{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:AON34PKGWAHTPVGCJGLKPEBR7T","short_pith_number":"pith:AON34PKG","canonical_record":{"source":{"id":"2608.00030","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-15T11:11:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e1688148281f7511ff36883196b3324ddd2fbdf35524c58b12cf36588cbebffa","abstract_canon_sha256":"952367391fd7e4671a0f2edd8b1f6f9ce45e8377ec48e0250c4fd9213e1eaaa2"},"schema_version":"1.0"},"canonical_sha256":"039bbe3d46b00f37d4c24996a79031fcf73614608fa6353ccb3ac59f81b449dc","source":{"kind":"arxiv","id":"2608.00030","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.00030","created_at":"2026-08-04T00:31:48Z"},{"alias_kind":"arxiv_version","alias_value":"2608.00030v1","created_at":"2026-08-04T00:31:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.00030","created_at":"2026-08-04T00:31:48Z"},{"alias_kind":"pith_short_12","alias_value":"AON34PKGWAHT","created_at":"2026-08-04T00:31:48Z"},{"alias_kind":"pith_short_16","alias_value":"AON34PKGWAHTPVGC","created_at":"2026-08-04T00:31:48Z"},{"alias_kind":"pith_short_8","alias_value":"AON34PKG","created_at":"2026-08-04T00:31:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:AON34PKGWAHTPVGCJGLKPEBR7T","target":"record","payload":{"canonical_record":{"source":{"id":"2608.00030","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-15T11:11:39Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"e1688148281f7511ff36883196b3324ddd2fbdf35524c58b12cf36588cbebffa","abstract_canon_sha256":"952367391fd7e4671a0f2edd8b1f6f9ce45e8377ec48e0250c4fd9213e1eaaa2"},"schema_version":"1.0"},"canonical_sha256":"039bbe3d46b00f37d4c24996a79031fcf73614608fa6353ccb3ac59f81b449dc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-04T00:31:48.494839Z","signature_b64":"oxl6l4bZDlxTddndk+AY3CganluIDmEw1w5TQSXXKnvltsaHCyWi0fCK8mjdfWHPJqV1fYZUCLB5RbKdppTjDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"039bbe3d46b00f37d4c24996a79031fcf73614608fa6353ccb3ac59f81b449dc","last_reissued_at":"2026-08-04T00:31:48.493446Z","signature_status":"signed_v1","first_computed_at":"2026-08-04T00:31:48.493446Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.00030","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":"2026-08-04T00:31:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZztZX10iLcGGCeNitiP4RCuvZJ8bcMv7qJUyhRNotyrocTKPck+6OUxdJXJUM+WHsHlIHTMmB+vCKsPq+PSeAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:15:29.653412Z"},"content_sha256":"3a3965352ffd6f8418f291a0840e9a6102109a6e7666a44eb89fddc3cb25fbe7","schema_version":"1.0","event_id":"sha256:3a3965352ffd6f8418f291a0840e9a6102109a6e7666a44eb89fddc3cb25fbe7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:AON34PKGWAHTPVGCJGLKPEBR7T","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SLMs as Multi-Agent Routers: A Progressive SFT and Reinforcement Learning Approach","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Alexander Ng, Amir Kayhani, Gayathri V Kondapalli, Harvey Yorke, Hirsh Pithadia, Rahul Monish","submitted_at":"2026-07-15T11:11:39Z","abstract_excerpt":"Specialised retrieval agents typically surface higher quality results than general-purpose search, but selecting the optimal agent for a given query remains an open problem. Current approaches route queries based on inferred topic or intent, however intent-based selection is fundamentally limited: it does not incorporate signal from retrieved content, and cannot detect when a topically aligned agent produces low-relevance results. We address this by training a small language model via supervised fine-tuning followed by reinforcement learning to jointly perform agent selection and structured pa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.00030","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/2608.00030/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":"2026-08-04T00:31:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iZsv2GhU9CzLtzNDqy29O7JotYApbD4V0Htw0uHKS0blGLeNw7Vxvo+cHzhxDZNR4hgshP3x5c5uMvYVDq1GDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T10:15:29.653902Z"},"content_sha256":"cc2e983985d2a2948598c1b44969ee76a65602a6625f06f3dd797cc93a894bae","schema_version":"1.0","event_id":"sha256:cc2e983985d2a2948598c1b44969ee76a65602a6625f06f3dd797cc93a894bae"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AON34PKGWAHTPVGCJGLKPEBR7T/bundle.json","state_url":"