{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:B5UXBQDERXSXAOAFODSU4Y4D2I","short_pith_number":"pith:B5UXBQDE","canonical_record":{"source":{"id":"2605.19782","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-19T12:48:48Z","cross_cats_sorted":["cs.LG","cs.SE"],"title_canon_sha256":"03c6472bf332ffe596ab7c92627f167fd1ddc5b446e66e27a4bd9fd391e7b272","abstract_canon_sha256":"9deecfcdc5f4ef2fc3b2ccc4d04431d11b85245371549ef7a3024090484f4ffa"},"schema_version":"1.0"},"canonical_sha256":"0f6970c0648de570380570e54e6383d212fa36479ea354493cb3c424ac2fb57a","source":{"kind":"arxiv","id":"2605.19782","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.19782","created_at":"2026-05-20T01:06:13Z"},{"alias_kind":"arxiv_version","alias_value":"2605.19782v1","created_at":"2026-05-20T01:06:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19782","created_at":"2026-05-20T01:06:13Z"},{"alias_kind":"pith_short_12","alias_value":"B5UXBQDERXSX","created_at":"2026-05-20T01:06:13Z"},{"alias_kind":"pith_short_16","alias_value":"B5UXBQDERXSXAOAF","created_at":"2026-05-20T01:06:13Z"},{"alias_kind":"pith_short_8","alias_value":"B5UXBQDE","created_at":"2026-05-20T01:06:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:B5UXBQDERXSXAOAFODSU4Y4D2I","target":"record","payload":{"canonical_record":{"source":{"id":"2605.19782","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-19T12:48:48Z","cross_cats_sorted":["cs.LG","cs.SE"],"title_canon_sha256":"03c6472bf332ffe596ab7c92627f167fd1ddc5b446e66e27a4bd9fd391e7b272","abstract_canon_sha256":"9deecfcdc5f4ef2fc3b2ccc4d04431d11b85245371549ef7a3024090484f4ffa"},"schema_version":"1.0"},"canonical_sha256":"0f6970c0648de570380570e54e6383d212fa36479ea354493cb3c424ac2fb57a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T01:06:13.823976Z","signature_b64":"nNVl7ES8WnuWLGDdxwihgOwDN/eCQSUWzDPROU3g+lphZaJRwFkvwdDlCUCcfh1dnAJFt3yk9VnH8klnpxhiBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0f6970c0648de570380570e54e6383d212fa36479ea354493cb3c424ac2fb57a","last_reissued_at":"2026-05-20T01:06:13.823065Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T01:06:13.823065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.19782","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":"2026-05-20T01:06:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wiHZsq+4yqEh76Xcfk1sbSeZDO9L4lorBeDjCMww0p40LegE1yeL5vCK5VBHm597GZiZ1BLNc3EeMt4Hezn6AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T12:53:53.105850Z"},"content_sha256":"b12aad8acd24062ca428900d9c18b8ed773f7f0e860cbc6660d863fd5c50799b","schema_version":"1.0","event_id":"sha256:b12aad8acd24062ca428900d9c18b8ed773f7f0e860cbc6660d863fd5c50799b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:B5UXBQDERXSXAOAFODSU4Y4D2I","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Prior Knowledge or Search? A Study of LLM Agents in Hardware-Aware Code Optimization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","cs.SE"],"primary_cat":"cs.AI","authors_text":"1), (2) AI Talent Hub, (3) YSDA), Albert Fazlyev (2), Dmitry Redko (1), Egor Shvetsov (1) ((1) Applied AI Institute, Evgeny Burnaev (1), ITMO University, Konstantin Sozykin (1), Maria Ivanova (3","submitted_at":"2026-05-19T12:48:48Z","abstract_excerpt":"LLM discovery and optimization systems are increasingly applied across domains, implementing a common propose-evaluate-revise loop. Such optimization or discovery progresses via context conditioning on received feedback from an environment. However, as modern LLM agents are increasingly complex in their structure, it is difficult to evaluate which components contribute the most, and when and how this exploration may fail. We answer these questions through three controlled experiments. Our findings: (1) In pure black-box optimization, LLMs act as greedy optimizers. (2) In zero-shot kernel gener"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19782","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/2605.19782/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":"2026-05-20T01:06:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RiuvBMWZcyQP2wbngdjthjsTZWHRuoZf8db3fUr594pWXxaQ55+jNpasTYwVPM2msDF90JEct2wevL8Zf4LkBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T12:53:53.106650Z"},"content_sha256":"24a9b3a20e57fc4f755b692c5d9c8769eca93eeb4995647dd5da44b37022f4e8","schema_version":"1.0","event_id":"sha256:24a9b3a20e57fc4f755b692c5d9c8769eca93eeb4995647dd5da44b37022f4e8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/B5UXBQDERXSXAOAFODSU4Y4D2I/bundle.json","state_url":"https://pith.science/pith/B5UXBQDERXSXAOAFODSU4Y4D2I/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/B5UXBQDERXSXAOAFODSU4Y4D2I/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":"2026-05-23T12:53:53Z","links":{"resolver":"https://pith.science/pith/B5UXBQDERXSXAOAFODSU4Y4D2I","bundle":"https://pith.science/pith/B5UXBQDERXSXAOAFODSU4Y4D2I/bundle.json","state":"https://pith.science/pith/B5UXBQDERXSXAOAFODSU4Y4D2I/state.json","well_known_bundle":"https://pith.science/.well-known/pith/B5UXBQDERXSXAOAFODSU4Y4D2I/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:B5UXBQDERXSXAOAFODSU4Y4D2I","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":"9deecfcdc5f4ef2fc3b2ccc4d04431d11b85245371549ef7a3024090484f4ffa","cross_cats_sorted":["cs.LG","cs.SE"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-19T12:48:48Z","title_canon_sha256":"03c6472bf332ffe596ab7c92627f167fd1ddc5b446e66e27a4bd9fd391e7b272"},"schema_version":"1.0","source":{"id":"2605.19782","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.19782","created_at":"2026-05-20T01:06:13Z"},{"alias_kind":"arxiv_version","alias_value":"2605.19782v1","created_at":"2026-05-20T01:06:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.19782","created_at":"2026-05-20T01:06:13Z"},{"alias_kind":"pith_short_12","alias_value":"B5UXBQDERXSX","created_at":"2026-05-20T01:06:13Z"},{"alias_kind":"pith_short_16","alias_value":"B5UXBQDERXSXAOAF","created_at":"2026-05-20T01:06:13Z"},{"alias_kind":"pith_short_8","alias_value":"B5UXBQDE","created_at":"2026-05-20T01:06:13Z"}],"graph_snapshots":[{"event_id":"sha256:24a9b3a20e57fc4f755b692c5d9c8769eca93eeb4995647dd5da44b37022f4e8","target":"graph","created_at":"2026-05-20T01:06:13Z","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/2605.19782/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"LLM discovery and optimization systems are increasingly applied across domains, implementing a common propose-evaluate-revise loop. Such optimization or discovery progresses via context conditioning on received feedback from an environment. However, as modern LLM agents are increasingly complex in their structure, it is difficult to evaluate which components contribute the most, and when and how this exploration may fail. We answer these questions through three controlled experiments. Our findings: (1) In pure black-box optimization, LLMs act as greedy optimizers. (2) In zero-shot kernel gener","authors_text":"1), (2) AI Talent Hub, (3) YSDA), Albert Fazlyev (2), Dmitry Redko (1), Egor Shvetsov (1) ((1) Applied AI Institute, Evgeny Burnaev (1), ITMO University, Konstantin Sozykin (1), Maria Ivanova (3","cross_cats":["cs.LG","cs.SE"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-19T12:48:48Z","title":"Prior Knowledge or Search? A Study of LLM Agents in Hardware-Aware Code Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.19782","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:b12aad8acd24062ca428900d9c18b8ed773f7f0e860cbc6660d863fd5c50799b","target":"record","created_at":"2026-05-20T01:06:13Z","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":"9deecfcdc5f4ef2fc3b2ccc4d04431d11b85245371549ef7a3024090484f4ffa","cross_cats_sorted":["cs.LG","cs.SE"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-05-19T12:48:48Z","title_canon_sha256":"03c6472bf332ffe596ab7c92627f167fd1ddc5b446e66e27a4bd9fd391e7b272"},"schema_version":"1.0","source":{"id":"2605.19782","kind":"arxiv","version":1}},"canonical_sha256":"0f6970c0648de570380570e54e6383d212fa36479ea354493cb3c424ac2fb57a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0f6970c0648de570380570e54e6383d212fa36479ea354493cb3c424ac2fb57a","first_computed_at":"2026-05-20T01:06:13.823065Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T01:06:13.823065Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nNVl7ES8WnuWLGDdxwihgOwDN/eCQSUWzDPROU3g+lphZaJRwFkvwdDlCUCcfh1dnAJFt3yk9VnH8klnpxhiBg==","signature_status":"signed_v1","signed_at":"2026-05-20T01:06:13.823976Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.19782","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b12aad8acd24062ca428900d9c18b8ed773f7f0e860cbc6660d863fd5c50799b","sha256:24a9b3a20e57fc4f755b692c5d9c8769eca93eeb4995647dd5da44b37022f4e8"],"state_sha256":"f7a7e4399f10a3c53abfb853528457d1d95194a1d6c953cae9eae1451fa0c3ae"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0x8veFIMUNnGxSLE7qy7YXjFPX4r922xHoQQxTrFBM/jhVZn2bKx3qMZLfMykTK/AWQQPTJ92QKeiqogszaSCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T12:53:53.111011Z","bundle_sha256":"b853d0eead24dfc7557626fee240a7feed08d9fe03fc0737de0d7364c26d3f54"}}