{"as_of":"2026-08-22T17:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:75d1aa1c7a2c2eabc449c811564e77472c8a58701152630ac3f1cb016075acba","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-29T21:42:08.610000Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T14:41:17.911429Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-15T14:41:18.231573Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"cited_work":{"arxiv_id":"2605.25745","doi":null,"metadata_source":"pith","pith_arxiv_id":"2605.25745","snapshot_observed_at":"2026-08-15T14:41:18.231573Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","venue":"cs.CL","work_id":"a7a8796b-ac02-4d2f-a03f-6fa44bab3ed5","year":2026},"citing_paper":{"arxiv_id":"2608.04928","last_updated":"2026-08-05T14:55:23Z","snapshot_observed_at":"2026-08-19T07:48:35.623280Z","submitted_at":"2026-08-05T14:55:23Z","title":"Does Out-of-Sight Equal Out-of-Mind in CoT Monitorability?","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-15T14:41:17.911429Z"},"links":{"cited_paper":"/paper/2605.25745","citing_paper":"/paper/2608.04928"},"observation_digest":"sha256:773af7b6c71603e5b1f57eba7eba11772e337778d6fb0c2fd2bce02ec31d0aa4","observation_id":"5aa68907-6727-4c31-9a66-c13a6fcc3a58","resolution":{"observed_at":"2026-08-15T14:41:18.239816Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2605.25745/citation-record","integrity":"/paper/2605.25745/integrity","json":"/paper/2605.25745/citation-record.json","paper":"/paper/2605.25745"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.04697","last_updated":"2025-10-03T01:55:58Z","snapshot_observed_at":"2026-08-17T16:48:59.674177Z","submitted_at":"2025-03-06T18:43:29Z","title":"L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2503.04697","doi":"10.48550/arxiv.2503.04697","metadata_source":"pith","pith_arxiv_id":"2503.04697","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning","venue":"cs.CL","work_id":"ad7236fb-3752-48a9-b782-a384899c45a0","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2503.04697","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:e573a751a439ed15dfa0298612d7c06d86e85298e8dc6012893780f6d586f9aa","observation_id":"0fe43f3e-450b-47fe-9999-357dd4ae2610","resolution":{"observed_at":"2026-06-29T21:43:59.086669Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T21:42:08.610000Z","title":"Sketch-of-thought: Efficient llm reasoning with adaptive cognitive-inspired sketching","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:1befe749b028e5d0977b9f564a6e048a3934c2c17a9104e9e519694c93d71a3d","observation_id":"974438fd-461b-4902-945f-cd5326eb68d5","resolution":{"observed_at":"2026-06-29T21:42:08.610000Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.10774","last_updated":"2024-06-14T23:32:32Z","snapshot_observed_at":"2026-08-17T10:13:54.763177Z","submitted_at":"2024-01-19T15:48:40Z","title":"Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads","version":3},"cited_work":{"arxiv_id":"2401.10774","doi":"10.48550/arxiv.2401.10774","metadata_source":"pith","pith_arxiv_id":"2401.10774","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads","venue":"cs.LG","work_id":"f6202cd1-1a78-4c19-8242-688acf4952b6","year":2024},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2401.10774","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:481e8ac16961c069ecd332b2829dcfe95a773e5410ff48de33729076cf5d72c5","observation_id":"183e85d2-d286-4278-9cdd-a24f84f7e359","resolution":{"observed_at":"2026-06-29T21:43:59.080933Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2504.10903","doi":"10.48550/arxiv.2504.10903","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Efficient reasoning models: A survey","venue":"ArXiv.org","work_id":"4923c1ac-75d5-43c9-85a0-16f3b13d7ea8","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:ffd1aa62a657cbda11ba95c7bbb3eda0d2caf663795269585bf6b82b6c7c003d","observation_id":"ecc208d2-eabf-4dc2-b4a6-2bd87795e974","resolution":{"observed_at":"2026-06-29T21:43:59.075766Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.19737","last_updated":"2024-04-30T17:33:57Z","snapshot_observed_at":"2026-08-16T23:36:44.216328Z","submitted_at":"2024-04-30T17:33:57Z","title":"Better & Faster Large Language Models via Multi-token Prediction","version":1},"cited_work":{"arxiv_id":"2404.19737","doi":"10.48550/arxiv.2404.19737","metadata_source":"pith","pith_arxiv_id":"2404.19737","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Better & Faster Large Language Models via Multi-token