{"as_of":"2026-08-16T21:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c5d6a46ff0a802faede24c5bf40e562b1cb945d54bea81b43f566a7a44f3b13e","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T22:36:15.782162Z","state":"measured"},{"denominator":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/2506.21211/citation-record","integrity":"/paper/2506.21211/integrity","json":"/paper/2506.21211/citation-record.json","paper":"/paper/2506.21211"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:36:13.677475Z","title":"A systematic literature review on large language models for automated program repair,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:13.677475Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:9221aa464027fc73a817b6061f461894663ce257cb45514e72ef71b6c509e586","observation_id":"5ed40406-0e53-42fc-8107-95f75c07f61e","resolution":{"observed_at":"2026-08-06T22:36:13.677475Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.16708","last_updated":"2025-09-12T01:53:59Z","snapshot_observed_at":"2026-08-16T18:51:03.933174Z","submitted_at":"2024-10-22T05:25:54Z","title":"Atomic Fact Decomposition Helps Attributed Question Answering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.16708","snapshot_observed_at":"2026-08-06T22:36:13.765853Z","title":"Atomic fact decomposition helps attributed question answering,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:13.765853Z"},"links":{"cited_paper":"/paper/2410.16708","citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:fc8c5c53d14d8b0be0e9a3ea1ce7abe5b5c08812ff26606b23bb1608b23e8016","observation_id":"f490f2ae-dee8-4f2e-97d6-7d8cc40ef114","resolution":{"observed_at":"2026-08-06T22:36:13.765853Z","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":"2026-08-06T22:36:19.344415Z","title":"Nmt vs mlm: Which is the best paradigm for apr?","venue":null,"work_id":"c393b718-df9f-4ecb-b8f0-c3e388cac87c","year":2024},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:13.831156Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:798f823db5218c8ecdea43d61fd106527cabec5112e6c1c428091141b1201603","observation_id":"3c6e5f97-0ebc-496e-a924-df5e226afdb8","resolution":{"observed_at":"2026-08-06T22:36:19.406391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:19.185969Z","title":"Rap-gen: Retrieval- augmented patch generation with codet5 for automatic program repair,","venue":null,"work_id":"75f116dd-f7fe-414d-9f8a-3f02b2180d1b","year":2023},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:13.895232Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:0a8eb7d98b59fead60f51cf7dd97a57ab3e45a7abcc1fe1bcc84edb5032356a8","observation_id":"d9e8c19e-8f53-4348-9e83-d54471e9d820","resolution":{"observed_at":"2026-08-06T22:36:19.250062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:19.056824Z","title":"Applying codebert for automated pro- gram repair of java simple bugs,","venue":null,"work_id":"7027114a-5318-40e3-9667-2421a2e4e5a5","year":2021},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:13.982404Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:a2e3867ffa9053bf8cd7076cc0b87e943e032984acef859f76529ecc9fe1b5cb","observation_id":"04866a94-279a-4763-86d8-e49df1ca079c","resolution":{"observed_at":"2026-08-06T22:36:19.114265Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:18.888143Z","title":"CodeT5+: Open code large language models for code understanding and generation,","venue":null,"work_id":"799afc5e-5c9c-49f4-8fb6-3a7aea46ea4e","year":2023},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.045676Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:33bf6c39f79411feb1ed8fb67d761ed3621bf04a9bfa8ad01949a84d2dc10a00","observation_id":"4a8d8d06-cc44-4254-8ee2-af6d32c961dd","resolution":{"observed_at":"2026-08-06T22:36:18.982800Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:18.747965Z","title":"CodeT5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation,","venue":null,"work_id":"8a6298fc-6d01-482a-9f96-37ae46d90975","year":2021},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.098099Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:a002bdc3043ffad210e0aeabb17d490c85ec5ef306f96d92d1a96131f5aa46c7","observation_id":"d639a6d7-44df-4043-94bb-25876f2dbe3f","resolution":{"observed_at":"2026-08-06T22:36:18.815530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:18.570076Z","title":"CodeBERT: A pre-trained model for programming and natural languages,","venue":null,"work_id":"2d0a79c5-9c28-4f34-8ea9-116e5c86fedb","year":2020},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.168135Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:4986be7bb46a445fd0324d76e20c12c507a2ffda933b2e0f0ccbf2e12d80651a","observation_id":"7863f5ea-6e7c-4f92-8da3-eaa4a4b38f84","resolution":{"observed_at":"2026-08-06T22:36:18.646350Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:18.425816Z","title":"Less