{"as_of":"2026-08-15T21:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:45cbb9fe372fddb41e58b7b3462d1cb9b2ba4efb9530d07f4dc616c7bda111c7","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T21:57:50.843278Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:42:27.601318Z","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":"2026-08-04T23:56:34.941740Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.03226","snapshot_observed_at":"2026-08-07T14:42:27.601318Z","title":"Booststep: Boosting mathematical capability of large language models via improved single-step reasoning.arXiv preprint arXiv:2501.03226, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.18065","last_updated":"2025-05-23T16:12:12Z","snapshot_observed_at":"2026-08-15T14:53:00.799514Z","submitted_at":"2025-05-23T16:12:12Z","title":"Reward Model Generalization for Compute-Aware Test-Time Reasoning","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T14:42:27.601318Z"},"links":{"cited_paper":"/paper/2501.03226","citing_paper":"/paper/2505.18065"},"observation_digest":"sha256:477d84ec8bf0341f32f1200e6c1a6c84a4528bfc3e810254e99fe5e3dc2497c0","observation_id":"55695bc1-c234-4fde-aef1-1f7a950991d9","resolution":{"observed_at":"2026-08-07T14:42:27.601318Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"cited_work":{"arxiv_id":"2501.03226","doi":null,"metadata_source":"pith","pith_arxiv_id":"2501.03226","snapshot_observed_at":"2026-08-04T23:56:34.941740Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","venue":"cs.CL","work_id":"ee3d1a8f-d6a4-4b39-b339-2d11bca4c0ff","year":2025},"citing_paper":{"arxiv_id":"2509.06284","last_updated":"2025-09-08T02:11:49Z","snapshot_observed_at":"2026-08-15T00:06:04.457082Z","submitted_at":"2025-09-08T02:11:49Z","title":"From Implicit Exploration to Structured Reasoning: Leveraging Guideline and Refinement for LLMs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-04T23:56:34.903930Z"},"links":{"cited_paper":"/paper/2501.03226","citing_paper":"/paper/2509.06284"},"observation_digest":"sha256:8ca5a2739c702b6e62dfcc22d0a92b781ca2098dbc63ba0f2a7792d25d3340ec","observation_id":"dcd1332c-298e-4032-89b0-f7deb58b1d2a","resolution":{"observed_at":"2026-08-04T23:56:34.946482Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.03226/citation-record","integrity":"/paper/2501.03226/integrity","json":"/paper/2501.03226/citation-record.json","paper":"/paper/2501.03226"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.692055Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.692055Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:829495b98bc7fd1655d72c5a732c5c5c438a53b957751b697cf494e413182e66","observation_id":"73cd10e2-b787-4819-867f-76ad3823bbdc","resolution":{"observed_at":"2026-08-10T21:57:50.692055Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10858","last_updated":"2024-09-27T08:03:07Z","snapshot_observed_at":"2026-08-15T12:12:27.630427Z","submitted_at":"2024-06-16T09:06:17Z","title":"Step-level Value Preference Optimization for Mathematical Reasoning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.10858","snapshot_observed_at":"2026-08-10T21:57:50.695810Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.695810Z"},"links":{"cited_paper":"/paper/2406.10858","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:f65f2a6d318798d3adb2c2ae405d0a5dfa0a245b029eacddf9fc2ccd7c865126","observation_id":"e7183681-11f1-4634-a67a-e1a621731655","resolution":{"observed_at":"2026-08-10T21:57:50.695810Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.699809Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.699809Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:234535e1877fab4e0a6b6eca2b79af5c8312cf8c72d8ebc70a00d3553d01dba7","observation_id":"8b21918d-d856-4008-a576-77c46510e5a5","resolution":{"observed_at":"2026-08-10T21:57:50.699809Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14835","last_updated":"2024-12-19T13:25:39Z","snapshot_observed_at":"2026-08-15T00:18:31.213910Z","submitted_at":"2024-12-19T13:25:39Z","title":"Progressive Multimodal Reasoning via Active