{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:NLRRMPO23QNLGG7TN7LMYFA7FE","short_pith_number":"pith:NLRRMPO2","canonical_record":{"source":{"id":"2607.04395","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-05T16:37:41Z","cross_cats_sorted":[],"title_canon_sha256":"f573326786dd3692d89f329ef3d52d2683a56aaba40053b55f7bd8b356c87ef7","abstract_canon_sha256":"d6853656eec4075f62783fca30134f0117602aabfc6d9aa3f99a61f16659f788"},"schema_version":"1.0"},"canonical_sha256":"6ae3163ddadc1ab31bf36fd6cc141f29315c418262543a824bd670e870766cc9","source":{"kind":"arxiv","id":"2607.04395","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.04395","created_at":"2026-07-07T02:19:16Z"},{"alias_kind":"arxiv_version","alias_value":"2607.04395v1","created_at":"2026-07-07T02:19:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.04395","created_at":"2026-07-07T02:19:16Z"},{"alias_kind":"pith_short_12","alias_value":"NLRRMPO23QNL","created_at":"2026-07-07T02:19:16Z"},{"alias_kind":"pith_short_16","alias_value":"NLRRMPO23QNLGG7T","created_at":"2026-07-07T02:19:16Z"},{"alias_kind":"pith_short_8","alias_value":"NLRRMPO2","created_at":"2026-07-07T02:19:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:NLRRMPO23QNLGG7TN7LMYFA7FE","target":"record","payload":{"canonical_record":{"source":{"id":"2607.04395","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-05T16:37:41Z","cross_cats_sorted":[],"title_canon_sha256":"f573326786dd3692d89f329ef3d52d2683a56aaba40053b55f7bd8b356c87ef7","abstract_canon_sha256":"d6853656eec4075f62783fca30134f0117602aabfc6d9aa3f99a61f16659f788"},"schema_version":"1.0"},"canonical_sha256":"6ae3163ddadc1ab31bf36fd6cc141f29315c418262543a824bd670e870766cc9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-07T02:19:16.439716Z","signature_b64":"axfvJNLBQKX2URADLUM4NBvohHx5EQGss1A3eZF+gOBb9bRqLCmyli+3djQR20XK6973eyTE6xWhcSmGhy6pAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6ae3163ddadc1ab31bf36fd6cc141f29315c418262543a824bd670e870766cc9","last_reissued_at":"2026-07-07T02:19:16.439019Z","signature_status":"signed_v1","first_computed_at":"2026-07-07T02:19:16.439019Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.04395","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":"2026-07-07T02:19:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"y1/hrcEANS9ZYoEfQ7VwFd4bcWzQYwQRMtzlydnA9tx5by9TbSdtfuGWr9hOfpVOErllFyBVeqXHT2Q/MXEhBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T03:29:27.598782Z"},"content_sha256":"0547557d02cb6b9d34116b92855cd6ec3717b190ab988a78091cb332e4836b25","schema_version":"1.0","event_id":"sha256:0547557d02cb6b9d34116b92855cd6ec3717b190ab988a78091cb332e4836b25"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:NLRRMPO23QNLGG7TN7LMYFA7FE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NKI-Agent: Domain-Specific Fine-Tuning and Agentic Tool Use for Neuron Kernel Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Hao Zhou, Jun Huan, Junjie Tang, Lin Wang, Yuhao Zhang","submitted_at":"2026-07-05T16:37:41Z","abstract_excerpt":"Recent agentic approaches to LLM-based kernel generation have achieved impressive results on CUDA. For emerging AI accelerators such as AWS Trainium and Inferentia, automated kernel generation and optimization remain largely unaddressed. Writing kernels for these chips via the Neuron Kernel Interface (NKI) is particularly challenging: developers must navigate a multi-engine architecture, tile-based programming, and explicit data movement across multi-level memory hierarchy. Moreover, no publicly-available training data, benchmarks, or tool-augmented agents exist for this domain. We introduce N"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.04395","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/2607.04395/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":"2026-07-07T02:19:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IHdlFChg+0EJOxMR4dwEQzWfd9P43B6DnJ1KQc/DOpqry0VBqazLc116DEQvktjaGF5vfH7dv2DinedjBlilDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T03:29:27.599426Z"},"content_sha256":"a3b22a2b797af424a57d4264d188502ac82e4f7f1186b61a02b9d10683bd5ebd","schema_version":"1.0","event_id":"sha256:a3b22a2b797af424a57d4264d188502ac82e4f7f1186b61a02b9d10683bd5ebd"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NLRRMPO23QNLGG7TN7LMYFA7FE/bundle.json","state_url":"https://