{"as_of":"2026-08-08T21:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:29af80b0e3249313c8a5870ec51c04a2ada9d18f17eaf4c5875ac29e504ebd4f","coverage":[{"denominator":38,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":38,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T15:20:32.225118Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2509.20784/citation-record","integrity":"/paper/2509.20784/integrity","json":"/paper/2509.20784/citation-record.json","paper":"/paper/2509.20784"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-04T15:20:32.109848Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.109848Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:da9026a3fedbbcfeea97459479c08a64e26f94f55b453ab9ff0369dfcfe7afaf","observation_id":"0452359f-0be3-4ff1-9f6d-f2358be225e2","resolution":{"observed_at":"2026-08-04T15:20:32.109848Z","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":"2026-08-04T15:20:32.113112Z","title":"Language models can explain neurons in language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.113112Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:737bfbb665912590aaa43932e57c915d363ab23e838d962de77c560ab7803a42","observation_id":"0a1305f3-858e-45b5-996b-a1fd6c7a0a36","resolution":{"observed_at":"2026-08-04T15:20:32.113112Z","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":"2026-08-04T15:20:32.116116Z","title":"Towards monosemanticity: Decomposing language models with dictionary learning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.116116Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:21cf196996c19c1546d346b68fb930d76fb117a23c558cc0bf00ed754167c761","observation_id":"3c068fbf-1946-4573-be3b-0fb6493a3ca0","resolution":{"observed_at":"2026-08-04T15:20:32.116116Z","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":"2026-08-04T15:20:32.119499Z","title":"Language models are few-shot learners","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.119499Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:90b42df0b4d840563d2555569f52051a274e71a661e2c8251a4999bdedcb288c","observation_id":"a93462fa-87a4-4458-b968-399dd64ce0fb","resolution":{"observed_at":"2026-08-04T15:20:32.119499Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.17547","last_updated":"2025-03-21T21:43:28Z","snapshot_observed_at":"2026-08-07T16:44:55.194788Z","submitted_at":"2025-03-21T21:43:28Z","title":"Learning Multi-Level Features with Matryoshka Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.17547","snapshot_observed_at":"2026-08-04T15:20:32.122570Z","title":"Learning multi-level features with matryoshka sparse autoencoders","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.122570Z"},"links":{"cited_paper":"/paper/2503.17547","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:61de0da7011f8015368f093ce996f38abd317c22bb48954f98b25bd1f380e1a8","observation_id":"7a8ad517-1171-4701-8618-4be505441825","resolution":{"observed_at":"2026-08-04T15:20:32.122570Z","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":"2026-08-04T15:20:32.125753Z","title":"Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.125753Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:972005b9df648ab4dcf3ad33034e76bb062cd566f9a442a96adcbc8f6a354c4f","observation_id":"03ef157a-3f20-49d9-a1e1-9269d179e672","resolution":{"observed_at":"2026-08-04T15:20:32.125753Z","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":"2026-08-04T15:20:32.129134Z","title":"Feature hedging: Correlated features break narrow sparse autoencoders","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.129134Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:628dce3af7e2416f33b7163e662cce9d4239f47ce1188711a07feadc4857559e","observation_id":"39dd5bbd-da5f-4b5d-9f17-13ff2ea29192","resolution":{"observed_at":"2026-08-04T15:20:32.129134Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12483","last_updated":"2025-02-27T11:45:30Z","snapshot_observed_at":"2026-08-08T01:25:35.634766Z","submitted_at":"2025-02-18T03:09:55Z","title":"The Knowledge Microscope: Features as Better Analytical Lenses than Neurons","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12483","snapshot_observed_at":"2026-08-04T15:20:32.132190Z","title":"The knowledge microscope: Features as better analytical lenses than neurons","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.132190Z"},"links":{"cited_paper":"/paper/2502.12483","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:e3b8cd0ae2f6b4b8b6171f095d23d462a7c298441837a7b9d1b55fd07e968568","observation_id":"503c4995-2e93-49d5-937e-9b36ee987673","resolution":{"observed_at":"2026-08-04T15:20:32.132190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.08600","last_updated":"2023-10-04T13:17:38Z","snapshot_observed_at":"2026-07-06T16:19:05.495349Z","submitted_at":"2023-09-15T17:56:55Z","title":"Sparse