{"as_of":"2026-08-09T17:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2ff96b66f979f4d05032a2770bb724e3703d951a04310ed0e08bcd8c1ff96077","coverage":[{"denominator":31,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T10:21:34.571829Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.20265/citation-record","integrity":"/paper/2607.20265/integrity","json":"/paper/2607.20265/citation-record.json","paper":"/paper/2607.20265"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T10:21:32.122764Z","title":"Comet: Commonsense transformers for automatic knowledge graph con- struction","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.122764Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:4870223b489c47fbf8a30016b7c1e63d3be5796ac01afa0ea790f1c78984f220","observation_id":"1f046a00-f447-47e3-9b80-2f552a4828ef","resolution":{"observed_at":"2026-08-01T10:21:32.122764Z","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":"2026-08-01T10:21:32.172921Z","title":"Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.172921Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:1d1df537e910fe520915290ba254009aface4e525c9ab69bf7ba97982ac008ce","observation_id":"de5ba480-6885-40e4-99c0-33a6b3f058f0","resolution":{"observed_at":"2026-08-01T10:21:32.172921Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.07065","last_updated":"2022-11-14T01:39:26Z","snapshot_observed_at":"2026-08-07T07:02:37.651759Z","submitted_at":"2022-11-14T01:39:26Z","title":"ALBERT with Knowledge Graph Encoder Utilizing Semantic Similarity for Commonsense Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.07065","snapshot_observed_at":"2026-08-01T10:21:32.244482Z","title":"Albert with knowledge graph encoder utilizing semantic similarity for commonsense question answering","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.244482Z"},"links":{"cited_paper":"/paper/2211.07065","citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:f59fd930fd875b5616fdafe813523ca945d2e1b56645847df66dca672734d543","observation_id":"54be14ef-d0ca-4c9c-b04c-ed485fcb4022","resolution":{"observed_at":"2026-08-01T10:21:32.244482Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13464","last_updated":"2026-04-20T06:13:59Z","snapshot_observed_at":"2026-07-06T20:39:02.049006Z","submitted_at":"2025-02-19T06:31:06Z","title":"Estimating Commonsense Plausibility through Semantic Shifts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13464","snapshot_observed_at":"2026-08-01T10:21:32.318061Z","title":"Estimating commonsense plau- sibility through semantic shifts.arXiv preprint arXiv:2502.13464, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.318061Z"},"links":{"cited_paper":"/paper/2502.13464","citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:a46de52506e3ca72c19da839d3eafffc8bb02299fc0dc99d800b95960122724c","observation_id":"7ca305b1-d524-4bf8-93f2-faedac98de16","resolution":{"observed_at":"2026-08-01T10:21:32.318061Z","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":"2026-08-01T10:21:32.377638Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.377638Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:bc7d7ad949acee3a965f0ec53128f129390415deaf6e4626c54a16c934052b39","observation_id":"710ad39b-9d24-4fed-b3bb-6e2414964567","resolution":{"observed_at":"2026-08-01T10:21:32.377638Z","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":"2026-08-01T10:21:32.438738Z","title":"Bert: Pre-training of deep bidirectional transformers for language understanding","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.438738Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:d75467495afd7311200fa389d32b78e8c87e4ce10118fd80bf9f0c4edeb983bd","observation_id":"c1a5b05d-9287-4f05-b0c9-084db3511a1b","resolution":{"observed_at":"2026-08-01T10:21:32.438738Z","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":"2026-08-01T10:21:32.509822Z","title":"Making pre-trained language models better few-shot learners","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.509822Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:970e09505977fc07cd37593978f2683f7b4fe3b6d0e74395de1f964fbdb1cd45","observation_id":"6643f1a8-a763-45c1-94cb-06b7d35a24b6","resolution":{"observed_at":"2026-08-01T10:21:32.509822Z","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":"2026-08-01T10:21:32.604101Z","title":"Accent: An automatic event commonsense evaluation metric for open-domain dialogue