yaoning Yu, Ye Yu","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-12T14:05:09Z","title":"PREMISE: Scalable and Strategic Prompt Optimization for Efficient Mathematical Reasoning in Large Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.10716","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:eca16a657ad198b18ef2e659c6561aeaa9669d45bc6c9c0258457744aa36cf12","target":"record","created_at":"2026-07-05T11:20:29Z","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":"ecb3b006e302b4b2510466aa847012d67b22f37921d57d14c627d872e23220ed","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-06-12T14:05:09Z","title_canon_sha256":"a481055435e4f76865a5f2f4714cf9bd4514c9d7f6d8bc8b431b9d45c134765e"},"schema_version":"1.0","source":{"id":"2506.10716","kind":"arxiv","version":1}},"canonical_sha256":"0d60c242723661d39b9d47cb49d23763a892afea0a5162a120e4c6224626b2f2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0d60c242723661d39b9d47cb49d23763a892afea0a5162a120e4c6224626b2f2","first_computed_at":"2026-07-05T11:20:29.080041Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:20:29.080041Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zaboMUig3RCWH9nqY/Sd+YzdiEaTki45l3bfO+jrenrLFtEev0eElRA2GRukFNbamNfJwi+V5vLDqtUvASvBBg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:20:29.080666Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.10716","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eca16a657ad198b18ef2e659c6561aeaa9669d45bc6c9c0258457744aa36cf12","sha256:962f7cd22f9e2a66e563189e049a677492f1f4beea3a0804da9b980c7c1d6bac"],"state_sha256":"ed71df28e263ce127770df9f569aff38428f00acced9876022ce863487839682"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E1zBRVmoTeGGaWgEuHeWkT0dudEkcu8IaUhJ0gRMMqGgES4No0OIvXDXN/yV7N/RBQB/22QO3fk7iDTeWGDWBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T17:04:02.519363Z","bundle_sha256":"24bc2e80909fa1e291fcc1e8797c232969462c455c3e44c7522db3d7a946c97b"}}