Autoencoders Find Highly Interpretable Features in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.08600","snapshot_observed_at":"2026-08-04T15:20:32.135376Z","title":"Sparse autoencoders find highly interpretable features in language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.135376Z"},"links":{"cited_paper":"/paper/2309.08600","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:e885a270c138b24d52b3e86a90140d1caadfa0d71bdf3520c5f8c389d8da4a91","observation_id":"94de39c8-3f67-40e1-ab48-ce3e6c7d8fa9","resolution":{"observed_at":"2026-08-04T15:20:32.135376Z","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":"2026-08-04T15:20:32.138275Z","title":"Compressed sensing","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.138275Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:1e6598c447aebb3f4bcd2dc314a7c552b647ed778d3f68a88345b725998dd003","observation_id":"7e0d1c14-d098-4fad-a74a-3c149dbe7dd5","resolution":{"observed_at":"2026-08-04T15:20:32.138275Z","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":"2026-08-04T15:20:32.141109Z","title":"The llama 3 herd of models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.141109Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:e01d18cea7ce17682a7e37601d4ce9523f41919c3a388032da8a837eb2cef720","observation_id":"4d69c0c6-c4fb-4581-8c26-789b7f13c488","resolution":{"observed_at":"2026-08-04T15:20:32.141109Z","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":"2026-08-04T15:20:32.147836Z","title":"A mathematical framework for transformer circuits","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.147836Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:0dceef1b50de82250a88a9997d8e9613312a93a46b5d6c5d0102c3892e188dc0","observation_id":"e0d31a77-3c28-4991-8143-90623591692d","resolution":{"observed_at":"2026-08-04T15:20:32.147836Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2209.10652","last_updated":"2022-09-21T20:49:26Z","snapshot_observed_at":"2026-07-06T13:54:56.779166Z","submitted_at":"2022-09-21T20:49:26Z","title":"Toy Models of Superposition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.10652","snapshot_observed_at":"2026-08-04T15:20:32.150924Z","title":"Toy models of superposition","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.150924Z"},"links":{"cited_paper":"/paper/2209.10652","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:a7a01d0d91529426f75030301704b6ff838c36efbd041c60d8871d90a2f5f43b","observation_id":"6cbe8958-da46-41f4-bc88-cc7ab51dbc16","resolution":{"observed_at":"2026-08-04T15:20:32.150924Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.14670","last_updated":"2025-03-25T17:00:02Z","snapshot_observed_at":"2026-08-05T04:15:20.969875Z","submitted_at":"2024-10-18T17:58:53Z","title":"Decomposing The Dark Matter of Sparse Autoencoders","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.14670","snapshot_observed_at":"2026-08-04T15:20:32.153769Z","title":"Decomposing the dark matter of sparse autoencoders","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.153769Z"},"links":{"cited_paper":"/paper/2410.14670","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:ab0f5d9f0f4c1c3c46edf7c3ffbdc1d92ace3900ebdd38c1d11103b589e865e1","observation_id":"97455bb9-7e02-4faf-8851-0e158bf16bed","resolution":{"observed_at":"2026-08-04T15:20:32.153769Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.04093","last_updated":"2024-06-06T14:10:12Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-06-06T14:10:12Z","title":"Scaling and evaluating sparse autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.04093","snapshot_observed_at":"2026-08-04T15:20:32.156732Z","title":"Scaling and evaluating sparse autoencoders","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.156732Z"},"links":{"cited_paper":"/paper/2406.04093","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:d2e3669f533e63cce9af60e2f2de1f981d4e2e970b7a97ea4e528481e68021b4","observation_id":"cec40596-0877-418b-92f2-6a141598e684","resolution":{"observed_at":"2026-08-04T15:20:32.156732Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.14913","last_updated":"2021-09-05T17:32:27Z","snapshot_observed_at":"2026-08-07T23:50:29.977330Z","submitted_at":"2020-12-29T19:12:05Z","title":"Transformer Feed-Forward Layers Are Key-Value Memories","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.14913","snapshot_observed_at":"2026-08-04T15:20:32.159654Z","title":"Transformer