Prediction","venue":"cs.CL","work_id":"7235774b-df35-4d85-a7ef-7deebd473172","year":2024},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2404.19737","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:35c4a4602c79f151bffe81cf51555a4d5bdebae94f62b3de6f70412928f8aa3f","observation_id":"109e1b04-37a2-4652-bd88-79051c70c601","resolution":{"observed_at":"2026-06-29T21:43:59.078406Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-08-15T12:33:55.451951Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2501.12948","doi":"10.1016/j.artmed.2024.103001","metadata_source":"pith","pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","venue":"cs.CL","work_id":"e6b75ad5-2877-4168-97c8-710407094d20","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:6d728169712b5f8e78530e1b7c78061cde4fc04ae7717dc8b1054c8be425097e","observation_id":"b97ff6c7-5d82-43bc-af0b-59e557664add","resolution":{"observed_at":"2026-06-29T21:43:59.098991Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T21:42:08.610000Z","title":"Token-budget-aware llm reasoning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:e0a2e0369c29b7342ee9073c32c4401d3626f062d13120d7c25a60528c8aa15b","observation_id":"fb149b03-3c76-4e1a-8c98-d6fad3e32d8c","resolution":{"observed_at":"2026-06-29T21:42:08.610000Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.06769","last_updated":"2025-11-03T00:53:34Z","snapshot_observed_at":"2026-08-17T06:12:37.525438Z","submitted_at":"2024-12-09T18:55:56Z","title":"Training Large Language Models to Reason in a Continuous Latent Space","version":3},"cited_work":{"arxiv_id":"2412.06769","doi":"10.48550/arxiv.2412.06769","metadata_source":"pith","pith_arxiv_id":"2412.06769","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Training Large Language Models to Reason in a Continuous Latent Space","venue":"cs.CL","work_id":"3ddd0fd2-c176-408f-9b58-0666c2707f2d","year":2024},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2412.06769","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:bff292be52933a8ee4671f2da01d09fabe53a7715ffe0d90e229867400e28cbd","observation_id":"c7aeb090-d9e6-46e1-85f1-59da879a8c92","resolution":{"observed_at":"2026-06-29T21:43:59.092647Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:44.826594+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:44.826594+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-08-19T11:46:55.171293Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:9d0026bd12cd1048ac3aa49b1c9dce40a9619b120e3f1e6fad9ce9ddae4f0a39","observation_id":"22d0e4b5-e291-4313-b71a-8bd0bf7af72c","resolution":{"observed_at":"2026-06-29T21:43:59.072667Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01840","last_updated":"2025-04-23T07:08:17Z","snapshot_observed_at":"2026-08-13T11:30:48.832931Z","submitted_at":"2025-03-03T18:59:04Z","title":"EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test","version":3},"cited_work":{"arxiv_id":"2503.01840","doi":"10.48550/arxiv.2503.01840","metadata_source":"pith","pith_arxiv_id":"2503.01840","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test","venue":"cs.CL","work_id":"323c1b68-aec5-4444-944f-155a771bd8c6","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2503.01840","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:4a9818e46ea4c68c21d497a7ed74b40390a25d16279b12f21c492bbbc1dcb320","observation_id":"bd0b2c95-d2d7-4d65-9519-c7d0d1874e71","resolution":{"observed_at":"2026-06-29T21:43:59.065498Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12570","last_updated":"2025-01-29T03:11:03Z","snapshot_observed_at":"2026-08-18T10:17:24.497798Z","submitted_at":"2025-01-22T01:35:11Z","title":"O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning","version":2},"cited_work":{"arxiv_id":"2501.12570","doi":"10.48550/arxiv.2501.12570","metadata_source":"arxiv_reference","pith_arxiv_id":"2501.12570","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"O1-pruner: Length-harmonizing fine-tuning for o1-like reasoning pruning","venue":"ArXiv.org","work_id":"133f3b9f-d49a-46dd-9844-40063846c9ee","year":2026},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2501.12570","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:8537d980483214d8eb802b59cf20836cd73e1f5d0f8ae75d3656a008cdbb1bbe","observation_id":"6695664b-914a-4572-9330-2bd07904cf6e","resolution":{"observed_at":"2026-06-29T21:43:59.064553Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.13738","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T21:43:59.059914Z","title":"Onelatent: Single-token compression for visual latent reasoning.CoRR, abs/2602.13738","venue":null,"work_id":"66ba0f71-7b8b-4809-98f7-e9b3ff7ccfb8","year":2026},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:5297a6b8b0d3c4cee28d67206db98301e65a79e7c1e5b02ec6a36fb5c8a8b1f1","observation_id":"6bdd7854-1d68-4bdb-9c6b-cc40360b3fc8","resolution":{"observed_at":"2026-06-29T21:43:59.061450Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.11851","last_updated":"2025-07-16T02:31:40Z","snapshot_observed_at":"2026-08-20T11:40:12.060471Z","submitted_at":"2025-07-16T02:31:40Z","title":"Your LLM Knows the Future: Uncovering Its Multi-Token Prediction