{"as_of":"2026-08-10T18:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ce2e31b1c33bd40beccf62c457ea8d271b8be7d5db3f5bac066c066e1c17ccd5","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":27,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":27,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":27,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":27,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T15:15:43.569123Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2503.16419","last_updated":"2025-08-21T19:14:40Z","snapshot_observed_at":"2026-08-07T04:27:23.738927Z","submitted_at":"2025-03-20T17:59:38Z","title":"Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models","version":4},"reference_index":206,"source":"pdf_text","source_observed_at":"2026-05-14T01:29:56.480020Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2503.16419"},"observation_digest":"sha256:c04c7d2b1938803f381d10771a49540dcc7b04c0c0a2d320256c00e455d98b6e","observation_id":"5bdd5f2b-3dfc-4fb0-bb54-d30ebbeb309c","resolution":{"observed_at":"2026-05-14T01:29:57.189069Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-07T15:15:43.569123Z","title":"Softcot: Soft chain-of-thought for efficient reasoning with llms","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.15778","last_updated":"2025-05-21T17:29:15Z","snapshot_observed_at":"2026-08-10T11:39:20.508638Z","submitted_at":"2025-05-21T17:29:15Z","title":"Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T15:15:43.569123Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2505.15778"},"observation_digest":"sha256:e02a6df3e3b78702b223ab6ae915d302d0bec1987fb4e21644dffdb19d98d62c","observation_id":"0aa5bcdb-9900-42f3-a1f2-8405cdb6cb41","resolution":{"observed_at":"2026-08-07T15:15:43.569123Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-07T14:59:20.125250Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.16865","last_updated":"2025-06-04T11:31:59Z","snapshot_observed_at":"2026-08-09T17:57:03.404620Z","submitted_at":"2025-05-22T16:22:54Z","title":"LARES: Latent Reasoning for Sequential Recommendation","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T14:59:20.125250Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2505.16865"},"observation_digest":"sha256:66eb026e9194f11f2997ff5aea04c2766c9fca34aef02cdc3c9a86e386ad021d","observation_id":"9454cf9e-68d5-42b0-b224-d9031032e5f9","resolution":{"observed_at":"2026-08-07T14:59:20.125250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-07T14:49:35.225409Z","title":"Softcot: Soft chain-of-thought for efficient reasoning with llms.arXiv preprint arXiv:2502.12134, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.17481","last_updated":"2025-05-23T05:21:11Z","snapshot_observed_at":"2026-08-07T21:56:32.010090Z","submitted_at":"2025-05-23T05:21:11Z","title":"MARCO: Meta-Reflection with Cross-Referencing for Code Reasoning","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-07T14:49:35.225409Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2505.17481"},"observation_digest":"sha256:5b2b23408056c16c8d72ac0cb7d00375cd90b10102dbf414026700bb5e98667b","observation_id":"d5ba1cb2-1dc2-4448-a513-8d9f8d993208","resolution":{"observed_at":"2026-08-07T14:49:35.225409Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-06T23:00:46.000277Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.20160","last_updated":"2025-08-08T09:23:42Z","snapshot_observed_at":"2026-08-09T21:06:17.179483Z","submitted_at":"2025-06-25T06:29:18Z","title":"AALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-06T23:00:46.000277Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2506.20160"},"observation_digest":"sha256:68fdce5646ee192de56abc830d939cd21f0beaa1554d43b0e771d542158a9b19","observation_id":"a0b0adeb-d9eb-4aa4-a2de-3b39ae992cd8","resolution":{"observed_at":"2026-08-06T23:00:46.000277Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-06T20:43:10.970286Z","title":"Softcot: Soft chain-of-thought for efficient reasoning with llms","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.02076","last_updated":"2025-07-02T18:27:42Z","snapshot_observed_at":"2026-08-08T01:09:25.758170Z","submitted_at":"2025-07-02T18:27:42Z","title":"Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T20:43:10.970286Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2507.02076"},"observation_digest":"sha256:d8946221d42eeadb9fa86e16e0c811266338a267f27c120b325fe65446e09ad6","observation_id":"940832f4-6610-434e-a01d-26b89129ce53","resolution":{"observed_at":"2026-08-06T20:43:10.970286Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-06T17:54:17.926847Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.09662","last_updated":"2025-07-13T14:51:59Z","snapshot_observed_at":"2026-08-07T01:15:50.475193Z","submitted_at":"2025-07-13T14:51:59Z","title":"Towards