{"as_of":"2026-08-14T19:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a3161e8fcd1f79062fc61c30a82db4345f4fa26d12b0bd36227388ebf2e57302","coverage":[{"denominator":19,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":19,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T17:37:13.133120Z","state":"measured"},{"denominator":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+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/2412.00029/citation-record","integrity":"/paper/2412.00029/integrity","json":"/paper/2412.00029/citation-record.json","paper":"/paper/2412.00029"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.02344","last_updated":"2025-03-20T17:37:44Z","snapshot_observed_at":"2026-08-14T14:08:12.445176Z","submitted_at":"2024-11-04T18:14:07Z","title":"Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.02344","snapshot_observed_at":"2026-08-12T17:37:13.038657Z","title":"Seq-VCR: Preventing Collapse in In- termediate Transformer Representations for Enhanced Reasoning, November 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.038657Z"},"links":{"cited_paper":"/paper/2411.02344","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:8371b7c4aa65e305a14cfbc35edef5a43b93cf8ccca115eddc20ab9c162bf527","observation_id":"4dfe7392-4c4f-4440-8190-4cf9cad4a226","resolution":{"observed_at":"2026-08-12T17:37:13.038657Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.06963","last_updated":"2025-07-29T03:57:01Z","snapshot_observed_at":"2026-08-13T00:57:22.384205Z","submitted_at":"2024-03-11T17:47:30Z","title":"The pitfalls of next-token prediction","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.06963","snapshot_observed_at":"2026-08-12T17:37:13.051058Z","title":"The pitfalls of next-token prediction, July 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.051058Z"},"links":{"cited_paper":"/paper/2403.06963","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:240f97225e40e79f5ae54f9d56f6dd79e8bd6df7f560a7305cf8c34df91c18e2","observation_id":"b603b766-1b86-41f7-990f-f439f55ed1c4","resolution":{"observed_at":"2026-08-12T17:37:13.051058Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.09673","last_updated":"2024-09-20T21:21:56Z","snapshot_observed_at":"2026-08-13T00:06:55.915196Z","submitted_at":"2024-05-15T19:27:45Z","title":"LoRA Learns Less and Forgets Less","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.09673","snapshot_observed_at":"2026-08-12T17:37:13.056300Z","title":"Cunningham","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.056300Z"},"links":{"cited_paper":"/paper/2405.09673","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:6936b4e49721b22b34bb87017aba9ede5f31d17153bfe9d31fc7652c0ea1556d","observation_id":"bc05d85c-87e9-43ec-9d4d-d8dc63233340","resolution":{"observed_at":"2026-08-12T17:37:13.056300Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-14T02:43:01.480086Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-12T17:37:13.061080Z","title":"Training Verifiers to Solve Math Word Problems, November 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.061080Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:4422b4803d3a7167189659aa6b6d8ad712488d0f4dd29775ea74d834152a41c4","observation_id":"5e7e02aa-080a-4fef-9ea3-dc19358ddf25","resolution":{"observed_at":"2026-08-12T17:37:13.061080Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-08-13T15:58:13.809876Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-12T17:37:13.066899Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.066899Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:08c1f22e339c32dfd19f5e2a79f87a601a60d4aa96941bf5b8deab8e7170e9c5","observation_id":"12b04ac9-bf12-473b-8b1f-494ab84b1f3b","resolution":{"observed_at":"2026-08-12T17:37:13.066899Z","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":"2026-08-12T17:37:13.483627Z","title":null,"venue":null,"work_id":"d211c656-504b-451e-92f1-85d549931396","year":null},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.072196Z"},"links":{"citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:b94699245c725204a04dbf9b886bd4d28e089f78123781a53adeaabb081e19d7","observation_id":"2d31c8cb-4f29-47d0-bf32-dcbecc0ed953","resolution":{"observed_at":"2026-08-12T17:37:13.488622Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.06654","last_updated":"2024-08-06T21:48:58Z","snapshot_observed_at":"2026-08-14T09:25:42.723726Z","submitted_at":"2024-04-09T23:41:27Z","title":"RULER: What's the Real Context Size of Your Long-Context Language Models?