{"as_of":"2026-08-08T05:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b7bee854623ace7ad607803075d1eaa6a035e3a3300232e84f4893bfcb5041a2","coverage":[{"denominator":16,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:26:31.204976Z","state":"measured"},{"denominator":18,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":18,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-21T15:15:25.731014Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-21T15:20:17.443152Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"cited_work":{"arxiv_id":"2506.02519","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.02519","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning together to perform better: Teaching small-scale llms to collaborate via preferential ra- tionale tuning.ArXiv, abs/2506.02519","venue":null,"work_id":"dddf42f6-ba98-4d17-8b01-9189c6e850b5","year":2025},"citing_paper":{"arxiv_id":"2601.13992","last_updated":"2026-05-16T03:31:10Z","snapshot_observed_at":"2026-08-01T01:35:01.028258Z","submitted_at":"2026-01-20T14:05:19Z","title":"\"The Whole Is Greater Than the Sum of Its Parts\": A Compatibility-Aware Multi-Teacher CoT Distillation Framework","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-21T15:15:25.731014Z"},"links":{"cited_paper":"/paper/2506.02519","citing_paper":"/paper/2601.13992"},"observation_digest":"sha256:6774def65c65dcc7353b2722c78d614aba6961c4e9dbc2da40fc7e0ae6132462","observation_id":"d244099a-b9e7-4af6-930d-9eead7aded40","resolution":{"observed_at":"2026-05-21T15:20:17.445202Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"cited_work":{"arxiv_id":"2506.02519","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.02519","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning together to perform better: Teaching small-scale llms to collaborate via preferential ra- tionale tuning.ArXiv, abs/2506.02519","venue":null,"work_id":"dddf42f6-ba98-4d17-8b01-9189c6e850b5","year":2025},"citing_paper":{"arxiv_id":"2605.07353","last_updated":"2026-05-08T07:08:25Z","snapshot_observed_at":"2026-07-06T23:19:46.018236Z","submitted_at":"2026-05-08T07:08:25Z","title":"Confidence-Aware Alignment Makes Reasoning LLMs More Reliable","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-11T02:10:40.020460Z"},"links":{"cited_paper":"/paper/2506.02519","citing_paper":"/paper/2605.07353"},"observation_digest":"sha256:3f5b5591fc2cd3b64e880a3e4ce4d934e6b7294f3808916d03aea6787b111c2f","observation_id":"2bdac217-2b84-47fc-b5f7-c896d9f0a724","resolution":{"observed_at":"2026-05-11T03:55:54.060991Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.02519/citation-record","integrity":"/paper/2506.02519/integrity","json":"/paper/2506.02519/citation-record.json","paper":"/paper/2506.02519"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:32.946587Z","title":"15 samples ran- domly from the test sets of each of the 5 task datasets","venue":null,"work_id":"2c542ef8-cf1e-4dee-b566-c9d76f055f63","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.326291Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:d3f553bbe7f5173ee757bb4a7fef757072a235d940ebcf2a340e7247c8360573","observation_id":"fa548e25-64b5-4bac-8189-c931f8c6ec3d","resolution":{"observed_at":"2026-08-07T11:26:33.017486Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:33.280309Z","title":"InAdvances in Neural Information Processing Systems, volume 36, pages 11809–11822","venue":null,"work_id":"8833ada8-9ca7-4170-a547-10174a09b835","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.098866Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:5e1b112e972d828bd03ce9b6f497e6b2ceb6efe5ee44045207038df73468f2e2","observation_id":"55482794-62bb-4290-bbfa-574208ceb042","resolution":{"observed_at":"2026-08-07T11:26:33.315717Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.10020","last_updated":"2025-03-28T00:06:51Z","snapshot_observed_at":"2026-08-07T08:02:34.857823Z","submitted_at":"2024-01-18T14:43:47Z","title":"Self-Rewarding Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.10020","snapshot_observed_at":"2026-08-07T11:26:30.183317Z","title":"toaster\".✗ Rationale Provider 1:The issue described is that the eggplant didn’t fit in the toaster. Therefore, the correct answer is “eggplant","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.183317Z"},"links":{"cited_paper":"/paper/2401.10020","citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:acba0f2c4d4230317524a133a69c66bddde9025c916b6db1f8b4b6cde55e26a8","observation_id":"5def50aa-9528-476c-b9af-c84f39a50e25","resolution":{"observed_at":"2026-08-07T11:26:30.183317Z","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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:33.129037Z","title":"D Dataset Samples Details of datasets were discussed in the ‘Experi- ments and Evaluation’ section in the main paper","venue":null,"work_id":"6e043702-c642-472f-b16d-d0d036903432","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.255519Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:eec55f7e4a9a535f6182ce7e380ed021a29802d896ac1dc0f630329b0e94b9e3","observation_id":"c6faabc2-b02d-4592-a40a-437e7a2c97ab","resolution":{"observed_at":"2026-08-07T11:26:33.194898Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:32.784791Z","title":null,"venue":null,"work_id":"2a09e233-1137-4879-80a0-c060abf4edc2","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.394283Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:e485847f5e3bcbe97815be80be5f80e821ed2b4487ea2985e09884aa034e24a8","observation_id":"a67ad4df-5358-4527-a057-e52970b2fe60","resolution":{"observed_at":"2026-08-07T11:26:32.858269Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:32.617198Z","title":"Provide a label out of 0 or 1 such that 0 means that the final rationale is totally wrong; and 1 means that the final rationale is totally correct","venue":null,"work_id":"afab7336-0d4e-4831-8643-118347e83b77","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.472695Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:9879e6b87ea4daa5930abe0e25ee8d690462ede751ef09d7a289836b1c98f689","observation_id":"857e342e-3ed7-41aa-998a-f5fe4e62ad91","resolution":{"observed_at":"2026-08-07T11:26:32.695497Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:32.426518Z","title":"Provide