{"as_of":"2026-08-20T18:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3029211de8a6806457d9ef02cd9f32be149396767ceb2661cca70530e04f93a1","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T17:26:09.437091Z","state":"measured"},{"denominator":60,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":60,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+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/2502.05932/citation-record","integrity":"/paper/2502.05932/integrity","json":"/paper/2502.05932/citation-record.json","paper":"/paper/2502.05932"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T17:26:10.348504Z","title":"Road” encompasses three levels of difficulty for self-driving cars: easy, medium, and hard, while “Vehicle","venue":null,"work_id":"5d04fd20-98a9-46a7-bbe6-8eddd6b9d68d","year":2023},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.425011Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:96309ed29721bc9910b310dd4c01d10f57147b882b29b46648d83e64d1d8af41","observation_id":"c68d389e-f948-4cf5-be6b-7578ed29c020","resolution":{"observed_at":"2026-08-08T17:26:10.352249Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.385496Z","title":null,"venue":null,"work_id":"f2000d80-d3eb-4ce4-9016-b8b154fcfb35","year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.413198Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:4252e8b71a3f30013421a580256264846f713894606791e894608a4d0676246c","observation_id":"08614ba3-cb0e-4e75-a533-e715290d6e4b","resolution":{"observed_at":"2026-08-08T17:26:10.388541Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.14548","last_updated":"2023-02-28T04:19:48Z","snapshot_observed_at":"2026-08-18T09:02:07.700200Z","submitted_at":"2022-09-29T04:36:23Z","title":"Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.14548","snapshot_observed_at":"2026-08-08T17:26:09.250585Z","title":"Offline reinforcement learning via high-fidelity generative behavior modeling","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.250585Z"},"links":{"cited_paper":"/paper/2209.14548","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:511a2ea1fa3617f1efea9a5fead79645c68a897c10e31f0235837daddac6726b","observation_id":"1e34ce56-c691-4043-9a86-7da0dad1c6e4","resolution":{"observed_at":"2026-08-08T17:26:09.250585Z","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":"2026-08-08T17:26:10.482880Z","title":"Modularized skills for multitask learning","venue":null,"work_id":"a8bf08c8-ba47-44aa-b416-fe4cf28173ff","year":2020},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.377638Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:9df8d30c07bbe95f9c0fd6eefb59443619965b1a362510edc7c28707374c3ab6","observation_id":"54816bda-3665-4dc7-b267-aaa005dccf8e","resolution":{"observed_at":"2026-08-08T17:26:10.486222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12094","last_updated":"2024-10-27T04:46:58Z","snapshot_observed_at":"2026-08-17T20:42:37.335823Z","submitted_at":"2024-05-20T15:05:47Z","title":"Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?","version":2},"cited_work":{"arxiv_id":"2405.12094","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.12094","snapshot_observed_at":"2026-08-08T17:26:09.984350Z","title":"Is Mamba Compatible with Trajectory Optimization in Offline Reinforcement Learning?","venue":"cs.LG","work_id":"610190c0-9704-433a-ad73-2feb6861592d","year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.257991Z"},"links":{"cited_paper":"/paper/2405.12094","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:a5807146fc976c7897f9b0bb322cec065722c817a58cdf6f034aad47a0415848","observation_id":"8f71172d-919a-4c9a-a7ca-e21d2eb4ba34","resolution":{"observed_at":"2026-08-08T17:26:09.987921Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.330811Z","title":null,"venue":null,"work_id":"24567823-a0ab-4534-b71e-229cbed1dc69","year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.430988Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:ccf817e1dd83e793a8b3207f74bc061c1cdc4baa8fbb002f41f4a92f28c6476e","observation_id":"11d6d900-fb11-4205-9755-36a757d400e2","resolution":{"observed_at":"2026-08-08T17:26:10.333906Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.07219","last_updated":"2021-02-06T01:57:28Z","snapshot_observed_at":"2026-08-16T08:32:46.407746Z","submitted_at":"2020-04-15T17:18:19Z","title":"D4RL: Datasets for Deep Data-Driven Reinforcement Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.07219","snapshot_observed_at":"2026-08-08T17:26:09.265050Z","title":"D4rl: Datasets for deep data-driven reinforcement