{"as_of":"2026-08-10T01:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6afae3070377fadcf855f4e1884c695ddb9d5fa3705f02169ba47d0668d8c410","coverage":[{"denominator":21,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":21,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T12:33:02.900923Z","state":"measured"},{"denominator":21,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":21,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2601.02871/citation-record","integrity":"/paper/2601.02871/integrity","json":"/paper/2601.02871/citation-record.json","paper":"/paper/2601.02871"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:01.397765Z","title":"action\":","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:01.397765Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:e6617bd02580330f73edc39680d427638cf7d3c1070db63c262e48cb29bcd298","observation_id":"a27f3092-f763-4165-97f0-fee7fc4a2fd0","resolution":{"observed_at":"2026-08-03T12:33:01.397765Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:00.912204Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:00.912204Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:c1852e3320d5b987ea5a25abe4cb989367eabe143ac414305821a49db577b565","observation_id":"39ae41d5-2209-4265-82bd-ace4088e31e8","resolution":{"observed_at":"2026-08-03T12:33:00.912204Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06706","last_updated":"2023-02-13T21:37:41Z","snapshot_observed_at":"2026-08-05T18:32:51.931194Z","submitted_at":"2023-02-13T21:37:41Z","title":"On the Planning Abilities of Large Language Models (A Critical Investigation with a Proposed Benchmark)","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06706","snapshot_observed_at":"2026-08-03T12:33:00.546549Z","title":"Jian Wang, Yi Cheng, Dongding Lin, Chak Tou Leong, and Wenjie Li","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:00.546549Z"},"links":{"cited_paper":"/paper/2302.06706","citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:90b0cb295e0978c638a477776c8b338ddd1af14ff44d451fa617183542d1fc79","observation_id":"d136aa95-f845-4816-8035-253ff2ece567","resolution":{"observed_at":"2026-08-03T12:33:00.546549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:02.800299Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:02.800299Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:a646983b11d0d0ff00631903ac97c61373b2f27c9acf5a582679c6d1b5c9079c","observation_id":"d3d2f323-db74-4fde-932d-82b1a4188475","resolution":{"observed_at":"2026-08-03T12:33:02.800299Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:02.900923Z","title":"action\":","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:02.900923Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:6944da4a4c707090561b7c10272391ff158d2fe14585ad61db60883ab78ec496","observation_id":"01bbbe0c-6a03-4267-8a0a-bf9adf530798","resolution":{"observed_at":"2026-08-03T12:33:02.900923Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:01.100158Z","title":"no fees\" policy to build trust. 2.Clarifying Logistics: It clearly explained the","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:01.100158Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:5cd8657ad37c8dec661ee28132a7fda6bd70fbda1b2929c53cf51cbf7305424c","observation_id":"fbf511cc-9e41-4a52-8306-5328a073f04f","resolution":{"observed_at":"2026-08-03T12:33:01.100158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:01.210204Z","title":"The user will stop trying to add the contact, believing they will be contacted","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:01.210204Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:3ca06305a3e92f107a1a71d41b1478e3c71dc30aaa57fed9ae1caa102ef4d404","observation_id":"186bd48b-09b3-45af-b137-2df992933417","resolution":{"observed_at":"2026-08-03T12:33:01.210204Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:01.322318Z","title":"My ID is wx12345","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:01.322318Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:f71e899c67a1d25c369c51aa9f6f8bcb3be89995ce6673ed69db4ff124142818","observation_id":"cbad8b49-cc54-498c-ba57-0133eee23ed2","resolution":{"observed_at":"2026-08-03T12:33:01.322318Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:01.572693Z","title":"current interest/intent level","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:01.572693Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:ce0c18968d0421c8a73f086f9acc7884418a0a5c979d0e1d2aa53ca001c3242f","observation_id":"933339fa-82e9-48df-810e-2f18391cbcb4","resolution":{"observed_at":"2026-08-03T12:33:01.572693Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:01.714369Z","title":"tendency","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:01.714369Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:d6e3d9dafa10a1a6fc6b3e93e81c43cd5334f6cbb4415a4335409c00ede31dc2","observation_id":"629fbfd1-2804-4605-b91b-8d2d6bf528dc","resolution":{"observed_at":"2026-08-03T12:33:01.714369Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:01.937959Z","title":"[Avoid Mechanical Repetition]","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:01.937959Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:2de0e400e6143c6254442eb48add402eed82c8275dfbd322d9552d97585c6616","observation_id":"59975e2a-3fb1-44ce-9448-7cfbf5740e2a","resolution":{"observed_at":"2026-08-03T12:33:01.937959Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:02.081212Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:02.081212Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:2d0a60a447090aba0dcb568d48fa09be7a542f7fedbaa19efed9b16a768747dd","observation_id":"9021158a-c221-430b-bdd5-75f512252597","resolution":{"observed_at":"2026-08-03T12:33:02.081212Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:02.213038Z","title":"Just