https://pith.science/pith/AON34PKGWAHTPVGCJGLKPEBR7T/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AON34PKGWAHTPVGCJGLKPEBR7T/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":"2026-08-04T10:15:29Z","links":{"resolver":"https://pith.science/pith/AON34PKGWAHTPVGCJGLKPEBR7T","bundle":"https://pith.science/pith/AON34PKGWAHTPVGCJGLKPEBR7T/bundle.json","state":"https://pith.science/pith/AON34PKGWAHTPVGCJGLKPEBR7T/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AON34PKGWAHTPVGCJGLKPEBR7T/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:AON34PKGWAHTPVGCJGLKPEBR7T","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":"952367391fd7e4671a0f2edd8b1f6f9ce45e8377ec48e0250c4fd9213e1eaaa2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-15T11:11:39Z","title_canon_sha256":"e1688148281f7511ff36883196b3324ddd2fbdf35524c58b12cf36588cbebffa"},"schema_version":"1.0","source":{"id":"2608.00030","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.00030","created_at":"2026-08-04T00:31:48Z"},{"alias_kind":"arxiv_version","alias_value":"2608.00030v1","created_at":"2026-08-04T00:31:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.00030","created_at":"2026-08-04T00:31:48Z"},{"alias_kind":"pith_short_12","alias_value":"AON34PKGWAHT","created_at":"2026-08-04T00:31:48Z"},{"alias_kind":"pith_short_16","alias_value":"AON34PKGWAHTPVGC","created_at":"2026-08-04T00:31:48Z"},{"alias_kind":"pith_short_8","alias_value":"AON34PKG","created_at":"2026-08-04T00:31:48Z"}],"graph_snapshots":[{"event_id":"sha256:cc2e983985d2a2948598c1b44969ee76a65602a6625f06f3dd797cc93a894bae","target":"graph","created_at":"2026-08-04T00:31:48Z","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/2608.00030/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Specialised retrieval agents typically surface higher quality results than general-purpose search, but selecting the optimal agent for a given query remains an open problem. Current approaches route queries based on inferred topic or intent, however intent-based selection is fundamentally limited: it does not incorporate signal from retrieved content, and cannot detect when a topically aligned agent produces low-relevance results. We address this by training a small language model via supervised fine-tuning followed by reinforcement learning to jointly perform agent selection and structured pa","authors_text":"Alexander Ng, Amir Kayhani, Gayathri V Kondapalli, Harvey Yorke, Hirsh Pithadia, Rahul Monish","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-15T11:11:39Z","title":"SLMs as Multi-Agent Routers: A Progressive SFT and Reinforcement Learning Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.00030","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":"sha256:3a3965352ffd6f8418f291a0840e9a6102109a6e7666a44eb89fddc3cb25fbe7","target":"record","created_at":"2026-08-04T00:31:48Z","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":"952367391fd7e4671a0f2edd8b1f6f9ce45e8377ec48e0250c4fd9213e1eaaa2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-15T11:11:39Z","title_canon_sha256":"e1688148281f7511ff36883196b3324ddd2fbdf35524c58b12cf36588cbebffa"},"schema_version":"1.0","source":{"id":"2608.00030","kind":"arxiv","version":1}},"canonical_sha256":"039bbe3d46b00f37d4c24996a79031fcf73614608fa6353ccb3ac59f81b449dc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"039bbe3d46b00f37d4c24996a79031fcf73614608fa6353ccb3ac59f81b449dc","first_computed_at":"2026-08-04T00:31:48.493446Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-04T00:31:48.493446Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oxl6l4bZDlxTddndk+AY3CganluIDmEw1w5TQSXXKnvltsaHCyWi0fCK8mjdfWHPJqV1fYZUCLB5RbKdppTjDg==","signature_status":"signed_v1","signed_at":"2026-08-04T00:31:48.494839Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.00030","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3a3965352ffd6f8418f291a0840e9a6102109a6e7666a44eb89fddc3cb25fbe7","sha256:cc2e983985d2a2948598c1b44969ee76a65602a6625f06f3dd797cc93a894bae"],"state_sha256":"1f6652d63b977a9795ab2603bb766c655ede8d5603412194430e66dcd72fb5ae"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZT5MAWqe2EI4ViqsZBfTMPk77X6wLVcl4gHam/ATLzyzYoJ0dA3J8a/FbDEBs7dCk+TOiWhJZWjBvPkipuyjCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T10:15:29.657879Z","bundle_sha256":"5981cae11afadca902f91f1d8427611c3115bc1d5586304849a915497d6b3032"}}