{"as_of":"2026-08-10T09:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c38cf4427b1b34712bdab29f97d66da016cc2eb2feb3c6f54efc08f5d587140e","coverage":[{"denominator":43,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":43,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T12:41:02.450581Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2502.02315/citation-record","integrity":"/paper/2502.02315/integrity","json":"/paper/2502.02315/citation-record.json","paper":"/paper/2502.02315"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1612.00410","last_updated":"2019-10-23T22:47:44Z","snapshot_observed_at":"2026-07-06T05:21:01.935928Z","submitted_at":"2016-12-01T20:12:40Z","title":"Deep Variational Information Bottleneck","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1612.00410","snapshot_observed_at":"2026-08-09T12:41:02.298836Z","title":"Deep variational information bottleneck","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.298836Z"},"links":{"cited_paper":"/paper/1612.00410","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:5363e15069e2daf7315b20ba9a301d9260763bdeaaf3fbe45a93aaad0b42e285","observation_id":"981fb0b2-22ef-4626-ad76-d02155f21e1f","resolution":{"observed_at":"2026-08-09T12:41:02.298836Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.04023","last_updated":"2023-11-28T09:01:12Z","snapshot_observed_at":"2026-08-07T14:17:12.140094Z","submitted_at":"2023-02-08T12:35:34Z","title":"A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.04023","snapshot_observed_at":"2026-08-09T12:41:02.307783Z","title":"A multitask, multilingual, multimodal evaluation of chatgpt on reasoning, hallucination, and interactivity","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.307783Z"},"links":{"cited_paper":"/paper/2302.04023","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:ea45aff1b59aa440743ad08f9dd52403602924e39927daf852685a32c621a7ad","observation_id":"fe216206-16b1-47d2-b806-730c00d82e4e","resolution":{"observed_at":"2026-08-09T12:41:02.307783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1511.06349","last_updated":"2016-05-12T20:51:23Z","snapshot_observed_at":"2026-08-05T16:42:28.278134Z","submitted_at":"2015-11-19T20:38:45Z","title":"Generating Sentences from a Continuous Space","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.06349","snapshot_observed_at":"2026-08-09T12:41:02.312195Z","title":"Generating sentences from a continuous space","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.312195Z"},"links":{"cited_paper":"/paper/1511.06349","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:420cbfd0c85eb707df940644a6121858813d0bbdcd0739cf649a24085f5e93e3","observation_id":"ecd151f2-5dd0-444b-851e-c0aef24829f4","resolution":{"observed_at":"2026-08-09T12:41:02.312195Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.10668","last_updated":"2024-03-18T23:15:47Z","snapshot_observed_at":"2026-07-06T16:20:36.866744Z","submitted_at":"2023-09-19T14:50:38Z","title":"Language Modeling Is Compression","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.10668","snapshot_observed_at":"2026-08-09T12:41:02.315940Z","title":"Language modeling is compression","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.315940Z"},"links":{"cited_paper":"/paper/2309.10668","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:fc6707c5eec4b18cebe2a55707f1e188a9dfdb3faa26a790e0f7001d9f84a947","observation_id":"61562504-e7e9-479f-aad3-b4c427c2f0e7","resolution":{"observed_at":"2026-08-09T12:41:02.315940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.19555","last_updated":"2024-01-02T22:30:00Z","snapshot_observed_at":"2026-08-09T06:55:53.522370Z","submitted_at":"2023-05-31T04:50:29Z","title":"Large Language Models Are Not Strong Abstract Reasoners","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.19555","snapshot_observed_at":"2026-08-09T12:41:02.319715Z","title":"Large language models are not abstract reasoners","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.319715Z"},"links":{"cited_paper":"/paper/2305.19555","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:1f3284228361d70b6d16bc067dff2bc73105ea4b5e10f02b1405b05dfd7a059a","observation_id":"865017c3-28b8-47f5-9c99-ce0e3b6892b1","resolution":{"observed_at":"2026-08-09T12:41:02.319715Z","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":"2026-08-09T12:41:02.851180Z","title":"Bowman, and Omer