{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:XHHOJ2R7CKNRHF7VA2IZP5A2GL","short_pith_number":"pith:XHHOJ2R7","canonical_record":{"source":{"id":"2010.00117","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-30T21:50:46Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"01dcbb4489180805a7ec433f1378b8a626df3c8cb61eb95f5a315d3ee964d0c1","abstract_canon_sha256":"db5cc2d45e86f5ae67ab478abd572f75e98be9e038624224eb50a96c259cd615"},"schema_version":"1.0"},"canonical_sha256":"b9cee4ea3f129b1397f5069197f41a32e2132c31efea3ce5dfd9f0c24ac88476","source":{"kind":"arxiv","id":"2010.00117","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.00117","created_at":"2026-07-05T01:39:30Z"},{"alias_kind":"arxiv_version","alias_value":"2010.00117v1","created_at":"2026-07-05T01:39:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.00117","created_at":"2026-07-05T01:39:30Z"},{"alias_kind":"pith_short_12","alias_value":"XHHOJ2R7CKNR","created_at":"2026-07-05T01:39:30Z"},{"alias_kind":"pith_short_16","alias_value":"XHHOJ2R7CKNRHF7V","created_at":"2026-07-05T01:39:30Z"},{"alias_kind":"pith_short_8","alias_value":"XHHOJ2R7","created_at":"2026-07-05T01:39:30Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:XHHOJ2R7CKNRHF7VA2IZP5A2GL","target":"record","payload":{"canonical_record":{"source":{"id":"2010.00117","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-30T21:50:46Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"01dcbb4489180805a7ec433f1378b8a626df3c8cb61eb95f5a315d3ee964d0c1","abstract_canon_sha256":"db5cc2d45e86f5ae67ab478abd572f75e98be9e038624224eb50a96c259cd615"},"schema_version":"1.0"},"canonical_sha256":"b9cee4ea3f129b1397f5069197f41a32e2132c31efea3ce5dfd9f0c24ac88476","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:39:30.457248Z","signature_b64":"hgM+MYstmeN0Dvc8KAmDhY5yuIL++CFK+8kY2o5uR71GbXCYeAXM3/tpGrmSMxW/790KMEYCsDWG/NMKuBIcCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b9cee4ea3f129b1397f5069197f41a32e2132c31efea3ce5dfd9f0c24ac88476","last_reissued_at":"2026-07-05T01:39:30.456754Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:39:30.456754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.00117","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":"2026-07-05T01:39:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GHX8+WXyEreG0BuP06CIwj737zkI89ea/m+9rXcFAn+PUBLYG3dyvGOls7ff3gLH/wuXaWGuNcxEkk5HPs1cAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T16:08:27.486574Z"},"content_sha256":"360462165f4bdf65f3b2c9351730112fb1ad86575e962383049e85a0142bf14a","schema_version":"1.0","event_id":"sha256:360462165f4bdf65f3b2c9351730112fb1ad86575e962383049e85a0142bf14a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:XHHOJ2R7CKNRHF7VA2IZP5A2GL","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Jiawei Han, Xiang Ren, Yanru Qu, Yiqing Xie, Yuning Mao","submitted_at":"2020-09-30T21:50:46Z","abstract_excerpt":"While neural sequence learning methods have made significant progress in single-document summarization (SDS), they produce unsatisfactory results on multi-document summarization (MDS). We observe two major challenges when adapting SDS advances to MDS: (1) MDS involves larger search space and yet more limited training data, setting obstacles for neural methods to learn adequate representations; (2) MDS needs to resolve higher information redundancy among the source documents, which SDS methods are less effective to handle. To close the gap, we present RL-MMR, Maximal Margin Relevance-guided Rei"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.00117","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/2010.00117/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":"2026-07-05T01:39:30Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nV/2FpYA+Hzbqsgcf15dJMnwTUKm7kHCxNDILXzrgNyYU8ziXB/eEGdbUZI0Enx87HaK6zWoAxK5Cqaam0gFAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T16:08:27.487124Z"},"content_sha256":"ea5413901bb946af58508d9e116450e20c255f71994bda353c27b8438cc6aa32","schema_version":"1.0","event_id":"sha256:ea5413901bb946af58508d9e116450e20c255f71994bda353c27b8438cc6aa32"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XHHOJ2R7CKNRHF7VA2IZP5A2GL/bundle.json","state_url":"https://pith.science/pith/XHHOJ2R7CKNRHF7VA2IZP5A2GL/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XHHOJ2R7CKNRHF7VA2IZP5A2GL/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":"2026-08-19T16:08:27Z","links":{"resolver":"https://pith.science/pith/XHHOJ2R7CKNRHF7VA2IZP5A2GL","bundle":"https://pith.science/pith/XHHOJ2R7CKNRHF7VA2IZP5A2GL/bundle.json","state":"https://pith.science/pith/XHHOJ2R7CKNRHF7VA2IZP5A2GL/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XHHOJ2R7CKNRHF7VA2IZP5A2GL/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:XHHOJ2R7CKNRHF7VA2IZP5A2GL","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":"db5cc2d45e86f5ae67ab478abd572f75e98be9e038624224eb50a96c259cd615","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-30T21:50:46Z","title_canon_sha256":"01dcbb4489180805a7ec433f1378b8a626df3c8cb61eb95f5a315d3ee964d0c1"},"schema_version":"1.0","source":{"id":"2010.00117","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.00117","created_at":"2026-07-05T01:39:30Z"},{"alias_kind":"arxiv_version","alias_value":"2010.00117v1","created_at":"2026-07-05T01:39:30Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.00117","created_at":"2026-07-05T01:39:30Z"},{"alias_kind":"pith_short_12","alias_value":"XHHOJ2R7CKNR","created_at":"2026-07-05T01:39:30Z"},{"alias_kind":"pith_short_16","alias_value":"XHHOJ2R7CKNRHF7V","created_at":"2026-07-05T01:39:30Z"},{"alias_kind":"pith_short_8","alias_value":"XHHOJ2R7","created_at":"2026-07-05T01:39:30Z"}],"graph_snapshots":[{"event_id":"sha256:ea5413901bb946af58508d9e116450e20c255f71994bda353c27b8438cc6aa32","target":"graph","created_at":"2026-07-05T01:39:30Z","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/2010.00117/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While neural sequence learning methods have made significant progress in single-document summarization (SDS), they produce unsatisfactory results on multi-document summarization (MDS). We observe two major challenges when adapting SDS advances to MDS: (1) MDS involves larger search space and yet more limited training data, setting obstacles for neural methods to learn adequate representations; (2) MDS needs to resolve higher information redundancy among the source documents, which SDS methods are less effective to handle. To close the gap, we present RL-MMR, Maximal Margin Relevance-guided Rei","authors_text":"Jiawei Han, Xiang Ren, Yanru Qu, Yiqing Xie, Yuning Mao","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-30T21:50:46Z","title":"Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.00117","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":"sha256:360462165f4bdf65f3b2c9351730112fb1ad86575e962383049e85a0142bf14a","target":"record","created_at":"2026-07-05T01:39:30Z","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":"db5cc2d45e86f5ae67ab478abd572f75e98be9e038624224eb50a96c259cd615","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2020-09-30T21:50:46Z","title_canon_sha256":"01dcbb4489180805a7ec433f1378b8a626df3c8cb61eb95f5a315d3ee964d0c1"},"schema_version":"1.0","source":{"id":"2010.00117","kind":"arxiv","version":1}},"canonical_sha256":"b9cee4ea3f129b1397f5069197f41a32e2132c31efea3ce5dfd9f0c24ac88476","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b9cee4ea3f129b1397f5069197f41a32e2132c31efea3ce5dfd9f0c24ac88476","first_computed_at":"2026-07-05T01:39:30.456754Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:39:30.456754Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hgM+MYstmeN0Dvc8KAmDhY5yuIL++CFK+8kY2o5uR71GbXCYeAXM3/tpGrmSMxW/790KMEYCsDWG/NMKuBIcCA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:39:30.457248Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.00117","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:360462165f4bdf65f3b2c9351730112fb1ad86575e962383049e85a0142bf14a","sha256:ea5413901bb946af58508d9e116450e20c255f71994bda353c27b8438cc6aa32"],"state_sha256":"6c5b1c1b5934dbe07069766e93e163c348847b7bd2add697f16f161a62261560"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WHoN1p533TkcpjYYan8UQlglpZY9pAKoFGi71tlF7Xs7i5LXPWcMaSzup41Wemt5F4veCy+RkVy2Glzp3r+nCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T16:08:27.492686Z","bundle_sha256":"cc69bd0f93ee968d09da315a818d107d0ed6cf42582fd7569bfaff321440ac7b"}}