pith.science/pith/NLRRMPO23QNLGG7TN7LMYFA7FE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NLRRMPO23QNLGG7TN7LMYFA7FE/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":"2026-08-19T03:29:27Z","links":{"resolver":"https://pith.science/pith/NLRRMPO23QNLGG7TN7LMYFA7FE","bundle":"https://pith.science/pith/NLRRMPO23QNLGG7TN7LMYFA7FE/bundle.json","state":"https://pith.science/pith/NLRRMPO23QNLGG7TN7LMYFA7FE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NLRRMPO23QNLGG7TN7LMYFA7FE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:NLRRMPO23QNLGG7TN7LMYFA7FE","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":"d6853656eec4075f62783fca30134f0117602aabfc6d9aa3f99a61f16659f788","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-05T16:37:41Z","title_canon_sha256":"f573326786dd3692d89f329ef3d52d2683a56aaba40053b55f7bd8b356c87ef7"},"schema_version":"1.0","source":{"id":"2607.04395","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.04395","created_at":"2026-07-07T02:19:16Z"},{"alias_kind":"arxiv_version","alias_value":"2607.04395v1","created_at":"2026-07-07T02:19:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.04395","created_at":"2026-07-07T02:19:16Z"},{"alias_kind":"pith_short_12","alias_value":"NLRRMPO23QNL","created_at":"2026-07-07T02:19:16Z"},{"alias_kind":"pith_short_16","alias_value":"NLRRMPO23QNLGG7T","created_at":"2026-07-07T02:19:16Z"},{"alias_kind":"pith_short_8","alias_value":"NLRRMPO2","created_at":"2026-07-07T02:19:16Z"}],"graph_snapshots":[{"event_id":"sha256:a3b22a2b797af424a57d4264d188502ac82e4f7f1186b61a02b9d10683bd5ebd","target":"graph","created_at":"2026-07-07T02:19:16Z","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/2607.04395/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent agentic approaches to LLM-based kernel generation have achieved impressive results on CUDA. For emerging AI accelerators such as AWS Trainium and Inferentia, automated kernel generation and optimization remain largely unaddressed. Writing kernels for these chips via the Neuron Kernel Interface (NKI) is particularly challenging: developers must navigate a multi-engine architecture, tile-based programming, and explicit data movement across multi-level memory hierarchy. Moreover, no publicly-available training data, benchmarks, or tool-augmented agents exist for this domain. We introduce N","authors_text":"Hao Zhou, Jun Huan, Junjie Tang, Lin Wang, Yuhao Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-05T16:37:41Z","title":"NKI-Agent: Domain-Specific Fine-Tuning and Agentic Tool Use for Neuron Kernel Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.04395","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":"sha256:0547557d02cb6b9d34116b92855cd6ec3717b190ab988a78091cb332e4836b25","target":"record","created_at":"2026-07-07T02:19:16Z","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":"d6853656eec4075f62783fca30134f0117602aabfc6d9aa3f99a61f16659f788","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-05T16:37:41Z","title_canon_sha256":"f573326786dd3692d89f329ef3d52d2683a56aaba40053b55f7bd8b356c87ef7"},"schema_version":"1.0","source":{"id":"2607.04395","kind":"arxiv","version":1}},"canonical_sha256":"6ae3163ddadc1ab31bf36fd6cc141f29315c418262543a824bd670e870766cc9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6ae3163ddadc1ab31bf36fd6cc141f29315c418262543a824bd670e870766cc9","first_computed_at":"2026-07-07T02:19:16.439019Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-07T02:19:16.439019Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"axfvJNLBQKX2URADLUM4NBvohHx5EQGss1A3eZF+gOBb9bRqLCmyli+3djQR20XK6973eyTE6xWhcSmGhy6pAA==","signature_status":"signed_v1","signed_at":"2026-07-07T02:19:16.439716Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.04395","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0547557d02cb6b9d34116b92855cd6ec3717b190ab988a78091cb332e4836b25","sha256:a3b22a2b797af424a57d4264d188502ac82e4f7f1186b61a02b9d10683bd5ebd"],"state_sha256":"4c4eed1a9e5f0727e56db80153ff2ae5fd63660306a600cf849fb5b4a572a8ff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"imqLAMpyb16TZDS9NzLwb3ZmqkJFB0shLveeCBJnHjivw5MXdlL2rvJqAG/zqozOy8HCHt+zAWzPLI/ytLfKBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T03:29:27.603530Z","bundle_sha256":"de3f5d7d0261f5815fbbd062f3f784d316cd323b6b0ecfde5c4d11cca278d522"}}