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.06654","snapshot_observed_at":"2026-08-12T17:37:13.081736Z","title":"RULER: What’s the Real Con- text Size of Your Long-Context Language Models?, August 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.081736Z"},"links":{"cited_paper":"/paper/2404.06654","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:5352527d0e58a4e5920f9b096a90a9ba68616cc048d687c6685812caec7ca840","observation_id":"1726a73c-1f23-49b6-9e3f-1796d32ee0ed","resolution":{"observed_at":"2026-08-12T17:37:13.081736Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-11T08:20:29.798517Z","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":"2026-08-12T17:37:13.085869Z","title":"Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.085869Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:230e15cf80a0ea7ff8a03e6afbbf7b623554083779c42d0560d56bf56fd58f44","observation_id":"4517a93b-4424-4a20-842a-815f1485c9d0","resolution":{"observed_at":"2026-08-12T17:37:13.085869Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05463","last_updated":"2023-09-11T14:01:45Z","snapshot_observed_at":"2026-08-02T22:47:03.212781Z","submitted_at":"2023-09-11T14:01:45Z","title":"Textbooks Are All You Need II: phi-1.5 technical report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05463","snapshot_observed_at":"2026-08-12T17:37:13.090152Z","title":"Textbooks Are All You Need II: phi-1.5 technical report, Septem- ber 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.090152Z"},"links":{"cited_paper":"/paper/2309.05463","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:151414561108dc21f698b3f24742c2766fe7475bd4bd60d97d3c34b7a36e9de9","observation_id":"9e3e4810-1e9d-494a-9db6-b339a39cc21c","resolution":{"observed_at":"2026-08-12T17:37:13.090152Z","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":"2026-08-12T17:37:13.467237Z","title":"HashHop: Long Context Evaluation, 2024","venue":null,"work_id":"6da21c70-ba8c-4a53-bc47-9454ecd0dcae","year":2024},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.094437Z"},"links":{"citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:db885ba2b9ff5fdf1bae2d1ae723b4f7f160cb7ad82b64c4f51719b11c378e94","observation_id":"7d5a7532-3fcf-4c4e-b3a0-1be9a0d48c3f","resolution":{"observed_at":"2026-08-12T17:37:13.473227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T17:37:13.452495Z","title":"Language Models are Unsupervised Multitask Learners","venue":null,"work_id":"6bc52e79-7501-4858-a3b5-d4e8c709bb95","year":2019},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.098683Z"},"links":{"citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:db4cb6884200b0ed0d94240b62b4116eeb0b730ffb16761fc47f61535a1f176b","observation_id":"c4ab6a36-7cef-4164-b324-1a70f4dfb949","resolution":{"observed_at":"2026-08-12T17:37:13.458307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T17:37:13.434064Z","title":"The effective rank: A measure of effective dimensionality","venue":null,"work_id":"95ced944-75ad-4eb2-b5de-e9fffef5fa59","year":2007},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.102702Z"},"links":{"citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:08e212e05b22ad82a9b03da273d369192dfab8864eb4f4f3091a5844643c8253","observation_id":"1675f53e-e596-43e0-9361-3b6dbfef5013","resolution":{"observed_at":"2026-08-12T17:37:13.439810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-12T17:37:13.411257Z","title":"Continual Learning of Large Language Models: A Comprehensive Survey, June","venue":null,"work_id":"c4fdb5f1-47eb-4e25-a652-ba6f8dcce31f","year":null},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.106620Z"},"links":{"citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:4f03b45a47f87d650458e7ac2276b22a1bae57765c7a234c5ee3936ecd974153","observation_id":"f2c47aff-6ac2-4c02-b100-9ade80244d43","resolution":{"observed_at":"2026-08-12T17:37:13.417423Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.02903","last_updated":"2024-08-05T03:24:09Z","snapshot_observed_at":"2026-08-13T05:57:30.320737Z","submitted_at":"2023-10-04T15:42:23Z","title":"FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning","version":4},"cited_work":{"arxiv_id":"2310.02903","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.02903","snapshot_observed_at":"2026-08-12T17:37:13.238743Z","title":"FroSSL: Frobenius Norm Minimization for Efficient Multiview Self-Supervised