a label of 0 or 1 where 0 means that none of the rationales is better than the other and 1 means that one rationale is better than the other","venue":null,"work_id":"918fb83f-f8aa-4a4d-906e-ef7cb8b1b51e","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.579647Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:f5e57c1992c25b3f93f21bda0f0fb37e6854a00e5789a7fb9ec8867f722582dc","observation_id":"3f781dfc-39cc-462b-a3fa-3447b8f7e9db","resolution":{"observed_at":"2026-08-07T11:26:32.526400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:32.233567Z","title":"Definition of Metrics Estimated from Human Labels Different rationales were presented to human evaluators in jumbled order to avoid biases while comparing rationales","venue":null,"work_id":"2278ffee-55cf-44e2-82f7-7786aab535b9","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.650907Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:4136ea99f6e987af31420102ad9d9b70f56f77bc053b25c596be99bc11bd8e47","observation_id":"a21e6bc8-409d-4c90-9361-936e5e07d537","resolution":{"observed_at":"2026-08-07T11:26:32.352408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:32.093254Z","title":"totally correct","venue":null,"work_id":"cff4a55e-44c1-4eaa-8625-39dc5207c3b2","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.727717Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:beb1583a11cf775ff3ed1e79fc030c8864b798c8df5a1abe8e80690e829982a6","observation_id":"ccb69efe-3f00-48f1-a32e-97fbc31b16b3","resolution":{"observed_at":"2026-08-07T11:26:32.157523Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:31.935526Z","title":"cases where one of the two ratio- nales is better than the other (label 1)","venue":null,"work_id":"58042b0c-c2ae-4883-a44f-aa93fb105134","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.823842Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:366b52ebe5a76bff89008564bf44aa699143585f4a483713e75802a1441a3b77","observation_id":"d3c17616-0ec0-479d-9c18-81c0cd731193","resolution":{"observed_at":"2026-08-07T11:26:32.017497Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:31.817411Z","title":"one of the generated rationales is judged better than the other generated rationale (comparing R1g and R2g)","venue":null,"work_id":"01ada86e-3b15-4935-ae16-06232def4762","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.886039Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:6d53ae96c284186d306c5b50d32b950b17489a2e57f47adad5489178bc0d0200","observation_id":"f39cce1e-c00a-4e15-bf07-aa85169b0e84","resolution":{"observed_at":"2026-08-07T11:26:31.864042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:31.696830Z","title":null,"venue":null,"work_id":"291147d4-86fa-4806-983d-439fc2ff58da","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.960338Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:825f9d6c12a85fc4536be890dab507854c7870ec0d766ccfc26454c04ab030d5","observation_id":"285d7483-7c87-492a-94f8-0bb4cd7fbde5","resolution":{"observed_at":"2026-08-07T11:26:31.751699Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:31.558508Z","title":"This means that employing two variants of same LLM is useful to obtain distinct and diverse rationales which are useful to improve quality of preference data for DPO","venue":null,"work_id":"a7b56c4c-9ba3-4d50-b40e-caded513d6e0","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:31.061800Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:fc7dc57aa09831458aae5e49bb4cdb54db39e7d5a30288c66f04bc0cc265fa82","observation_id":"dd7c32f8-8c38-42ce-9d29-3f7570953fbb","resolution":{"observed_at":"2026-08-07T11:26:31.606453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:31.448396Z","title":"This shows that our choice of using likelihood of final GT answer for selecting winner ra- tionale aligns with human preferences and is suitable to obtain the preference data","venue":null,"work_id":"6881c94f-d5b9-4e1e-95cc-9838ed7ec348","year":2024},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:31.137030Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:3dc183e0d408af0614253cb5ff8c21eb2501d1cba81e9bdb43917a55611cc3cb","observation_id":"66785ae3-7dcc-4c78-8803-f292447672f6","resolution":{"observed_at":"2026-08-07T11:26:31.500289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:26:31.343164Z","title":"The results are summarized in Table 14, where Table 14: Performance comparison of COLLATE with SPIN on additional benchmarks","venue":null,"work_id":"ea494741-b694-4ff3-aaea-58e50b218ba1","year":null},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:31.204976Z"},"links":{"citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:6949681c1b5a953a2309cc18673164e5a7f103c41023a5ca3228b700d67dea72","observation_id":"8dd4c841-36eb-4c66-8130-9ba0aab6223a","resolution":{"observed_at":"2026-08-07T11:26:31.408499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10683","last_updated":"2023-09-19T15:14:48Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-10-23T17:37:36Z","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10683","snapshot_observed_at":"2026-08-07T11:26:30.050480Z","title":"InAdvances in Neural Information Processing Systems, volume 36, pages 53728–53741","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:30.050480Z"},"links":{"cited_paper":"/paper/1910.10683","citing_paper":"/paper/2506.02519"},"observation_digest":"sha256:874017eac3b7f29dd7ae31e612f7c83d8f83f5dd58a38616ae37bbf1213139e1","observation_id":"ae6e3fa3-400b-46ea-91df-c96822058fb8","resolution":{"observed_at":"2026-08-07T11:26:30.050480Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.02519","last_updated":"2025-06-03T06:50:08Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T11:19:56.571148Z","submitted_at":"2025-06-03T06:50:08Z","title":"Learning Together to Perform Better: Teaching Small-Scale LLMs to Collaborate via Preferential Rationale Tuning"},"reference_resolution":{"displayed":16,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":0,"verified_fuzzy":11},"total_outbound_references":16},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 2 inbound Pith citation observations for arXiv:2506.02519."}