feed-forward layers are key-value memories","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.159654Z"},"links":{"cited_paper":"/paper/2012.14913","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:dcbe5e2e9d3bc7a1da2722259a41d636c8908dad5870f4840485f2988a0381bd","observation_id":"5352a3b0-4bb0-49c6-ad7d-c2ee2b106b71","resolution":{"observed_at":"2026-08-04T15:20:32.159654Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.01610","last_updated":"2023-06-02T21:52:17Z","snapshot_observed_at":"2026-08-02T17:50:59.894886Z","submitted_at":"2023-05-02T17:13:55Z","title":"Finding Neurons in a Haystack: Case Studies with Sparse Probing","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.01610","snapshot_observed_at":"2026-08-04T15:20:32.162715Z","title":"Finding neurons in a haystack: Case studies with sparse probing","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.162715Z"},"links":{"cited_paper":"/paper/2305.01610","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:7b4784a8868dbff307ca0e54109e0a799af572c469c09367ad49ff962c1525f9","observation_id":"c0a413f7-9c02-4123-bd2a-7837170e3caa","resolution":{"observed_at":"2026-08-04T15:20:32.162715Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.20526","last_updated":"2024-10-27T17:33:49Z","snapshot_observed_at":"2026-08-05T02:09:50.000836Z","submitted_at":"2024-10-27T17:33:49Z","title":"Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse Autoencoders","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.20526","snapshot_observed_at":"2026-08-04T15:20:32.165968Z","title":"Llama scope: Extracting millions of features from llama-3.1-8b with sparse autoencoders","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.165968Z"},"links":{"cited_paper":"/paper/2410.20526","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:247b017cc6bfebd3bd47103d8cdb96f2cdc7197413ca3e2796f707dae9e4f1c1","observation_id":"f7debc33-1c98-417d-9279-3b3b7223897b","resolution":{"observed_at":"2026-08-04T15:20:32.165968Z","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":"2026-08-04T15:20:32.168939Z","title":"A structural probe for finding syntax in word representations","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.168939Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:87fe86f73a150a505a917677f33fbdff242b604cca010bf924db09da8e968f23","observation_id":"69312b53-c1f1-477a-ade8-6fb620a5647f","resolution":{"observed_at":"2026-08-04T15:20:32.168939Z","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":"2026-08-04T15:20:32.171906Z","title":"Knowledge in superposition: Unveiling the failures of lifelong knowledge editing for large language models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.171906Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:5acc6db50cfd39f62bff6775b2716cd8d02644994fffeaa9c67ab31374bf05bf","observation_id":"3e4a300f-8ce5-4e9f-953b-71a4f732f442","resolution":{"observed_at":"2026-08-04T15:20:32.171906Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.05147","last_updated":"2024-08-19T07:51:05Z","snapshot_observed_at":"2026-08-04T11:44:14.524984Z","submitted_at":"2024-08-09T16:06:42Z","title":"Gemma Scope: Open Sparse Autoencoders Everywhere All At Once on Gemma 2","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.05147","snapshot_observed_at":"2026-08-04T15:20:32.174473Z","title":"Gemma scope: Open sparse autoencoders everywhere all at once on gemma 2","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.174473Z"},"links":{"cited_paper":"/paper/2408.05147","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:62ce9681cdd6793bfad169afa248619808a08d7e8c986684ac26caed6e793bad","observation_id":"889197ce-1165-4e6c-aa70-4a2b7dce9c1c","resolution":{"observed_at":"2026-08-04T15:20:32.174473Z","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":"2026-08-04T15:20:32.177256Z","title":"Locating and editing factual associations in gpt","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.177256Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:0136d708f6f5ddfc959923a76454a457a613191d0951a6dd29077f3b8f445655","observation_id":"8b69a1cf-5ee6-446d-a612-ad4ca2cd43f3","resolution":{"observed_at":"2026-08-04T15:20:32.177256Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.00941","last_updated":"2023-09-07T20:36:48Z","snapshot_observed_at":"2026-07-06T16:13:34.788427Z","submitted_at":"2023-09-02T13:37:34Z","title":"Emergent Linear Representations in World Models of Self-Supervised Sequence Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.00941","snapshot_observed_at":"2026-08-04T15:20:32.180384Z","title":"Emergent linear representations in world models