Learning","venue":"cs.LG","work_id":"eda3dc91-7627-4505-b839-eb6070fa6fa5","year":2023},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.115555Z"},"links":{"cited_paper":"/paper/2310.02903","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:7ccc8fe3525d44715deaae403942b7bef7b23e44aaa55a5eeac1ba16641cb8af","observation_id":"023e5d42-90c9-4f2f-af2c-10bf48f9dea0","resolution":{"observed_at":"2026-08-12T17:37:13.246059Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16789","last_updated":"2024-11-25T05:27:13Z","snapshot_observed_at":"2026-08-13T00:22:04.546556Z","submitted_at":"2024-04-25T17:38:57Z","title":"Continual Learning of Large Language Models: A Comprehensive Survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16789","snapshot_observed_at":"2026-08-12T17:37:13.110730Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.110730Z"},"links":{"cited_paper":"/paper/2404.16789","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:8187989bc5c0e7df6b6fd57ef811970d2d8a5f66ab9affb2d3f95cabeb8473bd","observation_id":"7cf2f62d-36df-47fc-bf25-243329eef74d","resolution":{"observed_at":"2026-08-12T17:37:13.110730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.05677","last_updated":"2024-04-25T21:45:35Z","snapshot_observed_at":"2026-08-13T05:05:57.142069Z","submitted_at":"2023-12-09T20:51:48Z","title":"Batched Low-Rank Adaptation of Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.05677","snapshot_observed_at":"2026-08-12T17:37:13.125205Z","title":"Batched Low- Rank Adaptation of Foundation Models, April 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.125205Z"},"links":{"cited_paper":"/paper/2312.05677","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:01da0f05932e6f18133ea2ded23918b14ca2730aa78d7936875f66992f9c5072","observation_id":"77d3875c-0e56-4716-935a-e5d509fac53a","resolution":{"observed_at":"2026-08-12T17:37:13.125205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.07816","last_updated":"2024-03-12T16:54:58Z","snapshot_observed_at":"2026-08-13T00:55:53.127378Z","submitted_at":"2024-03-12T16:54:58Z","title":"Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.07816","snapshot_observed_at":"2026-08-12T17:37:13.120746Z","title":"Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM, March 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.120746Z"},"links":{"cited_paper":"/paper/2403.07816","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:37c237c2adf816911c80ce0e68208f22293df7ab632532ee3e427ff72727e2d5","observation_id":"903710b6-f592-424e-806a-9e58992d768a","resolution":{"observed_at":"2026-08-12T17:37:13.120746Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.17601","last_updated":"2023-11-29T12:53:32Z","snapshot_observed_at":"2026-08-14T07:14:06.084884Z","submitted_at":"2023-11-29T12:53:32Z","title":"Continual Learning with Low Rank Adaptation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.17601","snapshot_observed_at":"2026-08-12T17:37:13.133120Z","title":"Continual Learning with Low Rank Adaptation, November 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.133120Z"},"links":{"cited_paper":"/paper/2311.17601","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:56c4d4ab7c6f8b0d641445f30003dbb89e6362c889704287db8d30f39a0705f4","observation_id":"3c80abb0-db87-4f5e-b303-8f377e29a449","resolution":{"observed_at":"2026-08-12T17:37:13.133120Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.08562","last_updated":"2024-02-13T16:04:21Z","snapshot_observed_at":"2026-08-13T04:19:43.818069Z","submitted_at":"2024-02-13T16:04:21Z","title":"Higher Layers Need More LoRA Experts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.08562","snapshot_observed_at":"2026-08-12T17:37:13.076797Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-12T17:37:13.076797Z"},"links":{"cited_paper":"/paper/2402.08562","citing_paper":"/paper/2412.00029"},"observation_digest":"sha256:84ec4984f2707a1ab6b71c87e3327d03aa894f63d82dc6144dd4f5553bf6408c","observation_id":"973c2bfd-6ec2-4ff1-9dc1-1cf1c6e73fc6","resolution":{"observed_at":"2026-08-12T17:37:13.076797Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.00029","last_updated":"2025-02-05T10:01:29Z","latest_version":2,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-14T07:13:46.626651Z","submitted_at":"2024-11-19T10:51:49Z","title":"Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers"},"reference_resolution":{"displayed":19,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":1,"verified_fuzzy":4},"total_outbound_references":19},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2412.00029."}