learning","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.265050Z"},"links":{"cited_paper":"/paper/2004.07219","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:20d6fd98d61b28d41babd9aafd7b59305040730ed643b4ad5b79a42cc59036ae","observation_id":"bdd6247c-8b15-43a3-a745-36ce58d3e245","resolution":{"observed_at":"2026-08-08T17:26:09.265050Z","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":"2026-08-08T17:26:10.474412Z","title":null,"venue":null,"work_id":"e02cff5b-a16f-4011-8f53-6d5567c8eac7","year":1994},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.380816Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:b0d9b9945f5b50ec2924f68e1ff6eb0ac1fd67c413c2ef38260744057a9e23a4","observation_id":"797886f4-8b74-4ac1-85ba-52270e2a2eba","resolution":{"observed_at":"2026-08-08T17:26:10.477648Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.10573","last_updated":"2023-05-19T18:31:04Z","snapshot_observed_at":"2026-08-14T17:40:51.391072Z","submitted_at":"2023-04-20T18:04:09Z","title":"IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.10573","snapshot_observed_at":"2026-08-08T17:26:09.272400Z","title":"Philippe Hansen-Estruch, Ilya Kostrikov, Michael Janner, Jakub Grudzien Kuba, and Sergey Levine","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.272400Z"},"links":{"cited_paper":"/paper/2304.10573","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:12369361790be51d8c8152fef47a11713ad2a81f724f5925290dea640f38f4f3","observation_id":"d2af2f35-d891-4602-94ef-bb549ad3d3b9","resolution":{"observed_at":"2026-08-08T17:26:09.272400Z","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":"2026-08-20T11:47:17.477107Z","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":"2026-08-08T17:26:09.276684Z","title":"Lora: Low-rank adaptation of large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.276684Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:33a4260ef1f633bddac637ac27ba5ac7f75233bbed3b9c1ed8cc820a4fe63eaa","observation_id":"7f621c8a-6c60-48f9-9981-fd59af033c40","resolution":{"observed_at":"2026-08-08T17:26:09.276684Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.08478","last_updated":"2024-04-07T11:29:37Z","snapshot_observed_at":"2026-08-16T14:27:04.703645Z","submitted_at":"2024-01-16T16:28:32Z","title":"Solving Continual Offline Reinforcement Learning with Decision Transformer","version":2},"cited_work":{"arxiv_id":"2401.08478","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.08478","snapshot_observed_at":"2026-08-08T17:26:09.928331Z","title":"Solving Continual Offline Reinforcement Learning with Decision Transformer","venue":"cs.LG","work_id":"67415ed4-6c67-484b-aeca-b578da8d3c4b","year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.284037Z"},"links":{"cited_paper":"/paper/2401.08478","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:a0fa771204a0ea72aa29b2f2dc58faabbb20ee8c7ddf6a7c2499330d613e3743","observation_id":"6827b9b6-28d4-4cd1-bbad-0e14bf6b216f","resolution":{"observed_at":"2026-08-08T17:26:09.931975Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.14785","last_updated":"2024-08-27T05:23:45Z","snapshot_observed_at":"2026-08-16T13:23:37.501478Z","submitted_at":"2024-08-27T05:23:45Z","title":"Unsupervised-to-Online Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.14785","snapshot_observed_at":"2026-08-08T17:26:09.287491Z","title":"Unsupervised-to-online reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.287491Z"},"links":{"cited_paper":"/paper/2408.14785","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:ec3a1a669d622cf501da3931c2b3a436e985ef3b11df349b1233a3db35ab729f","observation_id":"9b2dc2a4-ad80-4a17-a20c-3ee239e61086","resolution":{"observed_at":"2026-08-08T17:26:09.287491Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-08T17:26:09.291203Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.291203Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:61805ac9216871fbafec47eb24c559647b7f8363272f38ba4b21780760dd1561","observation_id":"d2bd19fc-ae44-44e4-a760-f27500f794b4","resolution":{"observed_at":"2026-08-08T17:26:09.291203Z","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":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T17:26:09.899916Z","title":"Daniel Lawson and Ahmed H Qureshi","venue":null,"work_id":"5006cf10-7fe3-4432-91d2-7eecc9863a78","year":2022},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.294419Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:7b3307189e05e570c3c422f8c78a94e66c6e21c8f9e4dd06f722e794db8ac848","observation_id":"da257823-d65a-468d-8c38-f5b0591bfe02","resolution":{"observed_at":"2026-08-08T17:26:09.903434Z","resolver_source":"arxiv_id_nonexistent","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.09303","last_updated":"2023-06-16T17:54:06Z","snapshot_observed_at":"2026-08-16T15:23:34.841529Z","submitted_at":"2023-06-15T17:31:26Z","title":"Datasets and Benchmarks for Offline Safe Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.09303","snapshot_observed_at":"2026-08-08T17:26:09.304205Z","title":"Adaptive advantage-guided policy regularization for offline reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.304205Z"},"links":{"cited_paper":"/paper/2306.09303","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:7d7eacdba2da9635ef06c3007fa52efb8d2ee89e06531c52fa5907df4cd6ed5e","observation_id":"97092806-0863-493d-be61-7e200cb4bf3e","resolution":{"observed_at":"2026-08-08T17:26:09.304205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03029","last_updated":"2025-02-28T12:21:00Z","snapshot_observed_at":"2026-08-16T13:28:15.654041Z","submitted_at":"2024-08-06T08:22:16Z","title":"Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.03029","snapshot_observed_at":"2026-08-08T17:26:09.307525Z","title":"OMPO: A unified framework for RL under policy and dynamics shifts","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.307525Z"},"links":{"cited_paper":"/paper/2408.03029","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:425b7ac0304b52883f6dd40302dcacf6613bebe8fed4c2e364e0522a01dcda59","observation_id":"fc467a6f-ffc3-44be-8255-83d1f2edd583","resolution":{"observed_at":"2026-08-08T17:26:09.307525Z","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":"2026-08-08T17:26:10.554425Z","title":"Meta-neural networks that learn by learning","venue":null,"work_id":"3bfcffa6-d189-4dcb-b424-86c5416c38e8","year":1992},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.310841Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:72b0201af50181dc5a1fda97cc02c472cf40a0a7fa917ce6ee5d2eb77f38546c","observation_id":"07035c32-56ca-4f1f-bc4b-2b044a5be8a1","resolution":{"observed_at":"2026-08-08T17:26:10.557859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:09.317063Z","title":"6892–6903","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.317063Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:285aa4a37d790270a3195af428fa2853b8d60ca95e0c2dd2484807fa758a20b2","observation_id":"b3151623-9879-4888-a597-56dd0502d2c2","resolution":{"observed_at":"2026-08-08T17:26:09.317063Z","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":"2026-08-08T17:26:10.540360Z","title":"Modular deep belief networks that do not forget","venue":null,"work_id":"238b3503-0bf6-4bb2-bd33-d414744a7f64","year":2011},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.320646Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:3b21e31ff292e9341bcf56ce8ff0ae0c57bed5fe487f7f4fe0167fe56ded1206","observation_id":"b2cb53be-0e5f-4e0e-9a73-dd9c1b26b23c","resolution":{"observed_at":"2026-08-08T17:26:10.544003Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13025","last_updated":"2024-12-02T06:40:50Z","snapshot_observed_at":"2026-08-19T05:46:33.841981Z","submitted_at":"2024-10-16T20:33:06Z","title":"LoRA Soups: Merging LoRAs for Practical Skill Composition Tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13025","snapshot_observed_at":"2026-08-08T17:26:09.327285Z","title":"Lora soups: Merging loras for practical skill composition tasks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.327285Z"},"links":{"cited_paper":"/paper/2410.13025","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:857c0539146d03d21b3377a130de118f375c1955fb948b9bae88d0fcb3383b3d","observation_id":"3409346e-700e-43ee-a3c2-7846a08962f7","resolution":{"observed_at":"2026-08-08T17:26:09.327285Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.00588","last_updated":"2024-12-09T21:30:07Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-09-01T02:47:50Z","title":"Diffusion Policy Policy Optimization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.00588","snapshot_observed_at":"2026-08-08T17:26:09.330733Z","title":"Diffusion policy policy optimiza- tion","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.330733Z"},"links":{"cited_paper":"/paper/2409.00588","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:5ef88c9c3c319ecc73152f4d7ec4259acf7eded7cd98c4049200718e0f347292","observation_id":"7dfda73d-c3bd-483a-bca0-9836784701d6","resolution":{"observed_at":"2026-08-08T17:26:09.330733Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.05098","last_updated":"2017-06-15T21:38:12Z","snapshot_observed_at":"2026-08-13T21:53:02.384757Z","submitted_at":"2017-06-15T21:38:12Z","title":"An Overview of Multi-Task Learning in Deep Neural Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.05098","snapshot_observed_at":"2026-08-08T17:26:09.334479Z","title":"An overview of multi-task learning in deep neural networks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.334479Z"},"links":{"cited_paper":"/paper/1706.05098","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:e9476c4f2b4886dbe24f156da92e1131ae7e01728a5752df194063b368b615b7","observation_id":"f2575dc7-a734-4256-87cd-f205ed687d81","resolution":{"observed_at":"2026-08-08T17:26:09.334479Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06027","last_updated":"2024-05-02T17:43:34Z","snapshot_observed_at":"2026-08-16T15:40:54.833688Z","submitted_at":"2023-04-12T17:59:41Z","title":"Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06027","snapshot_observed_at":"2026-08-08T17:26:09.337824Z","title":"Continual