{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:C7N6GA4XTEK32GLJWSGABXBDWA","short_pith_number":"pith:C7N6GA4X","canonical_record":{"source":{"id":"2607.28982","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-07-31T03:20:14Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3e86d348fd0be0c4de9265cc74bbbfafcd39e47a214c98a5f0f93e1c4c3029eb","abstract_canon_sha256":"5815b7f2ee8a5f345946abcbff96c327ef97fc48b92ced67135bfb25b0f343c2"},"schema_version":"1.0"},"canonical_sha256":"17dbe303979915bd1969b48c00dc23b03438e133fcb5364828abcefcfa8ee4a8","source":{"kind":"arxiv","id":"2607.28982","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.28982","created_at":"2026-08-03T01:17:51Z"},{"alias_kind":"arxiv_version","alias_value":"2607.28982v1","created_at":"2026-08-03T01:17:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.28982","created_at":"2026-08-03T01:17:51Z"},{"alias_kind":"pith_short_12","alias_value":"C7N6GA4XTEK3","created_at":"2026-08-03T01:17:51Z"},{"alias_kind":"pith_short_16","alias_value":"C7N6GA4XTEK32GLJ","created_at":"2026-08-03T01:17:51Z"},{"alias_kind":"pith_short_8","alias_value":"C7N6GA4X","created_at":"2026-08-03T01:17:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:C7N6GA4XTEK32GLJWSGABXBDWA","target":"record","payload":{"canonical_record":{"source":{"id":"2607.28982","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-07-31T03:20:14Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"3e86d348fd0be0c4de9265cc74bbbfafcd39e47a214c98a5f0f93e1c4c3029eb","abstract_canon_sha256":"5815b7f2ee8a5f345946abcbff96c327ef97fc48b92ced67135bfb25b0f343c2"},"schema_version":"1.0"},"canonical_sha256":"17dbe303979915bd1969b48c00dc23b03438e133fcb5364828abcefcfa8ee4a8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-03T01:17:51.389793Z","signature_b64":"LP1loEOmRGmT6behUit13P5BIPWO3vIO9ai+DVnLetRZENq4Ta7dXf7kxkNsV6PpjI9ftiGcR4Ibqf6ihRvfBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17dbe303979915bd1969b48c00dc23b03438e133fcb5364828abcefcfa8ee4a8","last_reissued_at":"2026-08-03T01:17:51.388240Z","signature_status":"signed_v1","first_computed_at":"2026-08-03T01:17:51.388240Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.28982","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":"2026-08-03T01:17:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qQCGQuhEecXCnPFVUJscPa2HdOf9CCMkWeIESnMK/O7Tg5R3B9H3v5vdmmfAn60xo5BPdY2tlEzKYtFqTSoRBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T04:20:17.095041Z"},"content_sha256":"b812aaebd4d26bd5e33bb197e723339bc6f703c4019fb11ddec4574c89c1334a","schema_version":"1.0","event_id":"sha256:b812aaebd4d26bd5e33bb197e723339bc6f703c4019fb11ddec4574c89c1334a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:C7N6GA4XTEK32GLJWSGABXBDWA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PARALLEL: A Prefrontal-Aligned Reinforcement inspired Approach for Language-Model Learning under Explicit Limits","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Hwangnam Kim, Namkyung Yoon, Sanghong Kim","submitted_at":"2026-07-31T03:20:14Z","abstract_excerpt":"Recent language models achieve strong performance across a variety of tasks, but conventional adaptation applies updates uniformly across training samples regardless of their local update benefit. We propose PARALLEL, a prefrontal-aligned reinforcement inspired approach for language-model learning. Inspired by the complementary roles of goal-related and uncertainty-related control, PARALLEL represents these forms of information as separate controller signals and combines them with the current model representation. A reinforcement-inspired controller assigns sample-dependent update intensity us"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.28982","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/2607.28982/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":"2026-08-03T01:17:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PBURivj9g6PNfJEkzFjmYy1Xwyox+vxQv/LZkQvJ7mcvGmWQYGc/DeWPR78/Dvpbvu7hI9ax2lMxYT1XR56ZAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-11T04:20:17.095540Z"},"content_sha256":"a0941a9eb004678b346cd738a06040d65ba4ff041e8e5aa4e5e9ce111ac1a369","schema_version":"1.0","event_id":"sha256:a0941a9eb004678b346cd738a06040d65ba4ff041e8e5aa4e5e9ce111ac1a369"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C7N6GA4XTEK32GLJWSGABXBDWA/bundle.json","state_url":"https