Retrieval","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.14835","snapshot_observed_at":"2026-08-10T21:57:50.703760Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.703760Z"},"links":{"cited_paper":"/paper/2412.14835","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:3244f21035891086bf6323870e9fdd3f91817e48558633ae49a6bfaf8afce731","observation_id":"ef22bbf5-cc1d-4843-a697-055e0af9b851","resolution":{"observed_at":"2026-08-10T21:57:50.703760Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.707701Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.707701Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:7e709b24dbab701d29ed6e4acbd51ad17eb9813487bf3c77e306dffae63f0421","observation_id":"d0c2e2a2-96dc-4cfd-9b81-22de73023ede","resolution":{"observed_at":"2026-08-10T21:57:50.707701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-13T17:20:44.002518Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-10T21:57:50.711302Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.711302Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:ba482d88fc8d0c6e1b72cffac5008a2f6aeb9521fff4daed58b5153fcadca660","observation_id":"ad2203c6-e99d-4243-8527-2de482c6c2d7","resolution":{"observed_at":"2026-08-10T21:57:50.711302Z","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":"2026-08-10T21:57:51.181145Z","title":null,"venue":null,"work_id":"89d7462c-e2e8-4621-9d0d-46be9418b855","year":1963},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.715436Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:9123c98e80ae396f53a20137b0b04d426f8bfc435f92817ef769fbd21076142d","observation_id":"42726751-0a41-4b8b-98b5-cc24c75405a2","resolution":{"observed_at":"2026-08-10T21:57:51.184839Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.17179","last_updated":"2024-02-09T00:13:46Z","snapshot_observed_at":"2026-08-15T12:53:06.624601Z","submitted_at":"2023-09-29T12:20:19Z","title":"Alphazero-like Tree-Search can Guide Large Language Model Decoding and Training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.17179","snapshot_observed_at":"2026-08-10T21:57:50.718863Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.718863Z"},"links":{"cited_paper":"/paper/2309.17179","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:5e5cc5d186a35304b3018102e7ad065c1dfb2a0e46d8353529022055faa53ef4","observation_id":"d7acb99e-dda2-4a48-8d3c-85826cb4ee4a","resolution":{"observed_at":"2026-08-10T21:57:50.718863Z","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":"2026-08-10T21:57:51.169389Z","title":null,"venue":null,"work_id":"4bfc13d5-3bc9-4bf0-b129-76ebb29d2772","year":1985},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.722446Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:830a5e3f16f83c823571a56ba1b466ebf5a31c4d66ab6ba22054d6a264701e70","observation_id":"8fb950f8-d8db-4c50-a3d1-595909c76fea","resolution":{"observed_at":"2026-08-10T21:57:51.173882Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11738","last_updated":"2024-02-21T12:59:21Z","snapshot_observed_at":"2026-07-31T18:12:14.483728Z","submitted_at":"2023-05-19T15:19:44Z","title":"CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11738","snapshot_observed_at":"2026-08-10T21:57:50.726466Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.726466Z"},"links":{"cited_paper":"/paper/2305.11738","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:e0fb80f2ea1bda97a496a88709abb1255295f6e945d095f467a7d0c83dab19be","observation_id":"96742cba-428e-42de-993a-d940e9060dba","resolution":{"observed_at":"2026-08-10T21:57:50.726466Z","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":"2026-08-15T12:33:55.451951Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-10T21:57:50.729935Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.729935Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:3dc76e63605b03dcc74bde3e53c3ac3339d3183be62ee71723a1a376a524c2c3","observation_id":"b37d7a09-5d96-4c3d-a25b-57dd23f00ddb","resolution":{"observed_at":"2026-08-10T21:57:50.729935Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14008","last_updated":"2024-06-06T13:19:44Z","snapshot_observed_at":"2026-08-03T03:39:09.398343Z","submitted_at":"2024-02-21T18:49:26Z","title":"OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14008","snapshot_observed_at":"2026-08-10T21:57:50.733983Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.733983Z"},"links":{"cited_paper":"/paper/2402.14008","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:01dbbf6d1a8e740ec39104469c9e0d9cd2c9df6581d16ef8b4bb82d026686ee4","observation_id":"cd3d5a20-9039-4e0c-b036-351fa284213a","resolution":{"observed_at":"2026-08-10T21:57:50.733983Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.03874","last_updated":"2021-11-08T21:30:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-03-05T18:59:39Z","title":"Measuring Mathematical Problem Solving With the MATH Dataset","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.03874","snapshot_observed_at":"2026-08-10T21:57:50.737581Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.737581Z"},"links":{"cited_paper":"/paper/2103.03874","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:bf0596c2ddc0dfb1d56f93781b382e0d63515f7b81860499e4d585b870b7e4b1","observation_id":"5ee6192c-4bea-418f-b28a-890186e6b66a","resolution":{"observed_at":"2026-08-10T21:57:50.737581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21276","last_updated":"2024-10-25T17:43:01Z","snapshot_observed_at":"2026-08-15T14:02:47.366139Z","submitted_at":"2024-10-25T17:43:01Z","title":"GPT-4o System Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21276","snapshot_observed_at":"2026-08-10T21:57:50.741208Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.741208Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:adc8c993e89fca017f8e13d6950c4d1b31a582ec0e88f6287567b6f3f7925c59","observation_id":"42a8d1eb-e494-4acf-964c-1f4ce2b90149","resolution":{"observed_at":"2026-08-10T21:57:50.741208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.744888Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.744888Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:2bded8383d8c478fd0a728468a270d045e64a17d0ab6498cbc1db11c38e68971","observation_id":"62531d21-1b7d-4698-a791-da3e14aaa55b","resolution":{"observed_at":"2026-08-10T21:57:50.744888Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.748206Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.748206Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:fb5a14e2446cb31e58af6395de5d1ea5858b4af0a1bc693c770f5bbd2868b061","observation_id":"c01ef0fb-c1e4-491b-9f98-b51710cf0cb8","resolution":{"observed_at":"2026-08-10T21:57:50.748206Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.751499Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.751499Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:7996da74c6978a079f5bac511eb3cb17221d5c3c892a72a1c750bf87256f3775","observation_id":"acd04190-abff-4f34-8c21-f7735471c93d","resolution":{"observed_at":"2026-08-10T21:57:50.751499Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.20050","last_updated":"2023-05-31T17:24:00Z","snapshot_observed_at":"2026-08-11T17:22:43.545531Z","submitted_at":"2023-05-31T17:24:00Z","title":"Let's Verify Step by Step","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.20050","snapshot_observed_at":"2026-08-10T21:57:50.754686Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.754686Z"},"links":{"cited_paper":"/paper/2305.20050","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:89ba040c2743bd3832eefb2869a39d359fc67929067a5d65dae5800741df0dd9","observation_id":"8dc9c58d-c3e0-42a1-8bdd-c78c5ac41870","resolution":{"observed_at":"2026-08-10T21:57:50.754686Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1705.04146","last_updated":"2017-10-23T16:45:03Z","snapshot_observed_at":"2026-08-14T21:01:22.490456Z","submitted_at":"2017-05-11T13:04:47Z","title":"Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.04146","snapshot_observed_at":"2026-08-10T21:57:50.757835Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.757835Z"},"links":{"cited_paper":"/paper/1705.04146","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:4e3c5dabd32fef2e1180fc7edced32966bd58d0cf1f60f851330d6db5d8b9907","observation_id":"852fced7-c45f-4acf-886c-eb448d34ec3e","resolution":{"observed_at":"2026-08-10T21:57:50.757835Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12209","last_updated":"2024-05-20T17:52:29Z","snapshot_observed_at":"2026-08-13T15:51:50.035268Z","submitted_at":"2024-05-20T17:52:29Z","title":"MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics Benchmark","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12209","snapshot_observed_at":"2026-08-10T21:57:50.761801Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.761801Z"},"links":{"cited_paper":"/paper/2405.12209","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:6834b43fcd04f2eaab5d62392d7979e198c68275b5b5af63a29f4529a3efcfb7","observation_id":"ceb7efa3-2cf8-4dc0-a6f7-230339f2e9bf","resolution":{"observed_at":"2026-08-10T21:57:50.761801Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12157","last_updated":"2024-12-11T11:38:11Z","snapshot_observed_at":"2026-08-14T03:51:37.613577Z","submitted_at":"2024-12-11T11:38:11Z","title":"What Makes In-context Learning Effective for Mathematical Reasoning: A Theoretical Analysis","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.12157","snapshot_observed_at":"2026-08-10T21:57:50.765365Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.765365Z"},"links":{"cited_paper":"/paper/2412.12157","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:fb3a49bb5645930d2b9f979a87c5d5986c0a7377393d7abe4ff24bd16dc95b22","observation_id":"3737c199-ca52-41f9-ac2f-5f75f358194a","resolution":{"observed_at":"2026-08-10T21:57:50.765365Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.06592","last_updated":"2024-12-11T22:59:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-06-05T19:25:40Z","title":"Improve Mathematical Reasoning in Language Models by Automated Process