{"as_of":"2026-08-17T13:27:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b9b0db955c14d2135f8914112b6ef570d7c7e15d7cb530f9fe4a521c321753ad","coverage":[{"denominator":54,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":54,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T10:52:11.987091Z","state":"measured"},{"denominator":54,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":54,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2607.10555/citation-record","integrity":"/paper/2607.10555/integrity","json":"/paper/2607.10555/citation-record.json","paper":"/paper/2607.10555"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"From Exploration to Mastery: Enabling","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:42e27cbb474639f81123982e3226e2efeed5375707b0683acb16c6fdfb6411bd","observation_id":"98ca3ec3-7342-4eba-9b81-3ffc1475ac5a","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:8ea0a2e540de0c9b89cf6236934af1341dc81abcc1ec38eb8e6b503f68532cae","observation_id":"0956ef82-4330-4560-91b1-b88707e67a75","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Neural Information Processing System , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:690283d30691ab9240dc7560d2b1efde4f4cbe8467fddc861b12b7c57a3e41e8","observation_id":"7f01ab30-e6fe-4f1c-a2bd-77270e8b7302","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:6bab98550ea5a9534693bf9e79130e6c305d89f30b3600f191d71ac0f11ccfd0","observation_id":"43feb3b0-867a-44c4-9c9e-61419710c3c0","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.14192","last_updated":"2026-07-03T11:26:58Z","snapshot_observed_at":"2026-08-16T19:40:36.106334Z","submitted_at":"2026-01-20T17:51:56Z","title":"Toward Efficient Agents: Memory, Tool learning, and Planning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.14192","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2601.14192 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2601.14192","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:6f7f5a3dfa67754684156a371dce7593a6d78fd6f530998f19cadbbe8343ecf5","observation_id":"f20b51c9-7655-45f0-a29a-f72e6288d69b","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"International Conference on Learning Representations , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:844730f6e11268163014ede11956a00cba793e3e0c49aa00bfe9896d15702dcf","observation_id":"270da33b-6ceb-4ada-a50d-6631fa840f78","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.14870","last_updated":"2025-05-31T20:08:42Z","snapshot_observed_at":"2026-08-17T10:37:01.064934Z","submitted_at":"2025-04-21T05:40:05Z","title":"Acting Less is Reasoning More! Teaching Model to Act Efficiently","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.14870","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2504.14870 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2504.14870","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:3b4db84db9ede29a9a16c587adad620d17c047b17c2f79e5233d47aac19a7f6f","observation_id":"32dd47ce-024b-47ad-8dfd-58993f17a11f","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2511.21689 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:338202adfebd76407a100b33a0f87e9ed178fc0b8d59d8cb56bc91b190482ec9","observation_id":"e533c430-edac-40c0-9a49-ada235d94f33","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Findings of the Association for Computational Linguistics , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:2a7ac6565fc2e5ee428056d65093d482d07ee4493f67ffa2e5c7d7a1b7fa819f","observation_id":"043d7034-6fbb-4027-8708-0604ada4652e","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Neural Information Processing System , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:77a3bcb4b9f60f5a996181c54faf172e752230403250d79a26cd3e119cc8a07a","observation_id":"ed649be5-cf7a-4e35-97dc-8592ba4ee523","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.06034","last_updated":"2025-03-08T03:14:26Z","snapshot_observed_at":"2026-08-16T12:52:00.499828Z","submitted_at":"2025-03-08T03:14:26Z","title":"Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.06034","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2503.06034 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2503.06034","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:9234f1cbd7dbf280e933011371014c4fca8aca04de764a1a1dd89e6f79f2dd6f","observation_id":"db265419-95c1-4902-b25b-cf961df03aa6","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Empirical Methods in Natural Language Processing , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:c3487691e0b716ddaf2788e3899c5e856291b74eed1eb65c8ce0b0b6207041fc","observation_id":"63c64e71-4728-4a33-b3f6-9b1bdd9fe088","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"AAAI Conference on Artificial Intelligence , page=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:fc1d3481cf399f40e6d7476b5ff3ecdbedb28c0ae4777ef526474a76862f4393","observation_id":"e6c1f885-f029-4ee0-9fd6-b2f09a64edd9","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.07820","last_updated":"2020-03-18T16:56:56Z","snapshot_observed_at":"2026-08-10T13:25:09.780441Z","submitted_at":"2020-03-17T17:12:36Z","title":"Overview of the TREC 2019 deep learning track","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.07820","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2003.07820 , year=","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2003.07820","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:69575af019a5f5e9346f4db201a2e1578a60b51db5b28b559d3f178bf9eabb8c","observation_id":"0dcf768b-df19-4720-a913-5f9e46e44584","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.07662","last_updated":"2021-02-15T16:47:00Z","snapshot_observed_at":"2026-08-16T18:45:27.659994Z","submitted_at":"2021-02-15T16:47:00Z","title":"Overview of the TREC 2020 deep learning track","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.07662","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2102.07662 , year=","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2102.07662","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:fde89b084ec7f3a6c764bdabc65f6fe2b81a7fcd444d3edec66c3102f6d8ae3a","observation_id":"6a753244-3847-4e58-ae1a-2ee4b3fab096","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09388","last_updated":"2025-05-14T13:41:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-14T13:41:34Z","title":"Qwen3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2505.09388 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:93258075b1c28c70eea2249a6cc4447b819d0e3db78ba64b196edd868f3bb015","observation_id":"a0e16576-8068-496e-b117-ce43c653c2cc","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:846b8d5234e63a68d5fba1a90768f6f8a27a88b9facb6f4a5986cd176a432578","observation_id":"c128b54a-c70e-498d-bbbc-f4e087feafeb","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Neural Information Processing System , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:74430fc2b534b7ae3b51836b3fc753a72e224c3d1ae18a87a145b9e2ec43b1dc","observation_id":"71b2d84b-bc37-43c1-b8df-d6906390eddc","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"International ACM SIGIR Conference , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:f4021af409de9bee4ad0c4d6a3d4b99a096f9453ff4b2c2966e56472f1cc52a1","observation_id":"63922877-a538-49d8-b57d-d26ef0c5d543","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:1032b01202feb25d12caee4d99679608103186578f9810334ca91d63f21095e9","observation_id":"731c1223-007c-4970-b072-f6ec41882e73","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Conference on Language Modeling , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:337d1748ceafd981b9625451c8ed686a434f96309e4bf1cac27d58b6215e5779","observation_id":"84a0101f-425b-4eea-acce-9122abf2eb23","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"ACM SIGKDD Conference , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:39b5523c05e26c1a26717310d4b1bd87d9430a25e0882cf37c5cdf8f15412269","observation_id":"c33e0f99-c207-474a-89b0-d04ee8ff5cfc","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"International Conference on Information and Knowledge Management , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:c66735c54260f85b23f2386808dc7ad7c9d1b2ac1f3358c8aefb52af465be510","observation_id":"e2fe5d8a-dd33-46c7-bd95-c128986f3f0a","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:1ab717410fcf99a1a926519bf057d42b78676efa8ce4971ad3dc2b8d1d523b58","observation_id":"0b374453-199d-494f-80af-99763f8d0965","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Transactions on Machine Learning Research , page=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:3086d06967833ea3edbdc2bc443e3e8fcedaddafdd7b9c514816479ef6f99265","observation_id":"15eb4566-eda4-4d2d-8756-e63f802b2ffc","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Association for Computational Linguistics , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:b2116611758b00fa97e3943882c9cfd85acc71a98fbbf0fe34107e1a333a394a","observation_id":"30c3a6f0-6330-412c-99b8-ac13a544e9f6","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Findings of the Association for Computational Linguistics , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:0c3698c324b1df3febfd0cabb4298821e7d2b6f9f454d47ce4c0296d2fb45219","observation_id":"d6801176-6525-4a22-8c4b-f3a5c9ce9500","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"2024 , pages =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:f7645553551b6649114d7e7c4929bebce848e8488bd7298ed6974fb9ee0892bb","observation_id":"86c0b554-b80e-4538-8519-42922ca9502e","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.05242","last_updated":"2026-05-03T19:13:11Z","snapshot_observed_at":"2026-08-11T09:50:27.781126Z","submitted_at":"2026-05-03T19:13:11Z","title":"Beyond