{"as_of":"2026-08-10T04:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6d71564b89ccb7f105e3113434cfb1784da20da71d97fb289656f341b5a6d2a5","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":"2026-08-07T10:19:36.207209Z","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":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.06401/citation-record","integrity":"/paper/2506.06401/integrity","json":"/paper/2506.06401/citation-record.json","paper":"/paper/2506.06401"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2311.08803","last_updated":"2024-11-09T13:52:50Z","snapshot_observed_at":"2026-08-09T09:20:29.478541Z","submitted_at":"2023-11-15T09:18:09Z","title":"StrategyLLM: Large Language Models as Strategy Generators, Executors, Optimizers, and Evaluators for Problem Solving","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.08803","snapshot_observed_at":"2026-08-07T10:19:33.362267Z","title":"In The Eleventh International Conference on Learning Representations","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:33.362267Z"},"links":{"cited_paper":"/paper/2311.08803","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:d44f0fa4e32db0b79f93d52f079f335e81e26523d44a016030a4828852ec6867","observation_id":"84c211cc-f138-49d4-b275-f7286cd7d03e","resolution":{"observed_at":"2026-08-07T10:19:33.362267Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.02406","last_updated":"2023-04-11T19:39:17Z","snapshot_observed_at":"2026-07-06T14:00:01.450718Z","submitted_at":"2022-10-05T17:28:20Z","title":"Decomposed Prompting: A Modular Approach for Solving Complex Tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.02406","snapshot_observed_at":"2026-08-07T10:19:33.585059Z","title":"arXiv preprint arXiv:2210.02406","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:33.585059Z"},"links":{"cited_paper":"/paper/2210.02406","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:3d6bd79faaaa8387bafdde4c2b350c45dab2f5817f64b0aabb59f62a5ea3d4df","observation_id":"478b8067-e0d1-4b46-84e7-f5feee773f5a","resolution":{"observed_at":"2026-08-07T10:19:33.585059Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.08597","last_updated":"2022-10-22T07:51:53Z","snapshot_observed_at":"2026-08-09T09:21:03.252990Z","submitted_at":"2022-03-16T13:04:12Z","title":"Less is More: Summary of Long Instructions is Better for Program Synthesis","version":2},"cited_work":{"arxiv_id":"2203.08597","doi":null,"metadata_source":"pith","pith_arxiv_id":"2203.08597","snapshot_observed_at":"2026-08-07T10:19:36.467656Z","title":"Less is More: Summary of Long Instructions is Better for Program Synthesis","venue":"cs.CL","work_id":"d24c80cd-1235-49ae-90f8-67a0289312c4","year":2022},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:33.659012Z"},"links":{"cited_paper":"/paper/2203.08597","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:86debe5c1c9d5cf89a84da3234c6df907ab89e534d6ebebcbc325fa4e2cf17d4","observation_id":"3c8a36d9-357a-45b8-bae0-74e0b38c34b1","resolution":{"observed_at":"2026-08-07T10:19:36.532192Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14623","last_updated":"2024-04-01T03:23:23Z","snapshot_observed_at":"2026-07-06T15:32:10.481273Z","submitted_at":"2023-05-24T01:46:07Z","title":"Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.14623","snapshot_observed_at":"2026-08-07T10:19:33.726727Z","title":"arXiv preprint arXiv:2305.14623","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:33.726727Z"},"links":{"cited_paper":"/paper/2305.14623","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:f3dcc18398b7f6cd200f2b35fde5fae1d184adc8ca886ff78cd583dd46d9ab8e","observation_id":"141d7c1f-ec64-41d8-b636-43957099702b","resolution":{"observed_at":"2026-08-07T10:19:33.726727Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.13379","last_updated":"2023-09-20T22:19:30Z","snapshot_observed_at":"2026-07-06T14:46:23.137171Z","submitted_at":"2023-01-31T03:04:26Z","title":"Faithful Chain-of-Thought Reasoning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.13379","snapshot_observed_at":"2026-08-07T10:19:33.925730Z","title":"arXiv preprint