systems","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.604101Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:beeb8b64f4ccff78caa4184e1a2987f5ce61e576422d6252a81b9833c91f2eb8","observation_id":"2562136e-f324-46a9-bc58-4188a6b43ec5","resolution":{"observed_at":"2026-08-01T10:21:32.604101Z","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":"2026-08-01T10:21:32.661171Z","title":"Hwang, Chandra Bhagavatula, Ronan Le Bras, Jeff Da, Keisuke Sakaguchi, Antoine Bosselut, and Yejin Choi","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.661171Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:11a9be50aa90351c0f02867f2ca5d30dffd9b15db0dccf00bfc203bcd955ef70","observation_id":"bb5c3af6-25da-4d5b-911d-ee75612a25a3","resolution":{"observed_at":"2026-08-01T10:21:32.661171Z","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":"2026-08-01T10:21:32.710595Z","title":"Hwang, Chandra Bhagavatula, Ronan Le Bras, Jeff Da, Keisuke Sakaguchi, Antoine Bosselut, and Yejin Choi","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.710595Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:288321222e57e07e287263bd259cdc2bec06b4c228aa71234ab6957726d76522","observation_id":"8df49e04-c0b1-4f09-b689-593e7126d3a6","resolution":{"observed_at":"2026-08-01T10:21:32.710595Z","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":"2026-08-01T10:21:32.797036Z","title":"Can you tell me how to improve my prompt? learning to rephrase prompts for language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.797036Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:ba342a152aa47b0477d5df2ac1f48a74854d6a3ac23fd9a1cf4543686e5edbe6","observation_id":"db0adfb8-dbc5-45b6-879f-db383c1cfa4e","resolution":{"observed_at":"2026-08-01T10:21:32.797036Z","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":"2026-08-01T10:21:32.977970Z","title":"Maieutic prompting: Logically consistent reasoning with recursive explanations","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.977970Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:c8e2a66555891d3157dd5d74e07c9bf148e257338d1d5fd710de275d5ad66b77","observation_id":"cda01f95-2fea-4f49-98ca-71a26bc70a47","resolution":{"observed_at":"2026-08-01T10:21:32.977970Z","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":"2026-08-01T10:21:33.060146Z","title":"Smith, Yejin Choi, and Hannaneh Hajishirzi","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.060146Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:e77a93bb185caaf2805698f9955b1b8fad24b7a48d175c526fd618d17fe6492d","observation_id":"179cd6b4-991a-4231-b4fe-706591aa46f4","resolution":{"observed_at":"2026-08-01T10:21:33.060146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.13586","last_updated":"2021-07-28T18:09:46Z","snapshot_observed_at":"2026-07-06T11:33:25.933445Z","submitted_at":"2021-07-28T18:09:46Z","title":"Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.13586","snapshot_observed_at":"2026-08-01T10:21:33.122234Z","title":"Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing.arXiv preprint arXiv:2107.13586, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.122234Z"},"links":{"cited_paper":"/paper/2107.13586","citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:d52f45d0790b159d672a7da1946130232c43add49bd36cef5c39b1a82c3b605f","observation_id":"4a5172ea-0bce-4ec9-8fda-941dbcd88e34","resolution":{"observed_at":"2026-08-01T10:21:33.122234Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.07170","last_updated":"2021-03-12T09:40:49Z","snapshot_observed_at":"2026-08-04T17:26:21.704629Z","submitted_at":"2021-03-12T09:40:49Z","title":"Constrained Text Generation with Global Guidance -- Case Study on CommonGen","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.07170","snapshot_observed_at":"2026-08-01T10:21:33.177999Z","title":"Constrained text gen- eration with global guidance: Case study on commongen.arXiv preprint arXiv:2103.07170, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.177999Z"},"links":{"cited_paper":"/paper/2103.07170","citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:d807f7eb6520c265002360f43ec6fb9a240c393c458a1bae2bb82caf2adca431","observation_id":"3d7ca722-7bad-4264-be60-ce022f77f124","resolution":{"observed_at":"2026-08-01T10:21:33.177999Z","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":"2026-08-01T10:21:33.258779Z","title":"A robustly optimized bert pre-training approach with