Levy","venue":null,"work_id":"6fb959dd-e113-4c94-b9e1-9bc55c0f57aa","year":1935},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.323366Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:87a071a0919c8b564b5629bebbb766da63de0920dc8b760221241ee2ba2a2ab8","observation_id":"1af033cb-8eaf-42db-a59f-58d13e8d6c07","resolution":{"observed_at":"2026-08-09T12:41:02.854479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-07T07:43:16.294957Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-09T12:41:02.330419Z","title":"Lora: Low-rank adaptation of large language models","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.330419Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:08237888cbc66cbbace6f9c67de4e6afdc18ff1f8bd2af6f1328f50a09ee43b7","observation_id":"ac0c1ca0-2ade-47e2-96ee-f1ed22226118","resolution":{"observed_at":"2026-08-09T12:41:02.330419Z","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":"2026-08-09T12:41:02.835175Z","title":"HINT: Hypernetwork instruction tuning for efficient zero- and few-shot generalisation","venue":null,"work_id":"970e9a7a-14f0-4154-ad61-3cf92262ba7e","year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.333788Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:6d6015ba5c1969202ec7a44c70dda545c6c9b7c1516df754521ea0358e09c0cc","observation_id":"ac6d37ff-a77b-442f-a436-8e59bd48da5c","resolution":{"observed_at":"2026-08-09T12:41:02.838693Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6114","last_updated":"2022-12-10T21:04:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2013-12-20T20:58:10Z","title":"Auto-Encoding Variational Bayes","version":11},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6114","snapshot_observed_at":"2026-08-09T12:41:02.336882Z","title":"Auto-encoding variational bayes","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.336882Z"},"links":{"cited_paper":"/paper/1312.6114","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:23ecc9810a3dafa2c451e4f567a26eade8295ae826554dbdbe22ae9dba755087","observation_id":"24329ca8-cc8b-44d4-8b13-934b2f8deb21","resolution":{"observed_at":"2026-08-09T12:41:02.336882Z","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":"2026-08-09T12:41:02.825283Z","title":"Variational dropout and the local reparame- terization trick","venue":null,"work_id":"5a9b15cf-32ea-4eef-84f1-0c1b51302e37","year":2015},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.340169Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:62689a41510746ef33ac9063478fbd091bcac0ceaaed627cc2f515a3e0ce0ced","observation_id":"904575b3-d26f-4cd6-95ce-b510823ee1ba","resolution":{"observed_at":"2026-08-09T12:41:02.828804Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08691","last_updated":"2021-09-02T17:34:41Z","snapshot_observed_at":"2026-08-06T15:24:34.790850Z","submitted_at":"2021-04-18T03:19:26Z","title":"The Power of Scale for Parameter-Efficient Prompt Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08691","snapshot_observed_at":"2026-08-09T12:41:02.343522Z","title":"The power of scale for parameter-efficient prompt tuning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.343522Z"},"links":{"cited_paper":"/paper/2104.08691","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:06b576f97406426b27335d3c9d6d48e8f202649da2e2158dbb66da37196887df","observation_id":"258b4e45-34f6-4ce5-9bc4-503c9e685fec","resolution":{"observed_at":"2026-08-09T12:41:02.343522Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.12382","last_updated":"2025-02-18T15:54:28Z","snapshot_observed_at":"2026-07-06T18:32:48.777640Z","submitted_at":"2024-06-18T08:14:28Z","title":"From Instance Training to Instruction Learning: Task Adapters Generation from Instructions","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.12382","snapshot_observed_at":"2026-08-09T12:41:02.346889Z","title":"From instance training to instruction learning: Task adapters generation from instructions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.346889Z"},"links":{"cited_paper":"/paper/2406.12382","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:2f626dd3e27de76e4941303a2c931fb2e2ac52b96382ed4abade0f09befc583f","observation_id":"e4ec10b5-9ee5-4cd9-ba4c-dc82b24528c7","resolution":{"observed_at":"2026-08-09T12:41:02.346889Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.04721","last_updated":"2023-10-26T01:27:29Z","snapshot_observed_at":"2026-08-08T00:48:24.957345Z","submitted_at":"2023-07-10T17:32:13Z","title":"Large Language Models as General Pattern Machines","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.04721","snapshot_observed_at":"2026-08-09T12:41:02.350367Z","title":"Large language models as general pattern