Supervision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.06592","snapshot_observed_at":"2026-08-10T21:57:50.768815Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.768815Z"},"links":{"cited_paper":"/paper/2406.06592","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:2650f3e517b4931c55f94d1d3993b78300bdeb4cd3949a283b8e856bcff3ec99","observation_id":"2ab212a4-aae9-415a-ae89-b4457ebf7174","resolution":{"observed_at":"2026-08-10T21:57:50.768815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.772411Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.772411Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:b29a956281d54dcec532585c4b07c83f642fa982d5dfc94aaaf8aad77f953567","observation_id":"bd64591e-8fed-4a13-9da8-bd581138fd7c","resolution":{"observed_at":"2026-08-10T21:57:50.772411Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.775682Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.775682Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:39f0397ad9278deb7dc0a1bf377a5e33d79f0775405e9063fa89f93f2113b3c7","observation_id":"9397312e-be06-45a2-8ba6-3e838f8d4428","resolution":{"observed_at":"2026-08-10T21:57:50.775682Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-08-06T14:58:42.911363Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-10T21:57:50.779279Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.779279Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:10e024fb3bc6676bd5d30d9da5babff0f0231e1a9f81082c048595cf2369105b","observation_id":"21b2ec6b-3f19-4da0-ba26-84fb578f7c85","resolution":{"observed_at":"2026-08-10T21:57:50.779279Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.782874Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.782874Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:fa7e99fa2927993dcc41be3254a77d9bc81d45d5c09fa60e845a4e89654ed8ed","observation_id":"789ba29a-d9e4-47b2-bc68-88fb084c36ae","resolution":{"observed_at":"2026-08-10T21:57:50.782874Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14804","last_updated":"2024-02-22T18:56:38Z","snapshot_observed_at":"2026-08-13T01:56:18.092262Z","submitted_at":"2024-02-22T18:56:38Z","title":"Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14804","snapshot_observed_at":"2026-08-10T21:57:50.786405Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.786405Z"},"links":{"cited_paper":"/paper/2402.14804","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:e92de6c061d3a89037e76f42d2920fe23f5cd0a9a00b0d0876d1e48277f3077a","observation_id":"7d0f2e0e-dcfa-4a5a-a9aa-43fe4230366a","resolution":{"observed_at":"2026-08-10T21:57:50.786405Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.790276Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.790276Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:09a8978fd6ea78447e72c6f3698ad2660d8e4b69b51bf7be92b842795bbe2d6d","observation_id":"8ac77472-2bdd-4d94-9765-16a118160bc6","resolution":{"observed_at":"2026-08-10T21:57:50.790276Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.793845Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.793845Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:2917e895ed0bc093df53cac8357f96e492be3b53f413627ca1ae6d28f6a4cd7a","observation_id":"daa3ecb5-7879-4890-95d4-427b22548dac","resolution":{"observed_at":"2026-08-10T21:57:50.793845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.18478","last_updated":"2025-06-02T14:26:19Z","snapshot_observed_at":"2026-08-12T11:06:55.886082Z","submitted_at":"2024-11-27T16:19:00Z","title":"Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.18478","snapshot_observed_at":"2026-08-10T21:57:50.797300Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.797300Z"},"links":{"cited_paper":"/paper/2411.18478","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:7198be5e68470088dbf1b351ed0f1718f079a8cfd1a065d4e41d4ed0b04718eb","observation_id":"9e9f04ab-a74c-4ecc-8f5a-1d56326c0da6","resolution":{"observed_at":"2026-08-10T21:57:50.797300Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.02893","last_updated":"2024-04-03T17:51:18Z","snapshot_observed_at":"2026-08-13T00:38:17.242638Z","submitted_at":"2024-04-03T17:51:18Z","title":"ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.02893","snapshot_observed_at":"2026-08-10T21:57:50.801235Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.801235Z"},"links":{"cited_paper":"/paper/2404.02893","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:583aa919af6600fe2bcf3ae751da08c0a1553cae0744c8d633ca0817f5bf2c5c","observation_id":"bd4b49f9-6d42-4d52-b648-a20896383a4d","resolution":{"observed_at":"2026-08-10T21:57:50.801235Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12122","last_updated":"2024-09-18T16:45:37Z","snapshot_observed_at":"2026-08-14T16:00:41.902820Z","submitted_at":"2024-09-18T16:45:37Z","title":"Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.12122","snapshot_observed_at":"2026-08-10T21:57:50.805065Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.805065Z"},"links":{"cited_paper":"/paper/2409.12122","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