{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:3FWU7W3KIAUMQMJC2H4N77DOEC","short_pith_number":"pith:3FWU7W3K","canonical_record":{"source":{"id":"2508.12800","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-08-18T10:23:10Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c90a19e9eefd45800a8a46466cb8fa1774520a4f74ae101fc553ff841afba0ae","abstract_canon_sha256":"39403b0cd8140a6699655e122f4ce3c3125fdc190b53e174bdf1de5a9df175fb"},"schema_version":"1.0"},"canonical_sha256":"d96d4fdb6a4028c83122d1f8dffc6e2092a774f7b4cb02b6acf74790da5b1013","source":{"kind":"arxiv","id":"2508.12800","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.12800","created_at":"2026-07-05T12:01:25Z"},{"alias_kind":"arxiv_version","alias_value":"2508.12800v3","created_at":"2026-07-05T12:01:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.12800","created_at":"2026-07-05T12:01:25Z"},{"alias_kind":"pith_short_12","alias_value":"3FWU7W3KIAUM","created_at":"2026-07-05T12:01:25Z"},{"alias_kind":"pith_short_16","alias_value":"3FWU7W3KIAUMQMJC","created_at":"2026-07-05T12:01:25Z"},{"alias_kind":"pith_short_8","alias_value":"3FWU7W3K","created_at":"2026-07-05T12:01:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:3FWU7W3KIAUMQMJC2H4N77DOEC","target":"record","payload":{"canonical_record":{"source":{"id":"2508.12800","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-08-18T10:23:10Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"c90a19e9eefd45800a8a46466cb8fa1774520a4f74ae101fc553ff841afba0ae","abstract_canon_sha256":"39403b0cd8140a6699655e122f4ce3c3125fdc190b53e174bdf1de5a9df175fb"},"schema_version":"1.0"},"canonical_sha256":"d96d4fdb6a4028c83122d1f8dffc6e2092a774f7b4cb02b6acf74790da5b1013","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:01:25.687390Z","signature_b64":"YKG0pyPDfph2T6+WFQ04oTjfhsjNjQGpT2JD+ctJEjGjN+wUsEeeGJLhWYJp7L4StU4ncSswc8eLh6qb2+nxDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d96d4fdb6a4028c83122d1f8dffc6e2092a774f7b4cb02b6acf74790da5b1013","last_reissued_at":"2026-07-05T12:01:25.686769Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:01:25.686769Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.12800","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T12:01:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CkW/en8323jsP+AM/lavf4L+oWyeUepxsECpessgRV+gz13vOboz8oMTra2pMtllCFoBhcoP/KpOF8g8BVhzAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:15:18.505994Z"},"content_sha256":"80b6eae3723cd74cddb6e56f24e5c0a7772ea91b9398b13645035e5072715f30","schema_version":"1.0","event_id":"sha256:80b6eae3723cd74cddb6e56f24e5c0a7772ea91b9398b13645035e5072715f30"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:3FWU7W3KIAUMQMJC2H4N77DOEC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Changhua Meng, Guoqing Wang, Jinzhen Lin, Qiwen Wang, Quanxing Zha, Shuo Yang, Sunhao Dai, Wenwen Xiong, Xiaofeng Wu, Yang Qin, Yong Deng, Yuan Wang, Yuqin Dai, Zhanwei Zhang, Zhenzhe Ying","submitted_at":"2025-08-18T10:23:10Z","abstract_excerpt":"Large language models (LLMs) exhibit remarkable problem-solving abilities, but struggle with complex tasks due to static internal knowledge. Retrieval-Augmented Generation (RAG) enhances access to external information, yet remains limited in multi-hop reasoning and strategic search due to rigid workflows. Recent advancements in agentic deep research empower LLMs to autonomously reason, search, and synthesize information. However, current approaches relying on outcome-based reinforcement learning (RL) face critical issues such as conflicting gradients and reward sparsity, limiting performance g"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.12800","kind":"arxiv","version":3},"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/2508.12800/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":"2026-07-05T12:01:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1gkhT0i39hmoRGn8UqlKZ2oc5RqBeArgroqTx7brh/Emfm+I/EJxlAWNHyW3mTH7PGbCXtCAzHrTIq4YbM17Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T04:15:18.506392Z"},"content_sha256":"82f5ea2f1e2e82ed5a28dc578cb5e4894092dcc52705e184ff330abcb9e62b8f","schema_version":"1.0","event_id":"sha256:82f5ea2f1e2e82ed5a28dc578cb5e4894092dcc52705e184ff330abcb9e62b8f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3FWU7W3KIAUMQMJC2H4N77DOEC/bundle.json","state_url":"https://pith.science/pith/3FWU7W3