diffusion: Continual customization of text-to-image diffusion with c-lora","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.337824Z"},"links":{"cited_paper":"/paper/2304.06027","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:18e5e0f886c9ad14f43e613ced7c6a505a7e59147c9df436183fdb59b291ed1c","observation_id":"d5d21ab9-cb2e-4e06-8726-8ea5f0b54574","resolution":{"observed_at":"2026-08-08T17:26:09.337824Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.04354","last_updated":"2022-07-12T15:47:04Z","snapshot_observed_at":"2026-08-18T18:59:34.449108Z","submitted_at":"2022-07-10T00:48:42Z","title":"An Introduction to Lifelong Supervised Learning","version":2},"cited_work":{"arxiv_id":"2207.04354","doi":null,"metadata_source":"pith","pith_arxiv_id":"2207.04354","snapshot_observed_at":"2026-08-08T17:26:09.513748Z","title":"An Introduction to Lifelong Supervised Learning","venue":"cs.LG","work_id":"ab6cc904-3d2e-4f9a-a40a-9decea0de8b9","year":2022},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.341411Z"},"links":{"cited_paper":"/paper/2207.04354","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:a2c193137ff20fd058d960d07606a4e4fc71e9f39b508b00b5ac45bd22f29078","observation_id":"c5f66777-af89-4edf-9027-f92f12275466","resolution":{"observed_at":"2026-08-08T17:26:09.517748Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.521694Z","title":"Paco: Parameter-compositional multi-task reinforcement learning","venue":null,"work_id":"7cca49d2-6e13-417f-907e-ec274721540c","year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.344577Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:0a53ded774b52de8e3e1fe165208b223c2874e517c612163fb9026af8e4e55ce","observation_id":"570fadac-d2d3-42a2-aec1-f2f160ee4624","resolution":{"observed_at":"2026-08-08T17:26:10.525329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1801.00690","last_updated":"2018-01-02T15:48:14Z","snapshot_observed_at":"2026-08-20T08:13:02.541942Z","submitted_at":"2018-01-02T15:48:14Z","title":"DeepMind Control Suite","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.00690","snapshot_observed_at":"2026-08-08T17:26:09.347625Z","title":"Deepmind control suite","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.347625Z"},"links":{"cited_paper":"/paper/1801.00690","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:a1f7f2b4a61d6c5a573969ef215de0c4ec5373cd140847cfb647e1d1af4a8ac3","observation_id":"d6b13d53-5601-4e40-b84a-d9868ee27780","resolution":{"observed_at":"2026-08-08T17:26:09.347625Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.11253","last_updated":"2024-12-15T17:33:56Z","snapshot_observed_at":"2026-08-18T05:33:28.134673Z","submitted_at":"2024-12-15T17:33:56Z","title":"Are Expressive Models Truly Necessary for Offline RL?","version":1},"cited_work":{"arxiv_id":"2412.11253","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.11253","snapshot_observed_at":"2026-08-08T17:26:09.490565Z","title":"Are Expressive Models Truly Necessary for Offline RL?","venue":"cs.LG","work_id":"16968321-1067-40ec-be56-9404379643f2","year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.353856Z"},"links":{"cited_paper":"/paper/2412.11253","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:a3fb2e4a5d7060e61940f0ddde42e888bfd6cf1e5eb3c366cdc6af3681bb3362","observation_id":"3620e8d0-4638-48e8-83e9-587939699848","resolution":{"observed_at":"2026-08-08T17:26:09.495840Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.507998Z","title":"Multi-task reinforcement learning with soft modularization","venue":null,"work_id":"1f15858b-5001-4a95-bc22-838fbf6a002f","year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.357434Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:ac5fcb4bb12bfde3b02ce0c86a3115b44c434f2406e862e01daf4d46d2cfd8c3","observation_id":"48a3d7cc-c28f-4e2d-99c6-17c0ae9b52c0","resolution":{"observed_at":"2026-08-08T17:26:10.510944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.04038","last_updated":"2017-02-17T01:33:17Z","snapshot_observed_at":"2026-08-18T02:39:35.613437Z","submitted_at":"2016-06-13T17:15:43Z","title":"Trace Norm Regularised Deep Multi-Task Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.04038","snapshot_observed_at":"2026-08-08T17:26:09.360779Z","title":"Trace norm regularised deep multi-task learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.360779Z"},"links":{"cited_paper":"/paper/1606.04038","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:783a564706dcaf92a9b3c5fbcf0458a9aec435707585be2110e5625d7026d8fa","observation_id":"c71cad8c-03a6-488e-99fe-bc9a0b3d68e6","resolution":{"observed_at":"2026-08-08T17:26:09.360779Z","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":"2026-08-08T17:26:10.499432Z","title":"• Assumption on the expressiveness of the pretrain