training, more repairing please: revisiting automated program repair via zero-shot learning,","venue":null,"work_id":"7407ec14-b882-4dd4-a962-6f0cb697a1f8","year":2022},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.222167Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:cc091f45c6e1eb2035b0e4937804151bb17cadc27b4a1ca8b3a70cb64fc6eb7f","observation_id":"5c9fd7a3-43a6-4737-8dd8-15732791a78f","resolution":{"observed_at":"2026-08-06T22:36:18.497438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:18.243600Z","title":"Gamma: Revisiting template-based automated program repair via mask predic- tion,","venue":null,"work_id":"e8fe7309-63ff-41dd-8992-294284f66eff","year":2023},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.273599Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:efe445561c7bae09c756d01ab3b3136077c4c0b65d2a7a8cc24f6fa77ddd0667","observation_id":"3a7ec488-b126-4854-9e76-08c72cef0255","resolution":{"observed_at":"2026-08-06T22:36:18.342306Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:18.121269Z","title":"Automated program repair via conversation: Fixing 162 out of 337 bugs for 0.42 each using chatgpt,","venue":null,"work_id":"04203e94-f117-457a-a110-846e688dcc64","year":2024},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.335730Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:138e155db2835675bed8e76d8e15827c764679a6f850e8aed3a39e44052bfd66","observation_id":"b81d3864-6394-4390-9a21-bb4de65bdedc","resolution":{"observed_at":"2026-08-06T22:36:18.179989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:17.967109Z","title":"Using tree-of-thought prompting to boost chatgpt’s reason- ing,","venue":null,"work_id":"a4c51ac1-ce63-4dfe-942b-2ab583d3ec3f","year":2023},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.418521Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:aa2628e70f243e71d2046d8eb79089b0b686125544fcfceb49ae3395217fb812","observation_id":"2501d07f-71cb-4667-8275-cfc2e763b7c5","resolution":{"observed_at":"2026-08-06T22:36:18.046752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:17.818463Z","title":"Plan-and-solve prompting: Improving zero-shot chain-of-thought reasoning by large language models,","venue":null,"work_id":"3d4a60f3-c645-436b-9bb0-409651f96a5e","year":2023},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.479764Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:4c3dcee2283f129c78437ecf8a98636053ff53b38b1e78a6f68f1b6f3fa4adf3","observation_id":"ec468004-9dd4-471f-8941-b97d97d3555b","resolution":{"observed_at":"2026-08-06T22:36:17.887323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:17.664538Z","title":"Large language models as analogical reasoners,","venue":null,"work_id":"d3cacfe6-bd52-4c1e-91cf-7beb654cb10d","year":2024},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.543984Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:4b4da20c03bfbe094c5dde7a3a0c6cd88eeb564ea14c9d504d7db6399887043e","observation_id":"e1c1e0ad-6e37-4d76-a91f-6902062bfa66","resolution":{"observed_at":"2026-08-06T22:36:17.751075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:17.502244Z","title":"Search-based efficient automated program repair using mutation and fault localization,","venue":null,"work_id":"cd95f0a8-2513-46df-885f-328e5d93cbe6","year":2018},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.626559Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:9d04de80672c66e85f1da75d647eed780b379c7d45725881ccef39b5dfad3728","observation_id":"48a2d2bb-1045-4b3b-bb0b-d50a0ccb371b","resolution":{"observed_at":"2026-08-06T22:36:17.585661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:17.358492Z","title":"Speeding up constraint-based program repair using a search-based technique,","venue":null,"work_id":"0565f9b2-cade-4d15-814c-b5e4c3e41c62","year":2022},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.684477Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:0eb3cd83e551782a85cc2c0826b592a5417619157cdab57ee43e9016c55e7e56","observation_id":"b3c2c1c5-998c-4e47-ab73-78e13bb39db1","resolution":{"observed_at":"2026-08-06T22:36:17.438794Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:17.194481Z","title":"Tbar: Revisiting template-based automated program repair,","venue":null,"work_id":"5e3ea57a-c590-4e50-a8a9-e2a87dc2b87f","year":2019},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.735718Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:d18adb38cc78b2eee5d6eb740e51800521a61cfa1ffbbf686863bf27fa474fbe","observation_id":"402bf2a7-65d0-4828-83e0-035049b44429","resolution":{"observed_at":"2026-08-06T22:36:17.274604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:17.013061Z","title":"Dear: A novel deep learning-based approach for automated program repair,","venue":null,"work_id":"93779050-624c-4ce9-9ad0-8e0cd65140f0","year":2022},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.813282Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:130a6f9f6ba57a1af5d0753378b71ffec4d0707d7940baaa6cdeea6173c48c8d","observation_id":"6f8b275d-387d-44c6-ae62-cd8b82d4c069","resolution":{"observed_at":"2026-08-06T22:36:17.100223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.13246","last_updated":"2023-01-30T19:22:36Z","snapshot_observed_at":"2026-08-16T19:06:57.667917Z","submitted_at":"2023-01-30T19:22:36Z","title":"Conversational Automated Program Repair","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.13246","snapshot_observed_at":"2026-08-06T22:36:14.867498Z","title":"Conversational automated program repair,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.867498Z"},"links":{"cited_paper":"/paper/2301.13246","citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:d8313f82332ccdbea9a1b0f7aef4dacc141ee89601f6e4192618c9d0afc5e8da","observation_id":"542144b4-6dab-4a15-9e25-94c31ef3c229","resolution":{"observed_at":"2026-08-06T22:36:14.867498Z","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":"2026-08-06T22:36:14.916043Z","title":"Large language models-guided dynamic adaptation for temporal knowledge graph reasoning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:14.916043Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:37928f10638af66926ba06a8be658b7d70171a31bcb8cf9aef2cf397556992cc","observation_id":"c910974f-af67-45ee-a9f1-5464339811f2","resolution":{"observed_at":"2026-08-06T22:36:14.916043Z","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":"2026-08-06T22:36:16.843877Z","title":"Made: Multicurvature adaptive embedding for temporal knowledge graph completion,","venue":null,"work_id":"22223f02-ef56-4774-ba0a-978ebad8b286","year":2024},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.006956Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:7ccc7481b9a40df000feba11e5a1c15d32ebb3e95be0b928377821a7f97c7bbf","observation_id":"587071dd-e97d-415b-ab96-d85c2af2d045","resolution":{"observed_at":"2026-08-06T22:36:16.918617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:16.653781Z","title":"Ime: Integrating multi-curvature shared and specific embedding for temporal knowledge graph completion,","venue":null,"work_id":"0a26f406-f9ba-4b43-be7c-18895d7c3b7a","year":2024},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.063823Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:937a5fdad003de767c9357d29fd57a91f5af3ae8980af28f55482cd30e4060da","observation_id":"0f9a839c-2c8e-4c13-978b-7459264ab612","resolution":{"observed_at":"2026-08-06T22:36:16.725652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.03374","last_updated":"2021-07-14T17:16:02Z","snapshot_observed_at":"2026-08-08T11:58:24.516369Z","submitted_at":"2021-07-07T17:41:24Z","title":"Evaluating Large Language Models Trained on Code","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.03374","snapshot_observed_at":"2026-08-06T22:36:15.127066Z","title":"Evaluating large language models trained on code,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.127066Z"},"links":{"cited_paper":"/paper/2107.03374","citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:f7fd9db5f1fc2bdc447611b177c97f2957c7992e7c0ac67276d498d212d9d944","observation_id":"421477dd-f45c-4b50-aa25-85af16e442e9","resolution":{"observed_at":"2026-08-06T22:36:15.127066Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.05999","last_updated":"2023-04-09T14:31:40Z","snapshot_observed_at":"2026-08-13T02:34:38.117682Z","submitted_at":"2022-04-12T16:25:26Z","title":"InCoder: A Generative Model for Code Infilling and Synthesis","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.05999","snapshot_observed_at":"2026-08-06T22:36:15.187820Z","title":"Incoder: A generative model for code infilling and synthesis,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.187820Z"},"links":{"cited_paper":"/paper/2204.05999","citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:db12d098c7909b26df3fb3875883d22e8c41ac6401921f1f9a28979732232714","observation_id":"d2bc9946-b002-41d5-92b2-6f7f72739b07","resolution":{"observed_at":"2026-08-06T22:36:15.187820Z","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":"2026-08-06T22:36:15.264213Z","title":"A systematic evaluation of large language models of code,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.264213Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:7be77b1b1eeae2720076e0c6f17fe5e69967277f44858189754acf83b872cb2f","observation_id":"987ec0b2-4a8d-496e-bb66-48929518873b","resolution":{"observed_at":"2026-08-06T22:36:15.264213Z","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":"2026-08-06T22:36:16.504340Z","title":"Prompt