KIAUMQMJC2H4N77DOEC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3FWU7W3KIAUMQMJC2H4N77DOEC/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":"2026-07-07T04:15:18Z","links":{"resolver":"https://pith.science/pith/3FWU7W3KIAUMQMJC2H4N77DOEC","bundle":"https://pith.science/pith/3FWU7W3KIAUMQMJC2H4N77DOEC/bundle.json","state":"https://pith.science/pith/3FWU7W3KIAUMQMJC2H4N77DOEC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3FWU7W3KIAUMQMJC2H4N77DOEC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3FWU7W3KIAUMQMJC2H4N77DOEC","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":"39403b0cd8140a6699655e122f4ce3c3125fdc190b53e174bdf1de5a9df175fb","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-08-18T10:23:10Z","title_canon_sha256":"c90a19e9eefd45800a8a46466cb8fa1774520a4f74ae101fc553ff841afba0ae"},"schema_version":"1.0","source":{"id":"2508.12800","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.12800","created_at":"2026-07-05T12:01:25Z"},{"alias_kind":"arxiv_version","alias_value":"2508.12800v3","created_at":"2026-07-05T12:01:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.12800","created_at":"2026-07-05T12:01:25Z"},{"alias_kind":"pith_short_12","alias_value":"3FWU7W3KIAUM","created_at":"2026-07-05T12:01:25Z"},{"alias_kind":"pith_short_16","alias_value":"3FWU7W3KIAUMQMJC","created_at":"2026-07-05T12:01:25Z"},{"alias_kind":"pith_short_8","alias_value":"3FWU7W3K","created_at":"2026-07-05T12:01:25Z"}],"graph_snapshots":[{"event_id":"sha256:82f5ea2f1e2e82ed5a28dc578cb5e4894092dcc52705e184ff330abcb9e62b8f","target":"graph","created_at":"2026-07-05T12:01:25Z","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/2508.12800/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) exhibit remarkable problem-solving abilities, but struggle with complex tasks due to static internal knowledge. Retrieval-Augmented Generation (RAG) enhances access to external information, yet remains limited in multi-hop reasoning and strategic search due to rigid workflows. Recent advancements in agentic deep research empower LLMs to autonomously reason, search, and synthesize information. However, current approaches relying on outcome-based reinforcement learning (RL) face critical issues such as conflicting gradients and reward sparsity, limiting performance g","authors_text":"Changhua Meng, Guoqing Wang, Jinzhen Lin, Qiwen Wang, Quanxing Zha, Shuo Yang, Sunhao Dai, Wenwen Xiong, Xiaofeng Wu, Yang Qin, Yong Deng, Yuan Wang, Yuqin Dai, Zhanwei Zhang, Zhenzhe Ying","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-08-18T10:23:10Z","title":"Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.12800","kind":"arxiv","version":3},"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":"sha256:80b6eae3723cd74cddb6e56f24e5c0a7772ea91b9398b13645035e5072715f30","target":"record","created_at":"2026-07-05T12:01:25Z","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":"39403b0cd8140a6699655e122f4ce3c3125fdc190b53e174bdf1de5a9df175fb","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-08-18T10:23:10Z","title_canon_sha256":"c90a19e9eefd45800a8a46466cb8fa1774520a4f74ae101fc553ff841afba0ae"},"schema_version":"1.0","source":{"id":"2508.12800","kind":"arxiv","version":3}},"canonical_sha256":"d96d4fdb6a4028c83122d1f8dffc6e2092a774f7b4cb02b6acf74790da5b1013","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d96d4fdb6a4028c83122d1f8dffc6e2092a774f7b4cb02b6acf74790da5b1013","first_computed_at":"2026-07-05T12:01:25.686769Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:01:25.686769Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"YKG0pyPDfph2T6+WFQ04oTjfhsjNjQGpT2JD+ctJEjGjN+wUsEeeGJLhWYJp7L4StU4ncSswc8eLh6qb2+nxDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:01:25.687390Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.12800","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:80b6eae3723cd74cddb6e56f24e5c0a7772ea91b9398b13645035e5072715f30","sha256:82f5ea2f1e2e82ed5a28dc578cb5e4894092dcc52705e184ff330abcb9e62b8f"],"state_sha256":"555065feafa4e36def5dc0b500c062f54742a14193d6721820256e200c23b124"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bDuhnu3wKKgnKt/pI9s10/haZrw58n7BIyWWnIDhfe9rjCHOXO3/1SK18fQ3ejeiVvQc8J+uHocVnQm5okNkAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T04:15:18.508450Z","bundle_sha256":"7b53b1eaf6e79838eed7cc16128706d66cc114dcb0865bcb3c7cc32530ccf48f"}}