to follow up on my earlier question","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:02.213038Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:b1e333e9db14619032f4b5bd4821fdb759a8a66d3adfa0efefeb56b5265c12cf","observation_id":"45a4a673-0fcf-4aef-b615-3a640cce2c3a","resolution":{"observed_at":"2026-08-03T12:33:02.213038Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:02.347485Z","title":"action\" field: •null: no special action—only send a textual reply; •","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:02.347485Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:370ccfea71d2577e9797c04b6ed189449a673568ec41de45d6d9d0100cb58fae","observation_id":"ff1a5a41-0b85-4715-9652-8b6664421432","resolution":{"observed_at":"2026-08-03T12:33:02.347485Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:02.437489Z","title":"action\":...,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:02.437489Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:8dac7d002b8a505474a66ffc07645074ed9cb00ceca743777c55a34e3ba5203a","observation_id":"b6d520e8-eee3-4837-b77a-aa14d24c249e","resolution":{"observed_at":"2026-08-03T12:33:02.437489Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:02.507325Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:02.507325Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:6f6c1484f292e52f633a62268e44811577f1fb9697468d33737778d86027884d","observation_id":"d685a21e-5379-4368-bc79-f9d4c20a0617","resolution":{"observed_at":"2026-08-03T12:33:02.507325Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:02.640283Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:02.640283Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:b0df6ece8fc15cb32a7fd90b182894e8cc46194a41d8bd88384f6f09f450f591","observation_id":"ed58587e-0a65-495c-963a-d6c0a068f525","resolution":{"observed_at":"2026-08-03T12:33:02.640283Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-03T12:33:02.718190Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:02.718190Z"},"links":{"citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:7c5f63b097aeeb4117e3ff9e2995da31f1dc7b0a8b7f48e65b087b7823853e15","observation_id":"60498686-6130-4161-ad89-e017ba136166","resolution":{"observed_at":"2026-08-03T12:33:02.718190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.05125","last_updated":"2017-06-16T01:26:09Z","snapshot_observed_at":"2026-07-06T05:47:06.697057Z","submitted_at":"2017-06-16T01:26:09Z","title":"Deal or No Deal? End-to-End Learning for Negotiation Dialogues","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.05125","snapshot_observed_at":"2026-08-03T12:33:00.232534Z","title":"InIncreasing Naturalness and Flexibility in Spoken Dialogue Interaction: 10th International Workshop on Spoken Dialogue Systems, pages 291–297","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:00.232534Z"},"links":{"cited_paper":"/paper/1706.05125","citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:893a624661bb5cedfcdf3021f1620082f66d655af01aa557e48e40360bf79213","observation_id":"e4808cd2-9be7-4978-802d-ebee1a6bddb7","resolution":{"observed_at":"2026-08-03T12:33:00.232534Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.17493","last_updated":"2024-04-14T05:20:10Z","snapshot_observed_at":"2026-08-05T16:03:40.517679Z","submitted_at":"2023-05-27T15:10:41Z","title":"The Curse of Recursion: Training on Generated Data Makes Models Forget","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.17493","snapshot_observed_at":"2026-08-03T12:33:00.313784Z","title":"Karthik Valmeekam, Sarath Sreedharan, Matthew Mar- quez, Alberto Olmo, and Subbarao Kambhampati","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:00.313784Z"},"links":{"cited_paper":"/paper/2305.17493","citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:056a4c59f331fcca3c31e111d1338e3250ddaf18c4bd1c177f3338b6f1da453e","observation_id":"6629cca4-4f30-4f97-b0ba-7f4eb8a55d46","resolution":{"observed_at":"2026-08-03T12:33:00.313784Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.13366","last_updated":"2025-06-18T06:17:35Z","snapshot_observed_at":"2026-08-07T00:32:19.938378Z","submitted_at":"2025-06-16T11:15:21Z","title":"Enhancing Goal-oriented Proactive Dialogue Systems via Consistency Reflection and Correction","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.13366","snapshot_observed_at":"2026-08-03T12:33:00.685089Z","title":"arXiv preprint arXiv:2506.13366","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection","version":3},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-03T12:33:00.685089Z"},"links":{"cited_paper":"/paper/2506.13366","citing_paper":"/paper/2601.02871"},"observation_digest":"sha256:4211ed02d85299c3aba6ec87a225abd6a6b4c845d750547ba0b62fee230b7ebc","observation_id":"1b986b02-3cf5-4897-8a8f-b7c30b8964a7","resolution":{"observed_at":"2026-08-03T12:33:00.685089Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2601.02871","last_updated":"2026-07-09T14:15:48Z","latest_version":3,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-08T09:24:08.149965Z","submitted_at":"2026-01-06T10:00:15Z","title":"SimRPD: Optimizing Recruitment Proactive Dialogue Agents through Simulator-Based Data Evaluation and Selection"},"reference_resolution":{"displayed":21,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":21,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":21},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2601.02871."}