programming for large language models: Beyond the few-shot paradigm,","venue":null,"work_id":"3ae3e7a5-5475-4f36-8477-75020ac451f2","year":2021},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.325231Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:e7342702b958197eeb8a20fed9798a2f511650e3c244b057081d19be27315103","observation_id":"32fe3791-0417-4116-87f6-fa2444cf755a","resolution":{"observed_at":"2026-08-06T22:36:16.568332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.07927","last_updated":"2025-03-16T06:23:34Z","snapshot_observed_at":"2026-08-16T14:09:52.485275Z","submitted_at":"2024-02-05T19:49:13Z","title":"A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.07927","snapshot_observed_at":"2026-08-06T22:36:15.373462Z","title":"A systematic survey of prompt engineering in large language models: Techniques and applications,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.373462Z"},"links":{"cited_paper":"/paper/2402.07927","citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:babb98816f576a287d39833e780e860aca83737b25dfb21b39b7e451418a65c1","observation_id":"1652524a-c030-40fc-9f1d-d308bb7779f8","resolution":{"observed_at":"2026-08-06T22:36:15.373462Z","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":"2026-08-06T22:36:15.440083Z","title":"Chain-of-thought prompting elicits reasoning in large language models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.440083Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:36167a271934de9edc594af82f1075f485beae660b87c66b548fb3ad0f5bc73c","observation_id":"bfc164cb-9e7b-4811-86cc-8c80cb0b7e58","resolution":{"observed_at":"2026-08-06T22:36:15.440083Z","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":"2026-08-06T22:36:15.506340Z","title":"Large lan- guage models are zero-shot reasoners,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.506340Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:15da25190319972d26019a22843bc0f8a5155bb76909e0a0bd91d722f24dfa58","observation_id":"13a5f037-fa3b-4c3b-ac93-8a06f830b6e7","resolution":{"observed_at":"2026-08-06T22:36:15.506340Z","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":"2026-08-06T22:36:15.577136Z","title":"Self-consistency improves chain of thought reasoning in language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.577136Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:8f977d9156e7df497f8e8a38a2d7d6d0e2740c53b85f1ed58939cdc6685bd2ac","observation_id":"51f2de1a-1c85-4ebd-aa86-338314b37c6f","resolution":{"observed_at":"2026-08-06T22:36:15.577136Z","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":"2026-08-06T22:36:16.350922Z","title":"Better patching using llm prompting, via self-consistency,","venue":null,"work_id":"426ac331-d5ec-4f10-89ca-dc9178d44668","year":2023},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.637056Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:10d4c10c2adad92539d417b8fdf377854c90b0227c02a17c764802d45940f4a8","observation_id":"0ebb3737-8a47-448e-a614-2321e9de4401","resolution":{"observed_at":"2026-08-06T22:36:16.383919Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:16.212592Z","title":"An empirical study on learning bug-fixing patches in the wild via neural machine translation,","venue":null,"work_id":"ef50dd16-e7fb-4aa5-b2a8-b795c20a3306","year":2019},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.707305Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:8e4c1eea8e2537dd3a58f0dcc0ee2426d10ab45137b1a263abc59c812ad5eb5c","observation_id":"a3cc0672-2a6e-44d5-8374-a733f7858ee1","resolution":{"observed_at":"2026-08-06T22:36:16.290734Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-06T22:36:16.082560Z","title":"Natgen: generative pre-training by “naturalizing","venue":null,"work_id":"9400cdf9-d9a1-4263-92ff-533a627b8784","year":2022},"citing_paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T22:36:15.782162Z"},"links":{"citing_paper":"/paper/2506.21211"},"observation_digest":"sha256:74aec61dd486acb35cd5f74596c67b3f96dcaac74b9d109380ab9546fde110ca","observation_id":"ab3dd0f5-42ac-4565-aaef-157969e149f9","resolution":{"observed_at":"2026-08-06T22:36:16.148602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.21211","last_updated":"2025-06-26T13:04:28Z","latest_version":1,"primary_category":"cs.SE","snapshot_observed_at":"2026-08-16T18:50:10.765390Z","submitted_at":"2025-06-26T13:04:28Z","title":"$T^3$: Multi-level Tree-based Automatic Program Repair with Large Language Models"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":0,"verified_fuzzy":22},"total_outbound_references":33},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2506.21211."}