of self-supervised sequence models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.180384Z"},"links":{"cited_paper":"/paper/2309.00941","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:83a475347f76458967fcfe06c0c0844c9a53df08579581551da38682c0b895a3","observation_id":"fa8db5d3-17e2-430c-a5c2-6ca8a5913e43","resolution":{"observed_at":"2026-08-04T15:20:32.180384Z","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":"2026-08-04T15:20:32.183586Z","title":"Feature visualization","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.183586Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:76197fd9113a48e1f2ee9b7c218a1c220ece13137ce2f1afa84e216ef7419af1","observation_id":"6a74ead5-0965-4378-bf18-479be89ff688","resolution":{"observed_at":"2026-08-04T15:20:32.183586Z","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":"2026-08-04T15:20:32.186304Z","title":"Zoom in: An introduction to circuits","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.186304Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:c0cfccf60a430ec599412355131e5375ac8359cf9e85d65d0b82bb0adb2331bb","observation_id":"b19a7e7b-83cc-4f46-887b-8adf80e7f271","resolution":{"observed_at":"2026-08-04T15:20:32.186304Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.13117","last_updated":"2025-01-30T09:15:26Z","snapshot_observed_at":"2026-08-08T17:57:20.329783Z","submitted_at":"2024-11-20T08:21:53Z","title":"Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.13117","snapshot_observed_at":"2026-08-04T15:20:32.189070Z","title":"Compute optimal inference and provable amortisation gap in sparse autoencoders","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.189070Z"},"links":{"cited_paper":"/paper/2411.13117","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:1a0e73e552aa1321ee767d81a298aa82b396a3f7bbf3c5a28a7129055f3fba2e","observation_id":"60780d5f-74a1-4385-9266-7171d2fca26a","resolution":{"observed_at":"2026-08-04T15:20:32.189070Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.03658","last_updated":"2024-07-17T22:24:27Z","snapshot_observed_at":"2026-07-06T16:43:58.947915Z","submitted_at":"2023-11-07T01:59:11Z","title":"The Linear Representation Hypothesis and the Geometry of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.03658","snapshot_observed_at":"2026-08-04T15:20:32.191948Z","title":"The linear representation hypothesis and the geometry of large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.191948Z"},"links":{"cited_paper":"/paper/2311.03658","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:48585d7b169cf9a83ac503da9cf95becb610844ae00887c6d03a5c9b683a5f3d","observation_id":"5a417473-6d8a-484c-883c-d7e9f5247265","resolution":{"observed_at":"2026-08-04T15:20:32.191948Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1909.01066","last_updated":"2019-09-04T09:33:20Z","snapshot_observed_at":"2026-07-06T08:18:37.267833Z","submitted_at":"2019-09-03T11:11:08Z","title":"Language Models as Knowledge Bases?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.01066","snapshot_observed_at":"2026-08-04T15:20:32.195035Z","title":"Language models as knowledge bases? arXiv preprint arXiv:1909.01066, 2019","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.195035Z"},"links":{"cited_paper":"/paper/1909.01066","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:77cee473b392172d69469a2c1ce9cf37835cf849e2963c3e19869a21202195e9","observation_id":"d8745fcc-a4d5-4722-84d1-8267c0386c53","resolution":{"observed_at":"2026-08-04T15:20:32.195035Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16014","last_updated":"2024-04-30T17:54:04Z","snapshot_observed_at":"2026-08-02T10:59:21.418230Z","submitted_at":"2024-04-24T17:47:22Z","title":"Improving Dictionary Learning with Gated Sparse Autoencoders","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16014","snapshot_observed_at":"2026-08-04T15:20:32.198042Z","title":"Improving dictionary learning with gated sparse autoencoders","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.198042Z"},"links":{"cited_paper":"/paper/2404.16014","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:01e0e3b9b19abc99a83a84a160e113c72472451fe9de757077df018d28869b9e","observation_id":"898753f7-4cfd-4a79-8692-d282a20413cb","resolution":{"observed_at":"2026-08-04T15:20:32.198042Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.14435","last_updated":"2024-08-01T17:42:04Z","snapshot_observed_at":"2026-08-08T18:10:15.134088Z","submitted_at":"2024-07-19T16:07:19Z","title":"Jumping Ahead: Improving Reconstruction Fidelity with JumpReLU Sparse Autoencoders","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.14435","snapshot_observed_at":"2026-08-04T15:20:32.200772Z","title":"Jumping