arXiv:2301.13379","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:33.925730Z"},"links":{"cited_paper":"/paper/2301.13379","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:b8a696534a72c4853df23572e617218525e8549f5d7cef1313d02c2e89d5e57f","observation_id":"d0814cf7-7aaf-448f-8f77-61840729be00","resolution":{"observed_at":"2026-08-07T10:19:33.925730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.08294","last_updated":"2022-03-16T15:49:26Z","snapshot_observed_at":"2026-08-09T18:39:58.603582Z","submitted_at":"2021-10-15T18:05:33Z","title":"Coherence boosting: When your pretrained language model is not paying enough attention","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.08294","snapshot_observed_at":"2026-08-07T10:19:34.045731Z","title":"arXiv preprint arXiv:2110.08294","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.045731Z"},"links":{"cited_paper":"/paper/2110.08294","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:82bc4ec4565ee6397088302ca463f92199c02cf3ab3cd60d01ffe3680823b48f","observation_id":"b656e7f2-59e4-4b75-816f-06d10f376c0a","resolution":{"observed_at":"2026-08-07T10:19:34.045731Z","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":"2026-08-07T10:19:38.171331Z","title":"Hugging Face","venue":null,"work_id":"1a7ebf00-6f34-4267-b86b-7ae6857b2d8f","year":2025},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.251923Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:b8c9b1f97088276384b3a01cc0640784a52437e870afecadda02c9603d2914ac","observation_id":"a72b3b7a-e075-41a1-a8f9-6ab10daa98dd","resolution":{"observed_at":"2026-08-07T10:19:38.340437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-08-05T10:40:40.562724Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-08-07T10:19:34.293483Z","title":"arXiv preprint arXiv:2308.00436","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.293483Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:20be138f841aed3fbe9d005b490b3f857cd478877a924b1ced3133a9d5e5267a","observation_id":"d46cbc78-a18d-4a5e-8f48-114d9fbd4dd6","resolution":{"observed_at":"2026-08-07T10:19:34.293483Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.17517","last_updated":"2023-03-08T16:47:46Z","snapshot_observed_at":"2026-08-04T16:15:25.064317Z","submitted_at":"2022-10-31T17:41:26Z","title":"Lila: A Unified Benchmark for Mathematical Reasoning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.17517","snapshot_observed_at":"2026-08-07T10:19:34.414500Z","title":"arXiv preprint arXiv:2210.17517","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.414500Z"},"links":{"cited_paper":"/paper/2210.17517","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:bb3ce7f2c2476a404098ff4d6da49f67d4eaa4eb927bf0fb5e281c089c6b207c","observation_id":"2391460a-aa37-4a85-8b16-94b5fc9b06b0","resolution":{"observed_at":"2026-08-07T10:19:34.414500Z","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":"2026-08-07T10:19:38.464409Z","title":null,"venue":null,"work_id":"2f956a5c-465e-4f5f-8891-85a4d6f71a0e","year":2025},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.134726Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:f1facca03169672b31a175d3419d579e1f79cf7cd343fff802a76ae3851dbfec","observation_id":"335962a1-218e-42d1-8b1f-0498faa6135b","resolution":{"observed_at":"2026-08-07T10:19:38.561123Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:19:37.915849Z","title":"Accessed: 2025- 02-14","venue":null,"work_id":"995f1474-40a1-4d5b-853b-3c5d9065b821","year":2025},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.461311Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:cf029c20f2a3357dcd9bbda03960f86be616b651c94229cb7f559befca9ee82e","observation_id":"5dd6f083-aaf7-4fdd-b60c-20ccd126c663","resolution":{"observed_at":"2026-08-07T10:19:38.061226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.03188","last_updated":"2023-08-30T03:47:34Z","snapshot_observed_at":"2026-08-09T17:18:47.922122Z","submitted_at":"2023-08-06T18:38:52Z","title":"Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.03188","snapshot_observed_at":"2026-08-07T10:19:34.523636Z","title":"arXiv preprint arXiv:2308.03188","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.523636Z"},"links":{"cited_paper":"/paper/2308.03188","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:02a8d684b48526f4671fd0a3f96fe04e2a05533965b4f721622fd7a05f1f955b","observation_id":"d8794b37-2891-4372-9247-1828c320de3f","resolution":{"observed_at":"2026-08-07T10:19:34.523636Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.03350","last_updated":"2023-10-17T18:57:17Z","snapshot_observed_at":"2026-08-10T00:54:02.555288Z","submitted_at":"2022-10-07T06:50:23Z","title":"Measuring