Concise and Adaptive Thinking in Large Reasoning Models: A Survey","version":1},"reference_index":215,"source":"arxiv_source","source_observed_at":"2026-08-06T17:54:17.926847Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2507.09662"},"observation_digest":"sha256:8d085d3f00241817383387a9886ad3d6bdf8b4e362a6dbc2452915986e68cee9","observation_id":"923a9d45-fe44-4b05-b59b-189590c1aabb","resolution":{"observed_at":"2026-08-06T17:54:17.926847Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2601.06803","last_updated":"2026-04-20T09:04:42Z","snapshot_observed_at":"2026-07-06T22:41:19.981014Z","submitted_at":"2026-01-11T08:30:49Z","title":"Forest Before Trees: Latent Superposition for Efficient Visual Reasoning","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-16T15:58:03.654150Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2601.06803"},"observation_digest":"sha256:5efe324cd2c38b62cb2d8b679beb33b5cb30e135613aab6620a99bd1c10bb22f","observation_id":"eb57afc0-12a8-4059-8daf-f14e90602f4a","resolution":{"observed_at":"2026-05-16T16:01:05.159935Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-03T09:21:47.118713Z","title":"Softcot: Soft chain-of-thought for efficient reasoning with llms, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.14192","last_updated":"2026-07-03T11:26:58Z","snapshot_observed_at":"2026-08-07T15:05:40.772054Z","submitted_at":"2026-01-20T17:51:56Z","title":"Toward Efficient Agents: Memory, Tool learning, and Planning","version":2},"reference_index":163,"source":"pdf_text","source_observed_at":"2026-08-03T09:21:47.118713Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2601.14192"},"observation_digest":"sha256:eee340b3ac9e688c3611e4c9ac90ca0559eea06de2ab4423475c992948872d2c","observation_id":"415b78ba-d048-4df1-8689-beae89edff20","resolution":{"observed_at":"2026-08-03T09:21:47.118713Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-03T09:09:59.312887Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_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},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-03T09:09:59.312887Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2601.14750"},"observation_digest":"sha256:fa4fa8323a40ccbbd028c9957eede9a7fe21a602c124c7d58825500e3d5eb6ac","observation_id":"1a1b4b8d-ded5-44b3-bb9b-f2e7f315ccef","resolution":{"observed_at":"2026-08-03T09:09:59.312887Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2601.19917","last_updated":"2026-04-14T07:00:09Z","snapshot_observed_at":"2026-07-06T22:43:12.468415Z","submitted_at":"2026-01-07T12:38:56Z","title":"PILOT: Planning via Internalized Latent Optimization Trajectories for Large Language Models","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-16T16:37:56.162872Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2601.19917"},"observation_digest":"sha256:be326fd314630651157fe02891f08a2c2ed2b20903b1d5fa729c19e04ac14735","observation_id":"cf628015-4ec4-48b9-a6d9-f144fa9e0958","resolution":{"observed_at":"2026-05-16T16:38:06.074290Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-03T06:59:05.332260Z","title":"emnlp-main.165/","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2601.21576","last_updated":"2026-05-26T05:57:21Z","snapshot_observed_at":"2026-08-03T06:59:03.940440Z","submitted_at":"2026-01-29T11:42:03Z","title":"Chain Of Thought Compression: A Theoretical Analysis","version":2},"reference_index":165,"source":"pdf_text","source_observed_at":"2026-08-03T06:59:05.332260Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2601.21576"},"observation_digest":"sha256:ca97156e7909ef12787197f50afc140849bede1aebd3f274f51acccd49f86da2","observation_id":"96f806e0-4085-40f7-8c5a-7c0006d498be","resolution":{"observed_at":"2026-08-03T06:59:05.332260Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-03T04:03:55.088395Z","title":"Softcot: Soft chain-of-thought for efficient reasoning with llms, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.07075","last_updated":"2026-07-23T07:39:02Z","snapshot_observed_at":"2026-08-03T04:03:48.989631Z","submitted_at":"2026-02-06T01:28:27Z","title":"LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning","version":6},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-03T04:03:55.088395Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2602.07075"},"observation_digest":"sha256:41e35c4e050dca30492bf88195e322546f07827c6b8af43b657a7c2d05fd8d67","observation_id":"2815313b-72eb-4e7a-adb9-43899aefb7de","resolution":{"observed_at":"2026-08-03T04:03:55.088395Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2602.08324","last_updated":"2026-05-25T15:41:17Z","snapshot_observed_at":"2026-08-03T03:25:21.079471Z","submitted_at":"2026-02-09T06:57:15Z","title":"Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-21T13:43:51.127429Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2602.08324"},"observation_digest":"sha256:29c1c5db2d5ea9b3c7b6af65d16fece7409595cc3e351166a2797d8a4e96ab30","observation_id":"9f0dabe0-0719-4e7f-9b1f-46965d2ab2c0","resolution":{"observed_at":"2026-05-21T13:44:11.366290Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-03T03:25:23.113752Z","title":"Softcot: Soft chain-of-thought for efficient reasoning with llms.arXiv preprint arXiv:2502.12134,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.08324","last_updated":"2026-05-25T15:41:17Z","snapshot_observed_at":"2026-08-03T03:25:21.079471Z","submitted_at":"2026-02-09T06:57:15Z","title":"Towards Efficient Large Language Reasoning Models via Extreme-Ratio Chain-of-Thought Compression","version":4},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T03:25:23.113752Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2602.08324"},"observation_digest":"sha256:99f2831bfc2d4697136d0fcfe9091521a94bd9149a49ee15e7b9423197eca2aa","observation_id":"7540ab61-7b11-48c2-9f55-80b9e1ebd974","resolution":{"observed_at":"2026-08-03T03:25:23.113752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2603.17837","last_updated":"2026-06-04T13:47:38Z","snapshot_observed_at":"2026-08-02T07:45:21.753896Z","submitted_at":"2026-03-18T15:30:29Z","title":"The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-15T08:34:56.898815Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2603.17837"},"observation_digest":"sha256:48216a8f636bf5d2288cd0b46b96e9121afa74dac67af415c488ded56c29db11","observation_id":"917dc652-62f8-4370-bc63-18c4b3d0d9d0","resolution":{"observed_at":"2026-05-15T08:35:18.019245Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2603.17837","last_updated":"2026-06-04T13:47:38Z","snapshot_observed_at":"2026-08-02T07:45:21.753896Z","submitted_at":"2026-03-18T15:30:29Z","title":"The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning","version":4},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-21T10:43:27.176535Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2603.17837"},"observation_digest":"sha256:a2e53d0c25cbbe8647a084357c46aacd8abaebab5b668d46ac475ded78e77af5","observation_id":"4bcb5289-3482-4ffc-bc3e-b411ba841d61","resolution":{"observed_at":"2026-05-21T10:44:07.605785Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-07-13T22:57:11.059962Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.17837","last_updated":"2026-06-04T13:47:38Z","snapshot_observed_at":"2026-08-02T07:45:21.753896Z","submitted_at":"2026-03-18T15:30:29Z","title":"The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning","version":5},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-13T22:57:11.059962Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2603.17837"},"observation_digest":"sha256:59e19b17a9f8eb4e7bf048beec60ffb9a8e8401962340374cf8200bb1a7a5899","observation_id":"679987d1-3981-4352-b8ab-4b0897ce2966","resolution":{"observed_at":"2026-07-13T22:57:11.059962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2604.08299","last_updated":"2026-04-19T12:06:32Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T14:32:07Z","title":"SeLaR: Selective Latent Reasoning in Large Language Models","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-05-10T18:27:36.132030Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2604.08299"},"observation_digest":"sha256:ea32c0103011806fe6eaf79b92ebf69501c568826625c7ec646e6a9860274778","observation_id":"153c6204-8bfd-4ceb-9308-e41b9198f9fa","resolution":{"observed_at":"2026-05-11T00:35:49.661381Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2604.21027","last_updated":"2026-08-02T16:15:42Z","snapshot_observed_at":"2026-08-06T23:24:26.820832Z","submitted_at":"2026-04-22T19:18:36Z","title":"HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-05-09T23:51:47.724033Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2604.21027"},"observation_digest":"sha256:55993ab66a2eb297c8593d29613dcb28b1178e86c33f717454fd24878d9f60e9","observation_id":"5a2beff3-7f87-4027-ab0c-705a3c4efee1","resolution":{"observed_at":"2026-05-09T23:54:45.474163Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2605.06165","last_updated":"2026-05-07T12:51:49Z","snapshot_observed_at":"2026-07-06T23:18:41.400741Z","submitted_at":"2026-05-07T12:51:49Z","title":"Post Reasoning: Improving the Performance of Non-Thinking Models at No Cost","version":1},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-05-08T10:19:08.451445Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2605.06165"},"observation_digest":"sha256:dad294de01662aba412d0b5cec52598e0499d28a502843cd193a02aea4686d43","observation_id":"257fd052-7856-427a-88d3-1997b0eaf416","resolution":{"observed_at":"2026-05-11T20:06:09.846451Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2605.20075","last_updated":"2026-05-19T16:28:53Z","snapshot_observed_at":"2026-08-01T16:11:19.969726Z","submitted_at":"2026-05-19T16:28:53Z","title":"CopT: Contrastive On-Policy Thinking with Continuous Spaces for General and Agentic Reasoning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-20T05:25:51.655208Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2605.20075"},"observation_digest":"sha256:1724daae702c53b9b60cb2bced3903256fe35c7f3d9e045dca8439188acaa7fb","observation_id":"72fca595-5a26-455f-a709-3e333dc086a7","resolution":{"observed_at":"2026-05-20T05:28:04.865743Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2605.21951","last_updated":"2026-05-21T03:35:10Z","snapshot_observed_at":"2026-07-31T14:36:47.956964Z","submitted_at":"2026-05-21T03:35:10Z","title":"Dynamic Mixture of Latent Memories for Self-Evolving Agents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-22T07:38:42.113849Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2605.21951"},"observation_digest":"sha256:20a9743f185cf61f150ee2b528cf3db1210dcc04e8f9ebe1e8e6ed4465ef2222","observation_id":"71242dd4-2bd4-475b-8333-46b4f4586639","resolution":{"observed_at":"2026-05-22T07:41:14.556752Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2606.01168","last_updated":"2026-05-31T11:20:00Z","snapshot_observed_at":"2026-08-06T06:07:10.957400Z","submitted_at":"2026-05-31T11:20:00Z","title":"Thinking Economically: A Hierarchical Framework for Adaptive-Complexity Reasoning in LLMs","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-06-28T17:05:48.244094Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2606.01168"},"observation_digest":"sha256:218a1ded477d17d5d123bd84913db7fadf39ba23e7df86560a87776346647f69","observation_id":"ed19f37c-fe99-4b86-942d-2388e7de959a","resolution":{"observed_at":"2026-06-28T17:12:25.235310Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2606.02248","last_updated":"2026-06-01T13:40:55Z","snapshot_observed_at":"2026-08-02T08:45:16.160949Z","submitted_at":"2026-06-01T13:40:55Z","title":"Geometric Latent Reasoning Induces Shorter Generations in LLMs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-28T15:06:16.659461Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2606.02248"},"observation_digest":"sha256:d0d4a78043fe72251d94ad06769befe9b2250bb2d5cda72e5f39c7b0e971dfa1","observation_id":"8bbeb32d-f114-491a-8f71-18b3b3cf45c6","resolution":{"observed_at":"2026-07-01T22:46:19.052103Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":"2502.12134","doi":"10.48550/arxiv.2502.12134","metadata_source":"arxiv_reference","pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","venue":"ArXiv.org","work_id":"e57244aa-94b3-4af3-b68e-8169c9afc8ea","year":2025},"citing_paper":{"arxiv_id":"2606.09563","last_updated":"2026-06-08T14:37:46Z","snapshot_observed_at":"2026-08-01T00:37:11.487032Z","submitted_at":"2026-06-08T14:37:46Z","title":"PRISM: Recovering Instruction Sets from Language Model Activations","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-06-27T16:52:02.948457Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2606.09563"},"observation_digest":"sha256:18e525456488121b23607b4b973013f433dfb68d66ebd95471e72199dc0f856a","observation_id":"f1455cfd-644f-41ed-9c8e-6f38193f5430","resolution":{"observed_at":"2026-06-27T17:01:08.094017Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T15:52:33.292495+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.12134","snapshot_observed_at":"2026-08-01T18:49:31.791043Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.17188","last_updated":"2026-07-19T11:00:59Z","snapshot_observed_at":"2026-08-07T17:24:54.089188Z","submitted_at":"2026-07-19T11:00:59Z","title":"Is Your Model Thinking or Just Stagnating? PUMA: Diagnosing Reasoning Pathology via Phase-Momentum Alignment","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-01T18:49:31.791043Z"},"links":{"cited_paper":"/paper/2502.12134","citing_paper":"/paper/2607.17188"},"observation_digest":"sha256:426b05f023dd95ee0a6da14e7db86723ee37bcbc13a3731423cc05cfac4616b4","observation_id":"928fa9fd-707a-4342-a50a-98fed0c3dd7d","resolution":{"observed_at":"2026-08-01T18:49:31.791043Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.12134/citation-record","integrity":"/paper/2502.12134/integrity","json":"/paper/2502.12134/citation-record.json","paper":"/paper/2502.12134"},"outbound":[],"paper":{"arxiv_id":"2502.12134","last_updated":"2025-05-27T14:54:51Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T18:11:21.121498Z","submitted_at":"2025-02-17T18:52:29Z","title":"SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:2502.12134."}