{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:HBE2GPYFAJ5XDJVIT4XKA64ADC","short_pith_number":"pith:HBE2GPYF","canonical_record":{"source":{"id":"2505.17391","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T02:01:15Z","cross_cats_sorted":[],"title_canon_sha256":"6435c1121fb4b93d0fe24e518ae3e33839f2ed0d79bcfd651980d2f4da03f363","abstract_canon_sha256":"52b20b78c44f63c2984a34da15c2267cda215fe2224dfcf14a470a72fd127131"},"schema_version":"1.0"},"canonical_sha256":"3849a33f05027b71a6a89f2ea07b8018ba38cfeaec0f8eb6342cdf6d3e96cca8","source":{"kind":"arxiv","id":"2505.17391","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17391","created_at":"2026-07-05T11:08:25Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17391v1","created_at":"2026-07-05T11:08:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17391","created_at":"2026-07-05T11:08:25Z"},{"alias_kind":"pith_short_12","alias_value":"HBE2GPYFAJ5X","created_at":"2026-07-05T11:08:25Z"},{"alias_kind":"pith_short_16","alias_value":"HBE2GPYFAJ5XDJVI","created_at":"2026-07-05T11:08:25Z"},{"alias_kind":"pith_short_8","alias_value":"HBE2GPYF","created_at":"2026-07-05T11:08:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:HBE2GPYFAJ5XDJVIT4XKA64ADC","target":"record","payload":{"canonical_record":{"source":{"id":"2505.17391","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T02:01:15Z","cross_cats_sorted":[],"title_canon_sha256":"6435c1121fb4b93d0fe24e518ae3e33839f2ed0d79bcfd651980d2f4da03f363","abstract_canon_sha256":"52b20b78c44f63c2984a34da15c2267cda215fe2224dfcf14a470a72fd127131"},"schema_version":"1.0"},"canonical_sha256":"3849a33f05027b71a6a89f2ea07b8018ba38cfeaec0f8eb6342cdf6d3e96cca8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:08:25.256452Z","signature_b64":"NykGJLft+WjUlpXX7MfNFIe+FR7WIfnHjiHlg8mDvCqvFRNz0htFL+JBaSX/LD55E13HdzI+47jYW8p6L21tDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3849a33f05027b71a6a89f2ea07b8018ba38cfeaec0f8eb6342cdf6d3e96cca8","last_reissued_at":"2026-07-05T11:08:25.255902Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:08:25.255902Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.17391","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":"2026-07-05T11:08:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WvVEfeXfUw3Gl5RqbbCmqF/Kt7t8kG08MkSd74/Z/P6/Z/V2rMadsPEvEONsuqS7ODCk73HqlqaAah8p4OgGBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T18:32:11.911965Z"},"content_sha256":"c857ce7abba8c6a73403fd22e3f5ac2b30e99a47f82d060d0732e28a7ee5ff51","schema_version":"1.0","event_id":"sha256:c857ce7abba8c6a73403fd22e3f5ac2b30e99a47f82d060d0732e28a7ee5ff51"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:HBE2GPYFAJ5XDJVIT4XKA64ADC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Curriculum Guided Reinforcement Learning for Efficient Multi Hop Retrieval Augmented Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Daqing He, Rui Meng, Yuelyu Ji, Zhuochun Li","submitted_at":"2025-05-23T02:01:15Z","abstract_excerpt":"Retrieval-augmented generation (RAG) grounds large language models (LLMs) in up-to-date external evidence, yet existing multi-hop RAG pipelines still issue redundant subqueries, explore too shallowly, or wander through overly long search chains. We introduce EVO-RAG, a curriculum-guided reinforcement learning framework that evolves a query-rewriting agent from broad early-stage exploration to concise late-stage refinement. EVO-RAG couples a seven-factor, step-level reward vector (covering relevance, redundancy, efficiency, and answer correctness) with a time-varying scheduler that reweights th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17391","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/2505.17391/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":"2026-07-05T11:08:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nLl5VXFIWUXDldKzLbnvXpxH/C6iBy5acT55UzduuOpeLt9RoMSAgVbWrTCcP0lczx9f3B58WGRg2uqyLhjfAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T18:32:11.912892Z"},"content_sha256":"d6d605cde7966169c34b9844550cfe0516cd336fa6e53f9df2305dc9c660d969","schema_version":"1.0","event_id":"sha256:d6d605cde7966169c34b9844550cfe0516cd336fa6e53f9df2305dc9c660d969"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HBE2GPYFAJ5XDJVIT4XKA64ADC/bundle.json","state_url":"https://pith.science/pith/HBE2GPYFAJ5XDJVIT4XKA64ADC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HBE2GPYFAJ5XDJVIT4XKA64ADC/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":"2026-08-07T18:32:11Z","links":{"resolver":"https://pith.science/pith/HBE2GPYFAJ5XDJVIT4XKA64ADC","bundle":"https://pith.science/pith/HBE2GPYFAJ5XDJVIT4XKA64ADC/bundle.json","state":"https://pith.science/pith/HBE2GPYFAJ5XDJVIT4XKA64ADC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HBE2GPYFAJ5XDJVIT4XKA64ADC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:HBE2GPYFAJ5XDJVIT4XKA64ADC","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":"52b20b78c44f63c2984a34da15c2267cda215fe2224dfcf14a470a72fd127131","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T02:01:15Z","title_canon_sha256":"6435c1121fb4b93d0fe24e518ae3e33839f2ed0d79bcfd651980d2f4da03f363"},"schema_version":"1.0","source":{"id":"2505.17391","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17391","created_at":"2026-07-05T11:08:25Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17391v1","created_at":"2026-07-05T11:08:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17391","created_at":"2026-07-05T11:08:25Z"},{"alias_kind":"pith_short_12","alias_value":"HBE2GPYFAJ5X","created_at":"2026-07-05T11:08:25Z"},{"alias_kind":"pith_short_16","alias_value":"HBE2GPYFAJ5XDJVI","created_at":"2026-07-05T11:08:25Z"},{"alias_kind":"pith_short_8","alias_value":"HBE2GPYF","created_at":"2026-07-05T11:08:25Z"}],"graph_snapshots":[{"event_id":"sha256:d6d605cde7966169c34b9844550cfe0516cd336fa6e53f9df2305dc9c660d969","target":"graph","created_at":"2026-07-05T11:08:25Z","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/2505.17391/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Retrieval-augmented generation (RAG) grounds large language models (LLMs) in up-to-date external evidence, yet existing multi-hop RAG pipelines still issue redundant subqueries, explore too shallowly, or wander through overly long search chains. We introduce EVO-RAG, a curriculum-guided reinforcement learning framework that evolves a query-rewriting agent from broad early-stage exploration to concise late-stage refinement. EVO-RAG couples a seven-factor, step-level reward vector (covering relevance, redundancy, efficiency, and answer correctness) with a time-varying scheduler that reweights th","authors_text":"Daqing He, Rui Meng, Yuelyu Ji, Zhuochun Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T02:01:15Z","title":"Curriculum Guided Reinforcement Learning for Efficient Multi Hop Retrieval Augmented Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17391","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:c857ce7abba8c6a73403fd22e3f5ac2b30e99a47f82d060d0732e28a7ee5ff51","target":"record","created_at":"2026-07-05T11:08:25Z","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":"52b20b78c44f63c2984a34da15c2267cda215fe2224dfcf14a470a72fd127131","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-05-23T02:01:15Z","title_canon_sha256":"6435c1121fb4b93d0fe24e518ae3e33839f2ed0d79bcfd651980d2f4da03f363"},"schema_version":"1.0","source":{"id":"2505.17391","kind":"arxiv","version":1}},"canonical_sha256":"3849a33f05027b71a6a89f2ea07b8018ba38cfeaec0f8eb6342cdf6d3e96cca8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3849a33f05027b71a6a89f2ea07b8018ba38cfeaec0f8eb6342cdf6d3e96cca8","first_computed_at":"2026-07-05T11:08:25.255902Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:08:25.255902Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NykGJLft+WjUlpXX7MfNFIe+FR7WIfnHjiHlg8mDvCqvFRNz0htFL+JBaSX/LD55E13HdzI+47jYW8p6L21tDA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:08:25.256452Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.17391","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c857ce7abba8c6a73403fd22e3f5ac2b30e99a47f82d060d0732e28a7ee5ff51","sha256:d6d605cde7966169c34b9844550cfe0516cd336fa6e53f9df2305dc9c660d969"],"state_sha256":"95174899411ae4934cb00049c4d2ddff76adb6f0f52111d257bff2b389992d0c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+23Jh4jpO0CaXR7mYSKkB9m84gYz3rCHRiq6LDdgAMkJ46RglukdEN1Pku7KNr3b6wPa5tK/IP3hAT4Gy3OYBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T18:32:11.924549Z","bundle_sha256":"b8f7f74de34699b228df7271d2252364c0fbdf7a77365b96cce5ceac8add0889"}}