Potential","version":1},"cited_work":{"arxiv_id":"2507.11851","doi":null,"metadata_source":"pith","pith_arxiv_id":"2507.11851","snapshot_observed_at":"2026-07-11T03:07:52.420950Z","title":"Your llm knows the future: Uncovering its multi-token prediction potential","venue":"cs.CL","work_id":"16bb770c-f778-4c03-a015-c2e45263b787","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2507.11851","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:9fe223a53bca9cf460417b0b75982e207220473dc2f75c21a11789340cf1bac2","observation_id":"f9af3921-7eb9-47fb-8f7f-c166bdcdaa17","resolution":{"observed_at":"2026-06-29T21:43:59.090000Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.19201","last_updated":"2026-05-04T05:23:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-31T15:10:29Z","title":"Efficient Reasoning with Hidden Thinking","version":2},"cited_work":{"arxiv_id":"2501.19201","doi":"10.48550/arxiv.2501.19201","metadata_source":"pith","pith_arxiv_id":"2501.19201","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"Efficient Reasoning with Hidden Thinking","venue":"cs.CL","work_id":"638ab221-ba45-480b-ad54-ebd57d3a7a74","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2501.19201","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:14421360126b8f35d0335ac25c7d0b1e47fdb47e749332d3d9ab774fb8e3c2da","observation_id":"9ea15bf4-8b15-45ff-b253-dd0cfee641b7","resolution":{"observed_at":"2026-06-29T21:43:59.070193Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.21074","last_updated":"2025-09-23T08:16:08Z","snapshot_observed_at":"2026-08-07T17:46:47.440455Z","submitted_at":"2025-02-28T14:07:48Z","title":"CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation","version":3},"cited_work":{"arxiv_id":"2502.21074","doi":"10.48550/arxiv.2502.21074","metadata_source":"pith","pith_arxiv_id":"2502.21074","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"CODI: Compressing Chain-of-Thought into Continuous Space via Self-Distillation","venue":"cs.CL","work_id":"c538c1a5-0662-4de7-ac6f-29061c2c9686","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2502.21074","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:46f7559629dc7392419555f0de6c3ca886d20728969c33c81162ca8137f9b253","observation_id":"97a6cdd8-dc94-442d-baed-3519616208b7","resolution":{"observed_at":"2026-06-29T21:43:59.082941Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.16419","last_updated":"2025-08-21T19:14:40Z","snapshot_observed_at":"2026-08-11T13:10:23.709172Z","submitted_at":"2025-03-20T17:59:38Z","title":"Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models","version":4},"cited_work":{"arxiv_id":"2503.16419","doi":"10.48550/arxiv.2503.16419","metadata_source":"pith","pith_arxiv_id":"2503.16419","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models","venue":"cs.CL","work_id":"21afd80d-63a7-472b-800d-3b81161c39d3","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2503.16419","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:9ed7cbb6bb32bd84ec9c60bcd67288900bd255f284d02fa07f7db10941a20065","observation_id":"24f1fe32-ae07-4d9c-81d3-79aee91bd3c4","resolution":{"observed_at":"2026-06-29T21:43:59.056107Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2505.16552","doi":"10.48550/arxiv.2505.16552","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2505.16552 (2025)","venue":"arXiv (Cornell University)","work_id":"125e724a-d7d2-4d72-9bc2-9b4d6dff0b3f","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:0c71da801d4fabbf87b5be8fa97a50546d9331a28bfd016a12df0d3cbb35642f","observation_id":"92260927-6b7a-4b1a-a3fd-fb2ceb57d17a","resolution":{"observed_at":"2026-06-29T21:43:59.047110Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12599","last_updated":"2025-06-03T02:14:54Z","snapshot_observed_at":"2026-08-15T22:38:53.825110Z","submitted_at":"2025-01-22T02:48:14Z","title":"Kimi k1.5: Scaling Reinforcement Learning with LLMs","version":4},"cited_work":{"arxiv_id":"2501.12599","doi":"10.48550/arxiv.2501.12599","metadata_source":"pith","pith_arxiv_id":"2501.12599","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Kimi k1.5: Scaling Reinforcement Learning with