and Narrowing the Compositionality Gap in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.03350","snapshot_observed_at":"2026-08-07T10:19:34.611121Z","title":"arXiv preprint arXiv:2210.03350","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.611121Z"},"links":{"cited_paper":"/paper/2210.03350","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:0b4353cbd90990cb278dd4acb35f253aa901bb7ae9031d6445d6f598097e23dd","observation_id":"f24c5fe0-5490-45fb-b1ff-36682edfd381","resolution":{"observed_at":"2026-08-07T10:19:34.611121Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.03495","last_updated":"2023-10-19T04:37:25Z","snapshot_observed_at":"2026-08-06T03:31:54.947656Z","submitted_at":"2023-05-04T15:15:22Z","title":"Automatic Prompt Optimization with \"Gradient Descent\" and Beam Search","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.03495","snapshot_observed_at":"2026-08-07T10:19:34.725290Z","title":"gradient descent","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.725290Z"},"links":{"cited_paper":"/paper/2305.03495","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:109586aa74d8f1dea9b726f939204dc26d6925e7f082a9992749f286dcaa3b58","observation_id":"c1c5b9b8-fa9c-4d5b-8bfe-23dae174d260","resolution":{"observed_at":"2026-08-07T10:19:34.725290Z","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":"2026-08-07T10:19:37.787222Z","title":"https://www.reuters.com/technology/chatgpt- fever-spreads-us-workplace-sounding-alarm-some- 2023-08-11","venue":null,"work_id":"ca841d9f-2ad0-4cec-a58c-93854c872c7a","year":2023},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.791666Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:b205f7121de6680f0f45c2e86988c3eb5342ab9fde117edeba7b8bf27958ec30","observation_id":"0a37a750-c4fe-4062-b1d0-b2aeb49622d9","resolution":{"observed_at":"2026-08-07T10:19:37.840409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.10379","last_updated":"2024-06-02T16:01:35Z","snapshot_observed_at":"2026-08-09T23:24:23.740381Z","submitted_at":"2023-08-20T22:36:23Z","title":"Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.10379","snapshot_observed_at":"2026-08-07T10:19:34.826282Z","title":"arXiv preprint arXiv:2308.10379","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.826282Z"},"links":{"cited_paper":"/paper/2308.10379","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:ab347aa88576cdf375e9563db37648174e2c270a3bc491f9cd2cadd0a446d0bd","observation_id":"df38ad69-e782-4b7e-9d30-5a9c74ea715b","resolution":{"observed_at":"2026-08-07T10:19:34.826282Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.04615","last_updated":"2023-06-12T17:51:15Z","snapshot_observed_at":"2026-07-06T13:19:12.109592Z","submitted_at":"2022-06-09T17:05:34Z","title":"Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.04615","snapshot_observed_at":"2026-08-07T10:19:34.916672Z","title":"arXiv preprint arXiv:2206.04615","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.916672Z"},"links":{"cited_paper":"/paper/2206.04615","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:790aaee28c98cab52436172a31e50fb9318f101328a1d1d5eb0755f77a4a02b8","observation_id":"e0cc99d7-c345-4fed-b8b9-667a29d40b7e","resolution":{"observed_at":"2026-08-07T10:19:34.916672Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.07415","last_updated":"2023-08-08T21:26:53Z","snapshot_observed_at":"2026-07-06T15:54:05.111212Z","submitted_at":"2023-07-13T00:49:27Z","title":"AutoHint: Automatic Prompt Optimization with Hint Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.07415","snapshot_observed_at":"2026-08-07T10:19:34.977087Z","title":"arXiv preprint arXiv:2307.07415","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:34.977087Z"},"links":{"cited_paper":"/paper/2307.07415","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:65fc2c2abd8437b0b46a4e7f83b96c2542f3fb5e24147c37bee7c6d5a163f56c","observation_id":"e7116de8-2f33-4d51-8430-0cfbd7a757eb","resolution":{"observed_at":"2026-08-07T10:19:34.977087Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.09261","last_updated":"2022-10-17T17:08:26Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-10-17T17:08:26Z","title":"Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.09261","snapshot_observed_at":"2026-08-07T10:19:35.030366Z","title":"arXiv