policy","venue":null,"work_id":"3cb5be7d-17ca-4e74-99ba-acf25970d368","year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.371218Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:8f04b9fb9af096674a7b6885f94eadb63ba0b3bea206b098ef7d11057a507f07","observation_id":"b61c2d69-6acc-4c34-b6b0-914a55a899ee","resolution":{"observed_at":"2026-08-08T17:26:10.502859Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.491400Z","title":null,"venue":null,"work_id":"a7c8b475-4345-4e97-a4fe-a7137ce808a0","year":2023},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.374492Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:0a16bd8394e7cfe004794334fb96356eceeb08db221afc7be3e55d1b76ef91b6","observation_id":"fc84c329-974d-41b4-9641-44e8002d9d5b","resolution":{"observed_at":"2026-08-08T17:26:10.494094Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.465828Z","title":null,"venue":null,"work_id":"e1a8bb87-298a-4de0-ad81-410158bf1490","year":2022},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.384215Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:bafcafee3c3eb21f31e7b6741d769b862de16ddcc178cff0e7eadc3e35f51922","observation_id":"880b8178-fac5-438d-98bf-88422c317402","resolution":{"observed_at":"2026-08-08T17:26:10.468922Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.456492Z","title":null,"venue":null,"work_id":"6899dc8b-8785-4755-8b24-8b1c55491ace","year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.387611Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:ea376138cd0950d9ec150fa48b0759f2ee9ca8f4d75b9815fc4b985ad762381a","observation_id":"161c4c26-f100-447c-b983-be322d204a1f","resolution":{"observed_at":"2026-08-08T17:26:10.459712Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.446983Z","title":"The modularization method, however, can address this problem fundamen- tally by learning new parameters without disrupting pretrained ones","venue":null,"work_id":"9854bd65-9571-40fd-aab1-149acb078b25","year":1994},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.390630Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:bfce9be7b12c41591e2a5a9fea0967ca6f021c6c6fef703c5af8d7a4545a751e","observation_id":"8cf0037b-f0bd-4e24-a5a7-aeee64ad1cd9","resolution":{"observed_at":"2026-08-08T17:26:10.450689Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.437853Z","title":null,"venue":null,"work_id":"71efdff7-6a9b-40aa-aa7a-59c2538ac074","year":2023},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.393914Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:ca4a62d1c0e40d58b0be6caf490f7b417995d4f303bf186e9830128dff794f73","observation_id":"814d8567-ccaa-46a4-aa21-0e9a1bc8eccf","resolution":{"observed_at":"2026-08-08T17:26:10.441303Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.429567Z","title":"Additionally, Araki et al","venue":null,"work_id":"a615c224-449c-40ae-9a4e-00f1c67b9834","year":2021},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.396885Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:3c96adc5f3ce4f06f98107a9cf89cde9e73961c734a29e1174d8e2bf471203c3","observation_id":"572641dd-c292-4ec1-85df-73427c9e87b9","resolution":{"observed_at":"2026-08-08T17:26:10.432569Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.420810Z","title":"For FISOR (Zheng et al., 2024), CDT (Liu et al., 2023b), COptiDICE (Lee et al., 2022a), CPQ (Xu et al.,","venue":null,"work_id":"3b96429d-4c3c-4563-bac9-57ac7cda3eb9","year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.400447Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:70317bdf3b00982065c3bc3c8851c341b0827a07a7c0df5acaeb13a047164994","observation_id":"085c2e6f-b164-4a7c-99d4-273f11098aa1","resolution":{"observed_at":"2026-08-08T17:26:10.424558Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.411937Z","title":"For NSEC and ASEC results, we only change the compositional stages, and meanwhile keep all other training details the same to ensure a fair comparison","venue":null,"work_id":"4888c701-ba8c-49f7-a3e7-643c0eb459cc","year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.403363Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:e51bab16c3aa47ac2417a0bbda6aac3ae5ef264fc7a3c540181d9cdbf63e2cef","observation_id":"025a08e7-fc26-475f-b349-7b31c66e2c26","resolution":{"observed_at":"2026-08-08T17:26:10.415309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.402899Z","title":"(2024) for the policy learning","venue":null,"work_id":"9b90546e-ff9e-4d2b-9142-576717f8dfcb","year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.406387Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:edbf064df9353728438f64932279c260e3e500d1ba2370477f2ea84993b9d58f","observation_id":"8b5d9df7-6f44-4543-9723-a939442fa1cb","resolution":{"observed_at":"2026-08-08T17:26:10.406190Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.393875Z","title":"We compare PSEC with other composition methods NSEC and ASEC, the Scratch method, and the