LLMs","venue":"cs.AI","work_id":"bff96ab1-bd6a-4585-be23-74fdb51969c7","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2501.12599","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:c22d9e5bcba88279203a03c15e9c201e6555d1c3dd57937bc368d35788aa401a","observation_id":"5a040682-aca1-4343-9246-4acf66e364b6","resolution":{"observed_at":"2026-06-29T21:43:59.053235Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-07-09T10:48:38.585868+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-09T10:48:38.585868+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2601.14750","last_updated":"2026-05-31T05:30:22Z","snapshot_observed_at":"2026-08-03T09:09:48.759756Z","submitted_at":"2026-01-21T08:09:25Z","title":"Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning","version":4},"cited_work":{"arxiv_id":"2601.14750","doi":"10.48550/arxiv.2601.14750","metadata_source":"pith","pith_arxiv_id":"2601.14750","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning","venue":"cs.CL","work_id":"a3e8c06c-5aa9-4d0f-92d1-f6f6bdd30820","year":2026},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2601.14750","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:8a51eb595554ff6e14c6612c422fa1c7f26f6b488eba621fee8c33cb68ecce48","observation_id":"37bbe05f-47fc-49e0-ba55-30ca06a27d5b","resolution":{"observed_at":"2026-06-29T21:43:59.067917Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T21:42:08.610000Z","title":"Chain-of-thought prompting elicits reasoning in large language models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:615e662ea1dddf4faae498375fd966adc60d7b8c9116c43a56688bb85b8b7b27","observation_id":"44d6179f-bc0d-4af0-a3d1-018b0ed9e3b1","resolution":{"observed_at":"2026-06-29T21:42:08.610000Z","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":"2502.12067","doi":"10.48550/arxiv.2502.12067","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Tokenskip: Controllable chain-of-thought compression in llms.arXiv preprint arXiv:2502.12067","venue":"ArXiv.org","work_id":"3ef0bd59-5ccb-4785-82a0-6c2ad863a0c1","year":2024},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:611d33539dc96aba470928884abb267162ee27fccb52aa2a8ebd69cce6997816","observation_id":"156894a0-4c8b-46cc-b98b-ccc2caeae6c3","resolution":{"observed_at":"2026-06-29T21:43:59.042578Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.04682","last_updated":"2025-01-08T18:42:48Z","snapshot_observed_at":"2026-08-19T22:21:38.527415Z","submitted_at":"2025-01-08T18:42:48Z","title":"Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought","version":1},"cited_work":{"arxiv_id":"2501.04682","doi":"10.48550/arxiv.2501.04682","metadata_source":"pith","pith_arxiv_id":"2501.04682","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Towards system 2 reasoning in llms: Learning how to think with meta chain-of-thought","venue":"cs.AI","work_id":"9e24c386-134f-4c23-b861-1bf5acc21088","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2501.04682","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:c3866f1c800d4624cfa11f5e5a9626627f9e393ffa003ec1247bc249cf256432","observation_id":"393e81c2-649a-4ec1-9997-8d24228a4c01","resolution":{"observed_at":"2026-06-29T21:43:59.096395Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.18600","last_updated":"2025-03-03T17:08:21Z","snapshot_observed_at":"2026-08-18T14:29:54.622995Z","submitted_at":"2025-02-25T19:36:06Z","title":"Chain of Draft: Thinking Faster by Writing Less","version":2},"cited_work":{"arxiv_id":"2502.18600","doi":"10.48550/arxiv.2502.18600","metadata_source":"pith","pith_arxiv_id":"2502.18600","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2502.18600 , year=","venue":"cs.CL","work_id":"9bb5ce25-93d1-4df0-bba6-491d6ba79d28","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"cited_paper":"/paper/2502.18600","citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:c408d3500d4971ad0590be48f84d6dd1e1c107e79addbd8c64caa72a097d2f4b","observation_id":"f9cfab1d-3006-41a3-9a0b-e94411950dce","resolution":{"observed_at":"2026-06-29T21:43:59.070231Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2504.15895","doi":"10.48550/arxiv.2504.15895","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Dynamic early exit in reasoning models.arXiv preprint arXiv:2504.15895, 2025a","venue":"ArXiv.org","work_id":"99c0642f-2c3c-4bfd-aa41-08cd3fb032e8","year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:be6a4361a4b766729a6cd581f8dc4995ed881c6ae84286af6599d4ca1a5aebab","observation_id":"ee564b3a-3310-4d43-858f-3cedfacdd3e6","resolution":{"observed_at":"2026-06-29T21:43:59.083753Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-29T21:42:08.610000Z","title":"semantic routing","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-29T21:42:08.610000Z"},"links":{"citing_paper":"/paper/2605.25745"},"observation_digest":"sha256:95eae753c69d746a471a580528f145fedeccb87396b32e1ce804a20b6dde34e0","observation_id":"029fc03e-d38e-4486-af97-0d1aa6a397a4","resolution":{"observed_at":"2026-06-29T21:42:08.610000Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2605.25745","last_updated":"2026-05-25T11:57:09Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-06T11:29:59.606951Z","submitted_at":"2026-05-25T11:57:09Z","title":"Selective Latent Thinking: Adaptive Compression of LLM Reasoning Chains"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":4,"verified_exact":21,"verified_fuzzy":0},"total_outbound_references":25},"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":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2605.25745."}