preprint arXiv:2210.09261","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.030366Z"},"links":{"cited_paper":"/paper/2210.09261","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:e55ff8c2db8425e7fbeb31e80682ac75d0f9c1cafe4bf4e0961756c58e757d13","observation_id":"c037001f-5feb-4870-bffa-896416e120b3","resolution":{"observed_at":"2026-08-07T10:19:35.030366Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.03863","last_updated":"2024-05-23T06:08:37Z","snapshot_observed_at":"2026-08-02T01:09:26.116796Z","submitted_at":"2023-12-06T19:18:42Z","title":"Efficient Large Language Models: A Survey","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.03863","snapshot_observed_at":"2026-08-07T10:19:35.095186Z","title":"arXiv preprint arXiv:2312.03863","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.095186Z"},"links":{"cited_paper":"/paper/2312.03863","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:3e18e4db115f8cc79c9bf4761a12674051d8afbde30e056b49670d280f5f59c8","observation_id":"0e60339d-5a4a-41cb-b92a-c1acc6c5b01e","resolution":{"observed_at":"2026-08-07T10:19:35.095186Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.16427","last_updated":"2023-12-07T14:39:22Z","snapshot_observed_at":"2026-07-06T16:38:13.945197Z","submitted_at":"2023-10-25T07:47:01Z","title":"PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.16427","snapshot_observed_at":"2026-08-07T10:19:35.176132Z","title":"arXiv preprint arXiv:2310.16427","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.176132Z"},"links":{"cited_paper":"/paper/2310.16427","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:51c47460ea540c24cecc90dcadb20a903822d4abaef7d858834981a32c683447","observation_id":"680eaec7-e165-4dc5-aaab-9bc77f0b5f07","resolution":{"observed_at":"2026-08-07T10:19:35.176132Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.18649","last_updated":"2024-02-28T19:00:12Z","snapshot_observed_at":"2026-08-10T03:18:14.587354Z","submitted_at":"2024-02-28T19:00:12Z","title":"A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.18649","snapshot_observed_at":"2026-08-07T10:19:35.285497Z","title":"arXiv preprint arXiv:2402.18649","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.285497Z"},"links":{"cited_paper":"/paper/2402.18649","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:173d5619cfe9f4ed11fdac5fedf4db7c656a1cf3290039afa7ff2d8de9c9a655","observation_id":"8688fd6e-c713-4618-8bef-ff6bcb32303a","resolution":{"observed_at":"2026-08-07T10:19:35.285497Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.10625","last_updated":"2023-04-16T22:08:08Z","snapshot_observed_at":"2026-08-06T09:00:42.886249Z","submitted_at":"2022-05-21T15:34:53Z","title":"Least-to-Most Prompting Enables Complex Reasoning in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.10625","snapshot_observed_at":"2026-08-07T10:19:35.384672Z","title":"arXiv preprint arXiv:2205.10625","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.384672Z"},"links":{"cited_paper":"/paper/2205.10625","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:5795c2c2aa3d3ed3cd13720710b3619e2b7dba6303549600b89fd9ce401af951","observation_id":"a42c6d9c-072e-4a7e-9288-e4fba7b6bcd0","resolution":{"observed_at":"2026-08-07T10:19:35.384672Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03620","last_updated":"2024-02-06T01:13:53Z","snapshot_observed_at":"2026-07-06T17:25:58.305593Z","submitted_at":"2024-02-06T01:13:53Z","title":"Self-Discover: Large Language Models Self-Compose Reasoning Structures","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03620","snapshot_observed_at":"2026-08-07T10:19:35.465699Z","title":"arXiv preprint arXiv:2402.03620","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.465699Z"},"links":{"cited_paper":"/paper/2402.03620","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:7f8e39f3496277d7c59e45e3e887a2d32413c8286cff74493569d5ebdb909957","observation_id":"e67e8a53-bd98-4acd-991f-e98fa4efd42a","resolution":{"observed_at":"2026-08-07T10:19:35.465699Z","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":"2026-08-07T10:19:37.659634Z","title":"Today is 3/5, and it is Jane’s second time in the year 1973 