variant PSEC (MLP)","venue":null,"work_id":"db353f94-0df3-4aab-b7f4-94ae1c947362","year":2023},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.409675Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:024ab985a487341eae1720e8f73dbc28aff66c985dbe150f38d88bf0dfac8bbb","observation_id":"c3bc6b9c-c1b9-41ec-a480-c25c9dd7b144","resolution":{"observed_at":"2026-08-08T17:26:10.397091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.376831Z","title":null,"venue":null,"work_id":"c2b59963-9698-41d4-b6e8-022328bf1a62","year":2020},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.416057Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:cd986a9f9461ac1b4cabc4792dbcfeda7feac9a73ce223d9734c4de4dd6138bb","observation_id":"56049cc3-1f81-4ca1-8476-7780a585343b","resolution":{"observed_at":"2026-08-08T17:26:10.379986Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.367265Z","title":"The baseline results for comparison are sourced from the TSRL paper (Cheng et al., 2023), which reports state-of-the-art performance in these regimes","venue":null,"work_id":"11801320-c540-422a-a376-f7ab847df26c","year":2023},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.418989Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:864130b22daf4bd4e3637f2f356c5d3ef7526829921c9be446a24426ebef9afd","observation_id":"0e96d659-c9f7-4fe4-9b8e-9ea78ce05caa","resolution":{"observed_at":"2026-08-08T17:26:10.370769Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.339646Z","title":"The training datasets are the same as the datasets collected by L2M","venue":null,"work_id":"cbe4c73f-9e71-4d06-9913-2b9bbaeb1f5f","year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.428055Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:e705786cb98eb0ac6d368a1ed34a78f11c4e2bbcce1c84d1a7aef9be8d523801","observation_id":"d518efe5-72bf-4c19-a8f1-7f1aa373ae20","resolution":{"observed_at":"2026-08-08T17:26:10.342931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.321071Z","title":"stand,” “walk,","venue":null,"work_id":"273382f3-f9c3-472b-ad09-11aeeb5a4ba8","year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.434101Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:ca1eb7b5ab92ab77242b9bcfd22959d2c503c9d6af7d6853f8a25aa8c0ea1533","observation_id":"fa712b5b-8952-4163-954b-50b1a8ad5e7e","resolution":{"observed_at":"2026-08-08T17:26:10.324586Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.09359","last_updated":"2021-04-24T22:39:30Z","snapshot_observed_at":"2026-08-15T03:52:49.245753Z","submitted_at":"2020-06-16T17:54:41Z","title":"AWAC: Accelerating Online Reinforcement Learning with Offline Datasets","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.09359","snapshot_observed_at":"2026-08-08T17:26:09.313821Z","title":"Awac: Accelerating online rein- forcement learning with offline datasets","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":1992,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.313821Z"},"links":{"cited_paper":"/paper/2006.09359","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:8e2648db82cc4032a4ef17e671a647da1d2d1e37b9ff27a0a947d0cf7c76bed7","observation_id":"006dce72-8cde-402c-a303-1459295ac7b3","resolution":{"observed_at":"2026-08-08T17:26:09.313821Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.06680","last_updated":"2019-12-13T19:56:40Z","snapshot_observed_at":"2026-08-13T14:13:07.807518Z","submitted_at":"2019-12-13T19:56:40Z","title":"Dota 2 with Large Scale Deep Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.06680","snapshot_observed_at":"2026-08-08T17:26:09.246508Z","title":"Dota 2 with large scale deep reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":1997,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.246508Z"},"links":{"cited_paper":"/paper/1912.06680","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:965356adf26ce28331eac60ee4ff321e2ca1dad7dfa98264ecf876a6e3d34be1","observation_id":"a273efe5-af70-47ae-ba0b-d5526438de78","resolution":{"observed_at":"2026-08-08T17:26:09.246508Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.09461","last_updated":"2022-02-24T18:25:18Z","snapshot_observed_at":"2026-08-16T17:48:24.231069Z","submitted_at":"2021-10-18T16:53:31Z","title":"In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications","version":2},"cited_work":{"arxiv_id":"2110.09461","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.09461","snapshot_observed_at":"2026-08-08T17:26:09.714472Z","title":"In a Nutshell, the Human Asked for This: Latent Goals for Following Temporal Specifications","venue":"cs.AI","work_id":"f9f78bd0-0c3e-45ab-adb5-7f6434fb090f","year":2021},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2006,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.297586Z"},"links":{"cited_paper":"/paper/2110.09461","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:df74c61947d3a3f113459369cf538b2f2a4e5973d39ab66e98ba552631e53551","observation_id":"d5214369-d0f8-472d-be46-0214c161b25b","resolution":{"observed_at":"2026-08-08T17:26:09.718189Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.358209Z","title":"$ 