post-training","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.258779Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:7da2e8650f804fa95c4f6cc3b030e1319ed240bda337de92ac91a57d69a5c8cc","observation_id":"af3744ed-9d5b-40cb-8c85-768b4d0984de","resolution":{"observed_at":"2026-08-01T10:21:33.258779Z","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":"2026-08-01T10:21:33.329422Z","title":"Language models as knowledge bases? InProceedings of the 2019 Conference on Empirical Methods in Natural Language Processing, pages 2463–2473, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.329422Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:f072be2df82ce992ee9d1f746474338979ef7a610112dc60381ad845909b1a29","observation_id":"31029836-4994-4f6d-8110-4f4e55cd50f5","resolution":{"observed_at":"2026-08-01T10:21:33.329422Z","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":"2026-08-01T10:21:33.423282Z","title":"Matching tasks to objectives: Fine-tuning and prompt-tuning strategies for encoder-decoder pre-trained language models.Applied In- telligence, 54(20):9783–9810, Oct 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.423282Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:c3f8598080914b9eaeb925e1312affa731f2b9abf663d9080061bd2e39da62a0","observation_id":"6e723fd8-6f9a-4ace-bae4-cd762478759d","resolution":{"observed_at":"2026-08-01T10:21:33.423282Z","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":"2026-08-01T10:21:33.501612Z","title":"Language models are unsupervised multitask learners","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.501612Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:ce873e8bc0f067eef503ed241601b1265a6f203af522467c1be8cca4003f8f14","observation_id":"bf916198-9a70-4c0b-8260-13eba0a49b62","resolution":{"observed_at":"2026-08-01T10:21:33.501612Z","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":"2026-08-01T10:21:33.559242Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.559242Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:5d37cd1b9dc93d3c09f1e0a6a0300a7a2bac484f981749adf357ab649203f5d0","observation_id":"3ffd41d7-715b-407a-a279-a398713e430b","resolution":{"observed_at":"2026-08-01T10:21:33.559242Z","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":"2026-08-01T10:21:33.632616Z","title":"Smith, and Yejin Choi","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.632616Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:7f61a83c0ed3ed06118a60908b51f651fd5c5f8d049b4897434b21572a74af84","observation_id":"b26012d0-a5de-4d79-977c-8ce250434b8b","resolution":{"observed_at":"2026-08-01T10:21:33.632616Z","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":"2026-08-01T10:21:33.757201Z","title":"Auto- prompt: Eliciting knowledge from language models with automatically generated prompts","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.757201Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:6d3c0a4ccdcf141a419a23c3503fea4daadd91d07e41e80509a009510b68a849","observation_id":"4d62c9ce-3679-4e2c-b6f8-f921104a0cdd","resolution":{"observed_at":"2026-08-01T10:21:33.757201Z","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":"2026-08-01T10:21:33.855040Z","title":"Conceptnet 5.5: An open multilingual graph of general knowledge","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.855040Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:a8287df29fbf7605486e54aeab32e23febad607106f42381daaaf48c721f76fd","observation_id":"36a7a092-f4a9-4c75-bbd7-0ce3ef61b6f7","resolution":{"observed_at":"2026-08-01T10:21:33.855040Z","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":"2026-08-01T10:21:33.985041Z","title":"Entailer: Answering questions with faithful and truthful chains of reasoning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:33.985041Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:96d1cdf35be90f49dcbb5c4dfcd89a50b3a2337999da882007246ea6d4d8ffa1","observation_id":"30764f6a-ae38-434c-9e0c-7d733532ab53","resolution":{"observed_at":"2026-08-01T10:21:33.985041Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.05131","last_updated":"2023-02-28T17:20:36Z","snapshot_observed_at":"2026-08-08T23:22:00.655876Z","submitted_at":"2022-05-10T19:32:20Z","title":"UL2: Unifying Language Learning Paradigms","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.05131","snapshot_observed_at":"2026-08-01T10:21:34.064126Z","title":"Ul2: Unifying lan- guage learning