to see a me- teor shower. What is the date 24 hours later in MM/DD/YYYY?","venue":null,"work_id":"ac7787d6-bded-4966-9f73-3a66314c458a","year":1973},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.546482Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:672925bd22adafc81794236f77b233b13150abf89aab9811cb30b01976eadc79","observation_id":"8e9aa06f-3744-4b70-b859-eea49344e367","resolution":{"observed_at":"2026-08-07T10:19:37.663238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:19:37.534799Z","title":"Therefore, we can get the general and instructive solution:","venue":null,"work_id":"53cb50e6-05f0-4acb-8fe2-f4a443294dca","year":2025},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.632877Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:6537959e1d01d720538bb22a23713232319566179ea4d44d27c07c02c664ab0c","observation_id":"55bcc3b6-e191-4906-a515-786d6e96d56e","resolution":{"observed_at":"2026-08-07T10:19:37.582669Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:19:37.262265Z","title":"So the answer is (D)","venue":null,"work_id":"383091cd-3c8a-4350-b427-a929d2dca88d","year":1937},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.824123Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:e1acede890119e96deb061c4d736d690f687aced00f9b6685a00916188ac2e65","observation_id":"d787bcc5-ee38-46a0-9136-3f75b6c3e5b4","resolution":{"observed_at":"2026-08-07T10:19:37.312735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:19:37.388931Z","title":null,"venue":null,"work_id":"15842904-e369-48ef-91c4-30532ad41e2f","year":2026},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":1937,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.718674Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:4b1d18e39a8bf3e1f33716181ae1baded38791b072bb37d2be61960810027b6d","observation_id":"2c4e3490-0212-48de-a4f3-5a2931cdf04b","resolution":{"observed_at":"2026-08-07T10:19:37.462252Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:19:37.121576Z","title":null,"venue":null,"work_id":"b6ebcc85-66c6-4cbc-9733-7af0bb1ff2dc","year":1961},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":1958,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.928053Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:6bb8f10683aecc92b8d0ae1976b3f30ca9c0ebe48895f60a15afaa5223563ff6","observation_id":"121ae80f-ce96-420b-9ccb-30f655b76f3b","resolution":{"observed_at":"2026-08-07T10:19:37.189790Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:19:36.984212Z","title":"they\" might be referring to. There are two possible referents for","venue":null,"work_id":"29d7806c-5a9a-4359-9bd8-437b1b546824","year":1963},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":1963,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:35.994927Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:2dbc435d21940293ef1c25f43a80a392891c1415d82a58b1a04218999c266ab7","observation_id":"509487d3-cdbc-480f-af2f-cfd66753086b","resolution":{"observed_at":"2026-08-07T10:19:37.053128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:19:36.637074Z","title":null,"venue":null,"work_id":"185845eb-2505-47fa-9ae0-1a4442d979dd","year":2014},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":1994,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:36.207209Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:c29c2f4c1d1db0e952b9c85f96740e8131de1e82eea3861e09d19eb0e3ca4309","observation_id":"fba009c1-c80b-4882-8269-07421df1aae6","resolution":{"observed_at":"2026-08-07T10:19:36.666261Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:19:36.733761Z","title":"Amongst all the options, the only movie similar to these ones seems to be Forrest Gump (comedy, drama, romance; 1994)","venue":null,"work_id":"900a636f-2561-4f2d-98f1-1a72a2291afa","year":1994},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":1995,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:36.132943Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:0d28e57105812a74801295861a5f57c0d0bca1290f860545eff8cdc963bdca26","observation_id":"07f959b0-6a52-41db-856c-a0e9ac1c73a0","resolution":{"observed_at":"2026-08-07T10:19:36.791037Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T10:19:36.857828Z","title":"So the answer is (C)","venue":null,"work_id":"4089f2a1-8722-44f8-8ba4-bce96995c723","year":1987},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":2000,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:36.067775Z"},"links":{"citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:98f37b4008ac8347008515e0b7a6434dfbc804ecb250083964d8b6be1f105ef8","observation_id":"2d5a219a-2126-4569-acc2-e368acba5b2d","resolution":{"observed_at":"2026-08-07T10:19:36.907655Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.07258","last_updated":"2022-07-12T23:45:14Z","snapshot_observed_at":"2026-08-02T09:20:40.804790Z","submitted_at":"2021-08-16T17:50:08Z","title":"On the Opportunities and Risks of Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.07258","snapshot_observed_at":"2026-08-07T10:19:33.234769Z","title":"arXiv preprint arXiv:2108.07258","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:33.234769Z"},"links":{"cited_paper":"/paper/2108.07258","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:d7b66b57f77cee20482cf268da55c7af2e83fb5e85026f8e8dd101742e40cc3d","observation_id":"d1c38d42-6efb-4843-8285-af388f1a5f6e","resolution":{"observed_at":"2026-08-07T10:19:33.234769Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.12588","last_updated":"2023-10-23T01:27:38Z","snapshot_observed_at":"2026-08-02T13:06:11.850456Z","submitted_at":"2022-11-22T21:06:00Z","title":"Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.12588","snapshot_observed_at":"2026-08-07T10:19:33.303554Z","title":"arXiv preprint arXiv:2211.12588","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:33.303554Z"},"links":{"cited_paper":"/paper/2211.12588","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:d279b3602bd6bccee79953b61275c03235da458678321d39183a576f781d81e8","observation_id":"8b87cf41-03fa-48db-8086-101b0e1995aa","resolution":{"observed_at":"2026-08-07T10:19:33.303554Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.05398","last_updated":"2023-03-04T04:43:49Z","snapshot_observed_at":"2026-08-09T20:47:04.856732Z","submitted_at":"2023-03-04T04:43:49Z","title":"MathPrompter: Mathematical Reasoning using Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.05398","snapshot_observed_at":"2026-08-07T10:19:33.505707Z","title":"arXiv preprint arXiv:2303.05398","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:33.505707Z"},"links":{"cited_paper":"/paper/2303.05398","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:c81199fd0c35dbf3072b5b77aab1a74869863c738d45f465cdd18eec3d8c7c50","observation_id":"ea991fb9-6da8-45a8-9831-72fc6250e744","resolution":{"observed_at":"2026-08-07T10:19:33.505707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.14628","last_updated":"2023-12-27T13:54:48Z","snapshot_observed_at":"2026-07-06T16:36:59.440643Z","submitted_at":"2023-10-23T07:02:20Z","title":"Plan, Verify and Switch: Integrated Reasoning with Diverse X-of-Thoughts","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.14628","snapshot_observed_at":"2026-08-07T10:19:33.848237Z","title":"In 2024 IEEE Congress on Evolutionary Computation (CEC), pages 1–8","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:33.848237Z"},"links":{"cited_paper":"/paper/2310.14628","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:464b79ba011b63f3b080fb9e9652bf2b68d032122726c954163dec3eb380acec","observation_id":"765b85e9-5ef7-497a-a058-7063fb065305","resolution":{"observed_at":"2026-08-07T10:19:33.848237Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-07T10:19:33.433284Z","title":"arXiv preprint arXiv:2501.12948","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-07T10:19:33.433284Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2506.06401"},"observation_digest":"sha256:6722b92a21271f9842dc709e05fda7c4feaffceda11fdb2dfee9d5e23315fb81","observation_id":"9010ed4a-642e-4d79-94d5-c55e80172dd0","resolution":{"observed_at":"2026-08-07T10:19:33.433284Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.06401","last_updated":"2025-06-06T02:40:42Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T09:20:46.645964Z","submitted_at":"2025-06-06T02:40:42Z","title":"Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs"},"reference_resolution":{"displayed":38,"state_counts":{"malformed_identifier":1,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":28,"verified_exact":0,"verified_fuzzy":8},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2506.06401."}