0.25 ×FrictionSource domain Target domain Thigh Size ×","venue":null,"work_id":"5b1a7c80-8cea-4b02-832c-98a3098573de","year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2008,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.421987Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:b1a32cd69fac26df15d1d9d9947a9c032011663445fda36692018d6b787c6e08","observation_id":"0d095663-05ae-4ac6-aa1a-c5893ef035a1","resolution":{"observed_at":"2026-08-08T17:26:10.361702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.531325Z","title":"The ideal continual learner: An agent that never forgets","venue":null,"work_id":"0d7b48a4-36f5-460c-bd69-9bb840c4e9e5","year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2011,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.324086Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:2dc37b4dc1d3890b9d6c484014f5130e51dbdc9394770d7157bb556755a37aa8","observation_id":"e90d89e5-4294-4a80-a1e2-2bac7e516751","resolution":{"observed_at":"2026-08-08T17:26:10.534394Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.10700","last_updated":"2024-01-19T14:05:09Z","snapshot_observed_at":"2026-08-19T18:15:33.231718Z","submitted_at":"2024-01-19T14:05:09Z","title":"Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.10700","snapshot_observed_at":"2026-08-08T17:26:09.364201Z","title":"Policy expansion for bridging offline-to-online reinforce- ment learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2012,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.364201Z"},"links":{"cited_paper":"/paper/2401.10700","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:913778e81f2d60516eee626ae477923e96e7a2f3b1ce1f4647b442eb2840f3d0","observation_id":"b7860f6e-447d-4ea8-b7b0-06377971c912","resolution":{"observed_at":"2026-08-08T17:26:09.364201Z","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":"2026-08-08T17:26:10.311390Z","title":"The lines and shaded areas indicate the averages and standard deviations calculated over 5 random seeds","venue":null,"work_id":"5ee99da1-4c7f-4893-becf-8567044cd97c","year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.437091Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:644648dfc0202b628dc6feba9e8118cbe501fd2dbeaed5223196d0e6a1b10ca6","observation_id":"8fd9fd45-bfbf-4dea-b1c8-db5055dfbcfd","resolution":{"observed_at":"2026-08-08T17:26:10.315122Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:10.564830Z","title":"Intelligent problem-solving as integrated hierarchical reinforcement learning","venue":null,"work_id":"cc677a95-8a76-4c04-85fe-95d505055c65","year":2025},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.261917Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:9033188a9dca062e8cd2cff2dd82324682f3be886f04438aac6bd18a4f819276","observation_id":"c9dda185-61fd-4b5c-9954-52164b39632a","resolution":{"observed_at":"2026-08-08T17:26:10.568514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-08T17:26:09.350898Z","title":"Do- main randomization for transferring deep neural networks from simulation to the real world","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.350898Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:fb9803368f63f15ce65bcd00869f34b4e991fae2147b3dae8f59b025261a34e0","observation_id":"49dbf5f3-12a0-48fa-a614-f4aa52cee14d","resolution":{"observed_at":"2026-08-08T17:26:09.350898Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.07768","last_updated":"2018-12-19T06:07:51Z","snapshot_observed_at":"2026-08-14T17:41:28.353201Z","submitted_at":"2018-12-19T06:07:51Z","title":"Modular meta-learning in abstract graph networks for combinatorial generalization","version":1},"cited_work":{"arxiv_id":"1812.07768","doi":null,"metadata_source":"pith","pith_arxiv_id":"1812.07768","snapshot_observed_at":"2026-08-08T17:26:10.291557Z","title":"Modular meta-learning in abstract graph networks for combinatorial generalization","venue":"cs.LG","work_id":"56fb0335-e1a7-440a-9bbc-fa21b18d5148","year":2018},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.241748Z"},"links":{"cited_paper":"/paper/1812.07768","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:7ca76de8e49896bf7d20da7c0c937aa299cf39bdc54b20e569b10be31bdb4267","observation_id":"e99eb39b-78fe-49da-a655-12dceeeb9cac","resolution":{"observed_at":"2026-08-08T17:26:10.296556Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12639","last_updated":"2024-12-16T15:00:05Z","snapshot_observed_at":"2026-08-16T13:59:33.819217Z","submitted_at":"2024-04-19T05:45:43Z","title":"Data-Incremental Continual Offline Reinforcement Learning","version":3},"cited_work":{"arxiv_id":"2404.12639","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.12639","snapshot_observed_at":"2026-08-08T17:26:09.964778Z","title":"Data-Incremental