machines","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.350367Z"},"links":{"cited_paper":"/paper/2307.04721","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:ad339b2d4c371f8d26937eb99cb32e8466946c5d69e9bcf5a8ae5a602b5a9755","observation_id":"a4b1ae9d-cee1-4b89-a072-f3172eef6d0e","resolution":{"observed_at":"2026-08-09T12:41:02.350367Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.09247","last_updated":"2023-12-11T23:57:17Z","snapshot_observed_at":"2026-07-06T16:48:09.248740Z","submitted_at":"2023-11-14T04:33:49Z","title":"Comparing Humans, GPT-4, and GPT-4V On Abstraction and Reasoning Tasks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.09247","snapshot_observed_at":"2026-08-09T12:41:02.353826Z","title":"Comparing humans, gpt-4, and gpt-4v on abstraction and reasoning tasks","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.353826Z"},"links":{"cited_paper":"/paper/2311.09247","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:151b5115b28c2da402c424eb69f1e44c371d94a92420c56863e72d61548dede8","observation_id":"17ef531a-2a64-4533-8747-93605bf1ab12","resolution":{"observed_at":"2026-08-09T12:41:02.353826Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.03601","last_updated":"2024-01-07T23:01:56Z","snapshot_observed_at":"2026-08-07T08:24:45.140295Z","submitted_at":"2024-01-07T23:01:56Z","title":"InFoBench: Evaluating Instruction Following Ability in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.03601","snapshot_observed_at":"2026-08-09T12:41:02.357079Z","title":"Infobench: Evaluating instruction following ability in large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.357079Z"},"links":{"cited_paper":"/paper/2401.03601","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:2f9f4b3b94e54ad6cac113bf0b9813f895366cfedc72e9ab8c2bbde53fc71665","observation_id":"94735af9-e993-47f0-9f2a-0734165c463f","resolution":{"observed_at":"2026-08-09T12:41:02.357079Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.08559","last_updated":"2024-05-22T14:35:15Z","snapshot_observed_at":"2026-08-08T15:26:27.022867Z","submitted_at":"2023-10-12T17:51:10Z","title":"Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08559","snapshot_observed_at":"2026-08-09T12:41:02.360552Z","title":"Phenomenal yet puzzling: Testing inductive reasoning capabilities of language models with hypothesis refinement","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.360552Z"},"links":{"cited_paper":"/paper/2310.08559","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:2306391e6a6381d45721dafb8ed0c9ef20cc1e8dc0469a192fc45c9467f3dfb2","observation_id":"b1d529eb-e7b5-4aa6-a015-c9b47890ca4c","resolution":{"observed_at":"2026-08-09T12:41:02.360552Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.08207","last_updated":"2022-03-17T17:53:01Z","snapshot_observed_at":"2026-07-06T11:58:21.596920Z","submitted_at":"2021-10-15T17:08:57Z","title":"Multitask Prompted Training Enables Zero-Shot Task Generalization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.08207","snapshot_observed_at":"2026-08-09T12:41:02.364015Z","title":"Multitask prompted training enables zero-shot task generalization","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.364015Z"},"links":{"cited_paper":"/paper/2110.08207","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:b5eb808ecdb58a1fe9fb420112ddcc210f43fcbde2e7150fa8bdab14b32b5ce8","observation_id":"7efa4000-1b7e-422d-a0e8-4f5532734fbc","resolution":{"observed_at":"2026-08-09T12:41:02.364015Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.05789","last_updated":"2024-03-09T04:20:46Z","snapshot_observed_at":"2026-07-06T17:41:55.780727Z","submitted_at":"2024-03-09T04:20:46Z","title":"ItD: Large Language Models Can Teach Themselves Induction through Deduction","version":1},"cited_work":{"arxiv_id":"2403.05789","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.05789","snapshot_observed_at":"2026-08-09T12:41:02.531514Z","title":"ItD: Large Language Models Can Teach Themselves Induction through Deduction","venue":"cs.CL","work_id":"5b256df5-14a8-4503-9546-6731cdbdaea9","year":2024},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.367871Z"},"links":{"cited_paper":"/paper/2403.05789","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:8cfadee46551ff667e0006e715458185b16e9a4bac1e6c45c31581f21587cad9","observation_id":"bbcca24d-f3e7-402a-b6b1-0f041cc7f342","resolution":{"observed_at":"2026-08-09T12:41:02.536916Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.08440","last_updated":"2024-10-17T07:00:19Z","snapshot_observed_at":"2026-08-10T09:48:43.509866Z","submitted_at":"2024-07-11T12:26:55Z","title":"Beyond Instruction Following: Evaluating Inferential Rule Following of Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.08440","snapshot_observed_at":"2026-08-09T12:41:02.371174Z","title":"Beyond instruction following: Evaluating inferential rule following of large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.371174Z"},"links":{"cited_paper":"/paper/2407.08440","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:bbdb7219f70e183da16a363dd16da06bf1dbabe8c04fffedc0b356bc669d3e33","observation_id":"cd2a23dd-2983-4ffa-bfa5-071455945bde","resolution":{"observed_at":"2026-08-09T12:41:02.371174Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14825","last_updated":"2023-06-08T16:38:51Z","snapshot_observed_at":"2026-07-06T15:32:18.583350Z","submitted_at":"2023-05-24T07:33:34Z","title":"Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.14825","snapshot_observed_at":"2026-08-09T12:41:02.374470Z","title":"Large language models are in-context semantic reasoners rather than symbolic reasoners","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.374470Z"},"links":{"cited_paper":"/paper/2305.14825","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:05e5af73598da7a2f2733c2aa278c5052a21009bf34bfe3117fa156b5b976ae0","observation_id":"ac10b2cc-a062-49f2-9826-2a7eeb29a336","resolution":{"observed_at":"2026-08-09T12:41:02.374470Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-09T12:41:02.377707Z","title":"Llama 2: Open foundation and fine-tuned chat models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.377707Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:7fde7c1655ea97c1dafde44365554b695a096fea74727b5e79300b773d06ec6c","observation_id":"081566b6-2347-4e2b-9545-f0e16b270bcb","resolution":{"observed_at":"2026-08-09T12:41:02.377707Z","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":"2026-08-09T12:41:02.381278Z","title":"Visualizing data using t-sne","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.381278Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:bb4768a55ded6fb1c28b3700ccb8d4b930e185506820f5736a591be5022df4bf","observation_id":"e0f4ab32-9175-41e5-ac44-958bf62de155","resolution":{"observed_at":"2026-08-09T12:41:02.381278Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05660","last_updated":"2024-05-30T23:10:00Z","snapshot_observed_at":"2026-08-09T03:52:15.854870Z","submitted_at":"2023-09-11T17:56:57Z","title":"Hypothesis Search: Inductive Reasoning with Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05660","snapshot_observed_at":"2026-08-09T12:41:02.384501Z","title":"Hypothesis search: Inductive reasoning with language models.arXiv preprint arXiv:2309.05660, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.384501Z"},"links":{"cited_paper":"/paper/2309.05660","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:d214e5687f7c0415192f85b68ef4fa59c3b7a30ea032e9abe61acd5fa24827c1","observation_id":"d59b1dea-3373-4756-bf1a-6ac0eb2e7bac","resolution":{"observed_at":"2026-08-09T12:41:02.384501Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.07705","last_updated":"2022-10-24T07:00:15Z","snapshot_observed_at":"2026-07-06T13:00:53.618234Z","submitted_at":"2022-04-16T03:12:30Z","title":"Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.07705","snapshot_observed_at":"2026-08-09T12:41:02.388039Z","title":"Super-naturalinstructions: Generalization via declarative instructions on 1600+ nlp tasks","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.388039Z"},"links":{"cited_paper":"/paper/2204.07705","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:8075e9087e25a9a6eccc2b70c0c3efca79ed4d0b7e234de2531e4686c77b1d65","observation_id":"e0e56dd4-8ead-4551-9660-ded5cbaa64b7","resolution":{"observed_at":"2026-08-09T12:41:02.388039Z","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":"2026-08-09T12:41:02.809201Z","title":"Llm-driven instruction following: Progresses and concerns","venue":null,"work_id":"e85f6eaf-5cb0-4ba5-8199-7f367192f838","year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.391688Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:3e0b74f355668b3fb6cd1ef4e61690913fc0aa9357e3dae3f8f27bcedd6ad935","observation_id":"1d53ab08-d0c3-4a35-b1fe-fd5a11296c80","resolution":{"observed_at":"2026-08-09T12:41:02.812623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.07911","last_updated":"2023-11-14T05:13:55Z","snapshot_observed_at":"2026-07-06T16:47:08.877195Z","submitted_at":"2023-11-14T05:13:55Z","title":"Instruction-Following Evaluation for Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.07911","snapshot_observed_at":"2026-08-09T12:41:02.398638Z","title":"True\" or “False","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.398638Z"},"links":{"cited_paper":"/paper/2311.07911","citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:965567aee0d1e1365cb85d208b5c84ad846fe2771394e458918241c0b801791f","observation_id":"a638f615-7de5-4b2b-ac58-b411b40684b0","resolution":{"observed_at":"2026-08-09T12:41:02.398638Z","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":"2026-08-09T12:41:02.799252Z","title":"Guidelines: • The answer NA means that the abstract and introduction do not include the claims made in the paper","venue":null,"work_id":"a8e8ecde-35d0-44bd-bb81-4e91a49a8f56","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.401765Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:55ad25ea0ef64a1ef46b2d650d1bc53b9728b8b63890bdebf96e2aa0caa08533","observation_id":"0a0b3e93-3c64-4213-903b-5be3a9b95e9d","resolution":{"observed_at":"2026-08-09T12:41:02.802732Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T12:41:02.789701Z","title":"Limitations","venue":null,"work_id":"a1a66a97-a1cc-4cd0-8b0c-60b67f979ddf","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.405154Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:096ee240dd150a71154834fdf829ae9a67321e6c977815acd7a18e248827a0be","observation_id":"5d977b84-303b-4e36-a5fe-b61e280c9eb3","resolution":{"observed_at":"2026-08-09T12:41:02.792901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T12:41:02.408356Z","title":"Guidelines: • The answer NA means that the paper does not include theoretical results","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.408356Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:b31923202cc858b1eeb94101645f398d5ea2a4622ed2c57bcdc3a54fd86f51b9","observation_id":"e64b5406-8d91-4df8-94f4-6fd7536d2db7","resolution":{"observed_at":"2026-08-09T12:41:02.408356Z","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":"2026-08-09T12:41:02.773986Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"410c19a7-c049-429d-a99a-a9b425a8af49","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.411849Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:5c06110c08c03f80cea1286cfd0e006ea8595cbfff6607543576fa08bdb23f69","observation_id":"da8aaeeb-1b95-4cbe-8d3a-231aa17ea9d5","resolution":{"observed_at":"2026-08-09T12:41:02.777531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T12:41:02.764491Z","title":"Guidelines: • The answer NA means that paper does not include experiments requiring code","venue":null,"work_id":"09faa706-dd75-4547-bf95-6f14deecf136","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.415286Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:f1c634ded24aa3e60c108839be084810d99d794c753eeeda1e4e0e0cd66421da","observation_id":"642ad414-3669-448f-bfc4-844cd085f40d","resolution":{"observed_at":"2026-08-09T12:41:02.767776Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T12:41:02.754743Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"c2ff1230-8f2b-4a8f-918a-81e87776530c","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.418539Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:6bb0c29cee425fad931f06addc553b42d3cace87f775dce27d694ca58e7e7bbb","observation_id":"73958ba9-f511-4874-8ab2-5655318778a8","resolution":{"observed_at":"2026-08-09T12:41:02.758193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T12:41:02.744621Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"c110d53f-8e30-4826-97a3-263f2698aed5","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.421946Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:07c6c7607063463f890dda4f3fc4c9bfb81925c3a8c1ad82d8f3485b11a41742","observation_id":"4d63ba14-12f6-4d77-952e-8d4c3896f7c7","resolution":{"observed_at":"2026-08-09T12:41:02.748079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T12:41:02.734659Z","title":"Guidelines: • The answer NA means that the paper does not include experiments","venue":null,"work_id":"ff8987d8-498c-42a8-9fea-06d6f04000bb","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.425152Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:b4f0ecaf6c59274784f210685a3b69099678feef8d14842b565dfaf738539fb1","observation_id":"b17f39b1-bb16-43ad-9d13-3c3824286f3e","resolution":{"observed_at":"2026-08-09T12:41:02.738114Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T12:41:02.428270Z","title":"Guidelines: • The answer NA means that the authors have not reviewed the NeurIPS Code of Ethics","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.428270Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:a2d0b469f0e30b6ba6609bf014e392843185dd52061fbabcac701fac725fbf81","observation_id":"89b68de8-4c55-40d7-b363-d24cd2ec0c40","resolution":{"observed_at":"2026-08-09T12:41:02.428270Z","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":"2026-08-09T12:41:02.718579Z","title":"We