://pith.science/pith/C7N6GA4XTEK32GLJWSGABXBDWA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C7N6GA4XTEK32GLJWSGABXBDWA/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":"2026-08-11T04:20:17Z","links":{"resolver":"https://pith.science/pith/C7N6GA4XTEK32GLJWSGABXBDWA","bundle":"https://pith.science/pith/C7N6GA4XTEK32GLJWSGABXBDWA/bundle.json","state":"https://pith.science/pith/C7N6GA4XTEK32GLJWSGABXBDWA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C7N6GA4XTEK32GLJWSGABXBDWA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:C7N6GA4XTEK32GLJWSGABXBDWA","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":"5815b7f2ee8a5f345946abcbff96c327ef97fc48b92ced67135bfb25b0f343c2","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-07-31T03:20:14Z","title_canon_sha256":"3e86d348fd0be0c4de9265cc74bbbfafcd39e47a214c98a5f0f93e1c4c3029eb"},"schema_version":"1.0","source":{"id":"2607.28982","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.28982","created_at":"2026-08-03T01:17:51Z"},{"alias_kind":"arxiv_version","alias_value":"2607.28982v1","created_at":"2026-08-03T01:17:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.28982","created_at":"2026-08-03T01:17:51Z"},{"alias_kind":"pith_short_12","alias_value":"C7N6GA4XTEK3","created_at":"2026-08-03T01:17:51Z"},{"alias_kind":"pith_short_16","alias_value":"C7N6GA4XTEK32GLJ","created_at":"2026-08-03T01:17:51Z"},{"alias_kind":"pith_short_8","alias_value":"C7N6GA4X","created_at":"2026-08-03T01:17:51Z"}],"graph_snapshots":[{"event_id":"sha256:a0941a9eb004678b346cd738a06040d65ba4ff041e8e5aa4e5e9ce111ac1a369","target":"graph","created_at":"2026-08-03T01:17:51Z","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/2607.28982/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent language models achieve strong performance across a variety of tasks, but conventional adaptation applies updates uniformly across training samples regardless of their local update benefit. We propose PARALLEL, a prefrontal-aligned reinforcement inspired approach for language-model learning. Inspired by the complementary roles of goal-related and uncertainty-related control, PARALLEL represents these forms of information as separate controller signals and combines them with the current model representation. A reinforcement-inspired controller assigns sample-dependent update intensity us","authors_text":"Hwangnam Kim, Namkyung Yoon, Sanghong Kim","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-07-31T03:20:14Z","title":"PARALLEL: A Prefrontal-Aligned Reinforcement inspired Approach for Language-Model Learning under Explicit Limits"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.28982","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:b812aaebd4d26bd5e33bb197e723339bc6f703c4019fb11ddec4574c89c1334a","target":"record","created_at":"2026-08-03T01:17:51Z","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":"5815b7f2ee8a5f345946abcbff96c327ef97fc48b92ced67135bfb25b0f343c2","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2026-07-31T03:20:14Z","title_canon_sha256":"3e86d348fd0be0c4de9265cc74bbbfafcd39e47a214c98a5f0f93e1c4c3029eb"},"schema_version":"1.0","source":{"id":"2607.28982","kind":"arxiv","version":1}},"canonical_sha256":"17dbe303979915bd1969b48c00dc23b03438e133fcb5364828abcefcfa8ee4a8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"17dbe303979915bd1969b48c00dc23b03438e133fcb5364828abcefcfa8ee4a8","first_computed_at":"2026-08-03T01:17:51.388240Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-03T01:17:51.388240Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LP1loEOmRGmT6behUit13P5BIPWO3vIO9ai+DVnLetRZENq4Ta7dXf7kxkNsV6PpjI9ftiGcR4Ibqf6ihRvfBw==","signature_status":"signed_v1","signed_at":"2026-08-03T01:17:51.389793Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.28982","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b812aaebd4d26bd5e33bb197e723339bc6f703c4019fb11ddec4574c89c1334a","sha256:a0941a9eb004678b346cd738a06040d65ba4ff041e8e5aa4e5e9ce111ac1a369"],"state_sha256":"f5a1de7f485ef82e3410d3c2967c83583f4467961a4d4b81e20d724f05bf26ef"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Kk+aw/nAoKPdLBP4a0MNqAoNEzTakuG4xd7Ofi5aXBnGeqkZR46kkGdgxs6t2OAlzMMcI1nunMBTlzrLrmzCBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-11T04:20:17.099429Z","bundle_sha256":"64cba48ef403f22c4fdcbcfb13a63edbfc73c92d1d36b584ff3409ff0f732cb5"}}