Semantic Similarity: Rethinking Retrieval for Agentic Search via Direct Corpus Interaction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.05242","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2605.05242 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2605.05242","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:836a5a0439d3eff7ffd18a6021d7887767c8e3c4d5ca8f94d5734f5b038154de","observation_id":"c3cd43ef-d42d-484c-9241-8b82d1029033","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"2025 , pages =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:d52b394e41bb4893a95dbb8bab9b027afab940366983b804f3933232ae3b2b1b","observation_id":"f97ae2e3-ccf7-4b36-ad51-d9f7e1e30194","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"2024 , pages =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:3c241b41e347678c7c6e389e4eb2686f2e91826aa541f5bf6e3e664f8a36c7aa","observation_id":"3c213418-9ddb-4e12-b1bb-7fb6c0c7f183","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.06412","last_updated":"2026-05-07T07:25:18Z","snapshot_observed_at":"2026-08-15T06:36:48.899200Z","submitted_at":"2025-08-08T15:56:49Z","title":"Sample-efficient LLM Optimization with Reset Replay","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.06412","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2508.06412 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2508.06412","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:0e054fd6231fad1493f020e45f0ebe229eb1a5504f3cb666a1f3345616d02997","observation_id":"cc8dd1ad-556a-4bf1-885b-ceb3357b46ab","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning , journal=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:bdd90ced8aa528c52d057ef752b300a631e4b5f6f47a8471991ea482da2de75b","observation_id":"08b03645-d433-4553-b84f-d85751cbb510","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:624e19a03a6962604d62562028f143fe3c7cd1b6581cc7348686f806b11c3a4b","observation_id":"96c5e10a-e255-4290-85c0-03d7bf177321","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Neural Information Processing System , page=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:7e36a3b6499d53a1053b6d477de223f8f2cbf87374bcca48d32feac5bc412536","observation_id":"8b1341d5-6243-437f-9431-eec4c5615f80","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Transactions on Information Systems , page=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:99bffe68c77567ae8325df6cb6334c6d87ed7fd28e83e6700b71cd131a05b2a2","observation_id":"b2eae90e-d9e2-4744-a277-caab302ca0c2","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Agentic Reasoning and Tool Integration for","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:fbd29540047fae713940b6ec0e14709acace1104ff4dcaf8e802cd127c5e17c9","observation_id":"50b4c117-a26c-4ffc-92d7-8f2f769e8f24","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:1ff03fddf9a8d7743aa82c08b5927531f2c1e45b6f3a6c2c7043f0a2348dcaea","observation_id":"a5b88476-202d-4e99-8f03-930a039f81e0","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"FacTool: Factuality Detection in Generative","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:a05841d4ecae2678f541965e2e0b91b28dc888c52aed8d474af2646ba4e02ac4","observation_id":"13a8e194-04ca-47fb-b03a-42ee62b6bcd8","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:9808f1fa02855e2345c3685731ab18da6a5c8ac26ed420e495b4fa0816d72b29","observation_id":"854e9e5e-4f7e-4a1f-a8aa-c0958135773c","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"International ACM SIGIR Conference , page=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:54458f52cb840e8e5c47ed56a965f584972eab48f1ec6255e2ae09554b47c805","observation_id":"56e4ff97-7b3f-4f6f-a9b7-69926268faa0","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.07050","last_updated":"2026-04-22T03:08:54Z","snapshot_observed_at":"2026-08-14T20:21:06.868200Z","submitted_at":"2025-08-09T17:26:18Z","title":"ReasonRank: Empowering Passage Ranking with Strong Reasoning Ability","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.07050","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2508.07050 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2508.07050","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:06c774693508bda5044cf7748ca376c6726965f71191eb14e3bc0fe6555c4990","observation_id":"b7ae7582-7a32-441e-b83f-5fd0b46faa56","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:18a609f4584b17b11f82cee5ace3300a0a4d24508c1bd65676666a285c302f78","observation_id":"f9333260-4338-449f-8997-98fb15ca625e","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Transactions of the Association for Computational Linguistics , page=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:2fc8e4ea7049032fb7be6bbea6a1527fe34c6e56a82525994942bdc26487177c","observation_id":"d8a3e0eb-f397-42d9-af23-a39ded4589b4","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:e24c31f85e37dd2dfe6bf55d4edc7faea108a69b22804417413df22732ca2336","observation_id":"66cffaf7-4b4b-45de-8bcc-691c9110573e","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Association for Computational Linguistics , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:59a0cf04967e7e9c98fc5321317c692ef6cf6666705d0ef90b58e06b346772b9","observation_id":"67805ea9-99d9-4d00-84ca-bafab9c53723","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":", booktitle =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:2df8590270014b4b079bd77852f09f2ec79f15dd347c1ea3372f4fa8e38c5be9","observation_id":"ae0b638a-e002-4348-a9fd-3153373a68a4","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Constructing A Multi-hop","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:e3a254aae47df1c34130a30cac5d7fa262947edc7ab8e49bd494964c0bde3eec","observation_id":"58779979-ed6b-4191-9baa-f0cb408099be","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2108.00573","last_updated":"2022-05-05T05:50:50Z","snapshot_observed_at":"2026-08-16T18:05:58.747950Z","submitted_at":"2021-08-02T00:33:27Z","title":"MuSiQue: Multihop Questions via Single-hop Question Composition","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.00573","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2108.00573 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2108.00573","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:c5d3725cf2841de9d72209bfa0143f557ad7c6109ccd9a6f411d667dddcbb766","observation_id":"214d11c6-9cf9-41a0-88d7-2c8743cff169","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"Findings of the Empirical Methods in Natural Language Processing , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:62cd9b72024a0f223a3d25633c46bb872ae952f20b330b278fb594440a6c157a","observation_id":"9b3b9b4f-573f-4444-9a68-ef82cbb122cd","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.04368","last_updated":"2024-11-07T01:58:42Z","snapshot_observed_at":"2026-08-17T10:08:57.374438Z","submitted_at":"2024-11-07T01:58:42Z","title":"Measuring short-form factuality in large language models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.04368","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2411.04368 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2411.04368","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:ad1becfa17add171a8d3b8f334da971798ef9efb49cf8738683a04e550f71274","observation_id":"7452ce0f-5786-4e28-a22e-ae4c3635de3a","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","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":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2512.10791 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:8c348a179a38598162908b086fa9fcdf5e1c84703f9b5a2558642b52bff14137","observation_id":"67c950b0-31f5-4575-aa2f-081424bc8e66","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.05176","last_updated":"2025-06-11T02:54:49Z","snapshot_observed_at":"2026-08-17T07:57:12.232097Z","submitted_at":"2025-06-05T15:49:48Z","title":"Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.05176","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2506.05176 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2506.05176","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:f03137cc9a3d64b4311a2ba377e8d1023d9ae6a61bcbd285106f465169e108be","observation_id":"51488516-644e-478e-a57b-adab5cf440ea","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.04720","last_updated":"2026-01-19T09:03:26Z","snapshot_observed_at":"2026-08-14T12:22:57.900954Z","submitted_at":"2026-01-08T08:36:06Z","title":"Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.04720","snapshot_observed_at":"2026-07-14T10:52:11.987091Z","title":"arXiv preprint arXiv:2601.04720 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-07-14T10:52:11.987091Z"},"links":{"cited_paper":"/paper/2601.04720","citing_paper":"/paper/2607.10555"},"observation_digest":"sha256:9bed251476b8abf1e55cce596afeeea577ab1f987b2eb8f0b4eade073d8bae90","observation_id":"b62a7137-e16b-479c-baa2-d553100f4dde","resolution":{"observed_at":"2026-07-14T10:52:11.987091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.10555","last_updated":"2026-07-12T04:04:59Z","latest_version":1,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-14T19:00:52.434753Z","submitted_at":"2026-07-12T04:04:59Z","title":"Tool-Adaptive LLM Reranker"},"reference_resolution":{"displayed":54,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":54,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":54},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2607.10555."}