paradigms.arXiv preprint arXiv:2205.05131, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:34.064126Z"},"links":{"cited_paper":"/paper/2205.05131","citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:eb9f536fd94ec762dffdb0afecf7542320f4a9158bea07b5207ab7d95c272130","observation_id":"eafb73b0-1662-4507-8e8d-942791d59370","resolution":{"observed_at":"2026-08-01T10:21:34.064126Z","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":"2026-08-01T10:21:34.170947Z","title":"Harnessing black-box control to boost com- monsense in lms’ generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:34.170947Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:4ff4b358c6ceff869e655ca40d815a1b31be88379324ffc35d32bdf048d07aeb","observation_id":"2e1dfc2c-e10c-461e-86a4-dc386da82992","resolution":{"observed_at":"2026-08-01T10:21:34.170947Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.02847","last_updated":"2019-09-26T22:33:06Z","snapshot_observed_at":"2026-07-06T06:43:37.618154Z","submitted_at":"2018-06-07T18:13:08Z","title":"A Simple Method for Commonsense Reasoning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.02847","snapshot_observed_at":"2026-08-01T10:21:34.280281Z","title":"Trinh and Quoc V","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:34.280281Z"},"links":{"cited_paper":"/paper/1806.02847","citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:3dc68722bcd8ef3901297f807270497f77efdea73ce8dca115e637f20f311b35","observation_id":"70c301b5-9b7e-4001-bac3-f333150bd8b9","resolution":{"observed_at":"2026-08-01T10:21:34.280281Z","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":"2026-08-01T10:21:34.388923Z","title":"Retrieval augmentation for commonsense reasoning: A unified approach","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:34.388923Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:775db77f26ca3f535a7d5669caa6e1cc133b1fe7d9556798248d01a7db89563a","observation_id":"17311912-8ea0-47e1-9e0d-e80793a117f2","resolution":{"observed_at":"2026-08-01T10:21:34.388923Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.13607","last_updated":"2021-05-31T13:09:19Z","snapshot_observed_at":"2026-08-04T04:04:46.199567Z","submitted_at":"2021-05-28T06:26:19Z","title":"Alleviating the Knowledge-Language Inconsistency: A Study for Deep Commonsense Knowledge","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.13607","snapshot_observed_at":"2026-08-01T10:21:34.457948Z","title":"Alleviating the knowledge-language inconsistency: A study for deep commonsense knowledge.arXiv preprint arXiv:2105.13607, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:34.457948Z"},"links":{"cited_paper":"/paper/2105.13607","citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:ccb1c9a7756c8a30f238688bcf57e2302ac6a9d81d5db91aa759f2edf636e147","observation_id":"9f77645e-80e9-479b-986b-4123c98dac47","resolution":{"observed_at":"2026-08-01T10:21:34.457948Z","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":"2026-08-01T10:21:34.571829Z","title":"Large language models as commonsense knowl- edge for large-scale task planning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:34.571829Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:94c64decd7bd903ed7360fe9f703474371a829745ea3a4e815c4521e23f29fc5","observation_id":"598cec4a-460a-43ec-b358-62bffe944352","resolution":{"observed_at":"2026-08-01T10:21:34.571829Z","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":"2026-08-01T10:21:32.879418Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models","version":1},"reference_index":5936,"source":"pdf_text","source_observed_at":"2026-08-01T10:21:32.879418Z"},"links":{"citing_paper":"/paper/2607.20265"},"observation_digest":"sha256:0618df534d8ba66c4dac72a9d7e5d8bae88016e4e6bb98cbfc1bfc866f5456fb","observation_id":"d60dc88c-c354-427e-91cb-871c0357482e","resolution":{"observed_at":"2026-08-01T10:21:32.879418Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.20265","last_updated":"2026-07-22T15:19:23Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-08T23:22:20.939354Z","submitted_at":"2026-07-22T15:19:23Z","title":"The Maskability Index: Predicting Task-Objective Alignment in Pretrained Language Models"},"reference_resolution":{"displayed":31,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":31,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":31},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2607.20265."}