believe its impact should be confined to the academic domain","venue":null,"work_id":"2d4b41d8-89bb-42f4-ba2a-50b480897465","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.431319Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:086c01a27a1214ed71cff2b911b49be19cad12b1ae9ba3ba9ffc73cf75e29b6b","observation_id":"d445bbb6-ebad-459d-85a0-bb1c85ac704c","resolution":{"observed_at":"2026-08-09T12:41:02.722074Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T12:41:02.708674Z","title":"Guidelines: • The answer NA means that the paper poses no such risks","venue":null,"work_id":"713ecb17-7c14-4cef-a9d0-0654ff4f6cc8","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.434541Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:1da4490f931a8027a3c4f0bae7c4a65f7b377ebf2451e8298e10d30d266062f8","observation_id":"9853fc54-f104-427b-b298-2640abeb237d","resolution":{"observed_at":"2026-08-09T12:41:02.712097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T12:41:02.698450Z","title":"Guidelines: • The answer NA means that the paper does not use existing assets","venue":null,"work_id":"7186583c-958f-4508-a577-9fb599e05412","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.437635Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:20ec52c58ac738f5d9a1c9a56875c089c1840833c5622569128f712134df6ffa","observation_id":"74bf5055-bc65-49db-8dbc-db84346f14ed","resolution":{"observed_at":"2026-08-09T12:41:02.702140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-09T12:41:02.688336Z","title":"Guidelines: • The answer NA means that the paper does not release new assets","venue":null,"work_id":"4c773dfa-8683-4057-a00f-23b835f9d157","year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.440842Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:d3f9105b4f9f44d2dddf65fc725d483f735465020698490c12484fc2a48e7381","observation_id":"1ac835b9-d96a-4f1b-aef7-d27a2e196d06","resolution":{"observed_at":"2026-08-09T12:41:02.691780Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T12:41:02.444129Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.444129Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:98c4cf7bedb6c3ac0e2877731e06ec335895153de7bad91107bd11e733d27510","observation_id":"e07fc50b-fb55-493e-8350-14f3e090d04b","resolution":{"observed_at":"2026-08-09T12:41:02.444129Z","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":"2026-08-09T12:41:02.447391Z","title":"Guidelines: • The answer NA means that the paper does not involve crowdsourcing nor research with human subjects","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.447391Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:0f799946b2af23ba722470c0f1a24b32cb5ef790df873a44ad7a7ad5370c2c24","observation_id":"1b6d7758-caca-419b-9cc6-8c7c05bc389c","resolution":{"observed_at":"2026-08-09T12:41:02.447391Z","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":"2026-08-09T12:41:02.667019Z","title":"Answer: [NA] Justification: The core method development in this research does not involve LLMs as any important, original, or non-standard components","venue":null,"work_id":"550f30cb-3fd7-48ed-9ae0-57fb3da03c1e","year":2025},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.450581Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:5d6f27c3b71a84a66da3ead7bebf3886c18897d3346efbe3f09e37a78873a14e","observation_id":"7f2f0d28-3eff-4d66-af74-85b10146115a","resolution":{"observed_at":"2026-08-09T12:41:02.670560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T12:41:02.327137Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models","version":3},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-09T12:41:02.327137Z"},"links":{"citing_paper":"/paper/2502.02315"},"observation_digest":"sha256:5fbee63186064375d0960bc713472c9383d475082a84088b6b959965fb34a2be","observation_id":"a5496679-740f-487f-8646-ceb157ab8ce7","resolution":{"observed_at":"2026-08-09T12:41:02.327137Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.02315","last_updated":"2025-05-16T06:54:01Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-09T20:17:07.037873Z","submitted_at":"2025-02-04T13:36:54Z","title":"Shuttle Between the Instructions and the Parameters of Large Language Models"},"reference_resolution":{"displayed":43,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":26,"verified_exact":1,"verified_fuzzy":16},"total_outbound_references":43},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2502.02315."}