ahead: Improving reconstruction fidelity with jumprelu sparse autoencoders","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.200772Z"},"links":{"cited_paper":"/paper/2407.14435","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:e2b1462ff0f979e673cd642c6cd808c5554ed794bbb1206d1caa1dcd1481a2fe","observation_id":"71629dbf-e71a-4909-96da-3041d7b65bcb","resolution":{"observed_at":"2026-08-04T15:20:32.200772Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00118","last_updated":"2024-10-02T15:22:49Z","snapshot_observed_at":"2026-08-02T16:20:09.773989Z","submitted_at":"2024-07-31T19:13:07Z","title":"Gemma 2: Improving Open Language Models at a Practical Size","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00118","snapshot_observed_at":"2026-08-04T15:20:32.203692Z","title":"Gemma 2: Improving open language models at a practical size","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.203692Z"},"links":{"cited_paper":"/paper/2408.00118","citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:4fb506818668ac9475717cacd004a15eea9fb606422a6a9c2b238b347a466792","observation_id":"05de22b5-8ce6-46d0-a199-c16846a2f783","resolution":{"observed_at":"2026-08-04T15:20:32.203692Z","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":"2026-08-04T15:20:32.206677Z","title":"Daniel Freeman, Theodore R","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.206677Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:12260e73141638f8cba778392412894d69fe38abd1e92d456d8d4c07a71a526d","observation_id":"d23c7774-2fa1-41e0-9859-fd7ed884958c","resolution":{"observed_at":"2026-08-04T15:20:32.206677Z","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":"2026-08-04T15:20:32.209485Z","title":"Wikidata: a free collaborative knowledgebase","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.209485Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:98db50d27afe7aa771410aded265f6f0649dca5e0209d825d1470b0e7d225f1a","observation_id":"4e26416c-ad34-4e77-ac51-298421cedf01","resolution":{"observed_at":"2026-08-04T15:20:32.209485Z","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":"2026-08-04T15:20:32.212154Z","title":"Addressing feature suppression in saes","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.212154Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:97cb9fab6bc053548641f0ed572de60587243f5cebedee8f991224c6c27ecdc0","observation_id":"55316153-570d-44e7-bb76-991fd45bbdf4","resolution":{"observed_at":"2026-08-04T15:20:32.212154Z","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":"2026-08-04T15:20:32.214850Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.214850Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:f24519bde253d79201ed40e6c961399f42020bd5325f3079331a693399d1477e","observation_id":"5bece62d-4711-4273-a677-b3f9b80e0942","resolution":{"observed_at":"2026-08-04T15:20:32.214850Z","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":"2026-08-04T15:20:32.218824Z","title":"@esa (Ref","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.218824Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:4bace618466c4ea92864ee5b418ca9d115d5c07f9fb18576d75c416f991d1a46","observation_id":"58914705-1efc-4281-9d1f-46a0edb0dcf6","resolution":{"observed_at":"2026-08-04T15:20:32.218824Z","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":"2026-08-04T15:20:32.222020Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.222020Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:1958b46a1f506939f71d1699f24712475d55b2f3f1de7c469cf5497b660e2842","observation_id":"2c244f1d-bde7-4cad-8b18-ed3e2de28507","resolution":{"observed_at":"2026-08-04T15:20:32.222020Z","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":"2026-08-04T15:20:32.225118Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models","version":3},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-04T15:20:32.225118Z"},"links":{"citing_paper":"/paper/2509.20784"},"observation_digest":"sha256:f21c90e1d3e25f32758684732f77a713b5b375a65165ffd25742877c597cbe38","observation_id":"cb141a72-5288-4c09-bf01-00db7590293e","resolution":{"observed_at":"2026-08-04T15:20:32.225118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.20784","last_updated":"2026-05-29T09:11:25Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-08T01:29:27.853337Z","submitted_at":"2025-09-25T06:13:05Z","title":"Towards Atoms of Large Language Models"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":38,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":38},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2509.20784."}