Continual Offline Reinforcement Learning","venue":"cs.LG","work_id":"bac4382c-d691-4ce0-a8e3-62821824711d","year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.268789Z"},"links":{"cited_paper":"/paper/2404.12639","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:5a6916cc065fd8dd44a3546ce3a8e73949c26c2d5ad14d3d30f591a2d7cb3614","observation_id":"376b62a5-f001-442f-8be6-d3028b2eb648","resolution":{"observed_at":"2026-08-08T17:26:09.968412Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.10662","last_updated":"2024-04-18T04:49:02Z","snapshot_observed_at":"2026-08-16T14:00:27.954852Z","submitted_at":"2024-04-16T15:39:11Z","title":"Continual Offline Reinforcement Learning via Diffusion-based Dual Generative Replay","version":2},"cited_work":{"arxiv_id":"2404.10662","doi":null,"metadata_source":"pith","pith_arxiv_id":"2404.10662","snapshot_observed_at":"2026-08-08T17:26:09.702913Z","title":"Continual Offline Reinforcement Learning via Diffusion-based Dual Generative Replay","venue":"cs.LG","work_id":"9556a391-3aeb-4986-993a-6d9619cc7f75","year":2024},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.300801Z"},"links":{"cited_paper":"/paper/2404.10662","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:5fc5ecae00c4ac21d42934cf556dadef75c9a6fb93101b958afde3e912958da5","observation_id":"401cbddc-5dff-4a2b-83b8-d0ab0978e4ef","resolution":{"observed_at":"2026-08-08T17:26:09.706500Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.13269","last_updated":"2024-08-19T03:31:19Z","snapshot_observed_at":"2026-08-20T05:25:59.382385Z","submitted_at":"2023-07-25T05:39:21Z","title":"LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA Composition","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.13269","snapshot_observed_at":"2026-08-08T17:26:09.280199Z","title":"Lorahub: Effi- cient cross-task generalization via dynamic lora composition","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.280199Z"},"links":{"cited_paper":"/paper/2307.13269","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:53df241e633f06b8bf85ebb8f7c137433e9103fa4fc5cf86fe439212e31c2f78","observation_id":"7b3463b7-b000-46d6-8908-5ec41306d2b8","resolution":{"observed_at":"2026-08-08T17:26:09.280199Z","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":"2026-08-08T17:26:09.254654Z","title":"Scaling offline model-based rl via jointly-optimized world-action model pretrain- ing","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.254654Z"},"links":{"citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:6ce2a1027aef9521554b5a101b45157f8fa326025d56a27238a173b09e106eb1","observation_id":"e2816dd5-8493-4ca9-b21d-c6397ae21122","resolution":{"observed_at":"2026-08-08T17:26:09.254654Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.07113","last_updated":"2019-10-16T00:59:05Z","snapshot_observed_at":"2026-08-02T15:37:37.200292Z","submitted_at":"2019-10-16T00:59:05Z","title":"Solving Rubik's Cube with a Robot Hand","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.07113","snapshot_observed_at":"2026-08-08T17:26:09.236721Z","title":"Solving rubik’s cube with a robot hand","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.236721Z"},"links":{"cited_paper":"/paper/1910.07113","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:80f4a45a4048f5a7d31e8e68fa64a806f22ad93746966ae29663fb232fca1379","observation_id":"ae54135e-6f6d-41fb-bfd3-f61a7c9e53c9","resolution":{"observed_at":"2026-08-08T17:26:09.236721Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.16843","last_updated":"2024-11-19T02:52:45Z","snapshot_observed_at":"2026-08-16T14:15:11.306545Z","submitted_at":"2024-02-26T18:59:18Z","title":"Multi-LoRA Composition for Image Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.16843","snapshot_observed_at":"2026-08-08T17:26:09.368041Z","title":"Ming Zhong, Yelong Shen, Shuohang Wang, Yadong Lu, Yizhu Jiao, Siru Ouyang, Donghan Yu, Jiawei Han, and Weizhu Chen","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-08T17:26:09.368041Z"},"links":{"cited_paper":"/paper/2402.16843","citing_paper":"/paper/2502.05932"},"observation_digest":"sha256:328d9f66d201af3a1bd4760212e114d34eaa8381d5d94d0cbdb4a7facf8904a4","observation_id":"ea8eef2f-1577-4dfc-a3d2-f917ed0d8973","resolution":{"observed_at":"2026-08-08T17:26:09.368041Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.05932","last_updated":"2025-03-16T11:57:19Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T19:14:12.530063Z","submitted_at":"2025-02-09T15:22:38Z","title":"Skill Expansion and Composition in Parameter Space"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":1,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":31,"verified_exact":8,"verified_fuzzy":19},"total_outbound_references":60},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2502.05932."}