:608e6180c5ffa24cbe5ba0b29ee7a88c7fdfaaf3519f31449377c4c8f6d6990d","observation_id":"1ec872e5-7cc0-4b3f-ae9f-8343b719dac5","resolution":{"observed_at":"2026-08-10T21:57:50.805065Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.809682Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.809682Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:b7a442c4718a203435e13654ce4731fac81074713323998d151adc2681472edc","observation_id":"5acbc9f7-2ead-44cf-9640-7cc46298b434","resolution":{"observed_at":"2026-08-10T21:57:50.809682Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.06332","last_updated":"2024-05-24T07:09:21Z","snapshot_observed_at":"2026-08-13T04:22:39.632135Z","submitted_at":"2024-02-09T11:22:08Z","title":"InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.06332","snapshot_observed_at":"2026-08-10T21:57:50.813252Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.813252Z"},"links":{"cited_paper":"/paper/2402.06332","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:b82b1dfb63ceada9f30f7fb870b443071e95ad057a133ac88affc8412252b457","observation_id":"97ac88ec-9922-4116-87aa-94f04d9786ed","resolution":{"observed_at":"2026-08-10T21:57:50.813252Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05653","last_updated":"2023-10-03T02:48:42Z","snapshot_observed_at":"2026-08-07T14:43:09.380195Z","submitted_at":"2023-09-11T17:47:22Z","title":"MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05653","snapshot_observed_at":"2026-08-10T21:57:50.817153Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.817153Z"},"links":{"cited_paper":"/paper/2309.05653","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:755c65a0b64511896ffcc28e8586e554f16dbe772b38be6ed52b8d8eb2dc739c","observation_id":"e5171beb-f855-4537-a9a3-7e61f0748c96","resolution":{"observed_at":"2026-08-10T21:57:50.817153Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07394","last_updated":"2024-06-13T07:19:06Z","snapshot_observed_at":"2026-08-12T23:45:25.243322Z","submitted_at":"2024-06-11T16:01:07Z","title":"Accessing GPT-4 level Mathematical Olympiad Solutions via Monte Carlo Tree Self-refine with LLaMa-3 8B","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.07394","snapshot_observed_at":"2026-08-10T21:57:50.821847Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.821847Z"},"links":{"cited_paper":"/paper/2406.07394","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:727342b3fa470971d650a7bcbbdf08bc7aeb35d8ccf0822e948d94903293f4b3","observation_id":"66a9c45e-6beb-43d8-ab05-0d39920eb7b4","resolution":{"observed_at":"2026-08-10T21:57:50.821847Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02884","last_updated":"2024-11-21T07:07:59Z","snapshot_observed_at":"2026-08-12T22:31:19.889900Z","submitted_at":"2024-10-03T18:12:29Z","title":"LLaMA-Berry: Pairwise Optimization for O1-like Olympiad-Level Mathematical Reasoning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02884","snapshot_observed_at":"2026-08-10T21:57:50.825944Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.825944Z"},"links":{"cited_paper":"/paper/2410.02884","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:136576dfda24fafcfc970ec5aceb9cf97e3f694158fc60388ab8fb567a387af0","observation_id":"36a2a22f-dce7-4fa1-8790-b4e62d1ae012","resolution":{"observed_at":"2026-08-10T21:57:50.825944Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.830096Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.830096Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:bc535791736a4470f63aaecebd8ae0f69f0a06b7ccd68791f624e86ff6f84502","observation_id":"37a84b5f-7e5a-4c62-ae92-8f647aaf3125","resolution":{"observed_at":"2026-08-10T21:57:50.830096Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.16257","last_updated":"2023-12-29T15:36:05Z","snapshot_observed_at":"2026-08-13T13:54:21.010998Z","submitted_at":"2022-10-28T16:47:03Z","title":"Solving Math Word Problems via Cooperative Reasoning induced Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.16257","snapshot_observed_at":"2026-08-10T21:57:50.833952Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.833952Z"},"links":{"cited_paper":"/paper/2210.16257","citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:c2cd3ee100232ab4663d69d1bf92d177e506e82218d5db61853fbbcaa3895465","observation_id":"ee06c3fe-f6dd-4492-b1d4-c93a6e9ed166","resolution":{"observed_at":"2026-08-10T21:57:50.833952Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.838297Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.838297Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:978fff31ca6c4b979d9b5bc6776d7b5e737b0fc9710a727c5a018e016ad29405","observation_id":"3d516fb1-b2fe-47bd-aeef-a178a509438f","resolution":{"observed_at":"2026-08-10T21:57:50.838297Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T21:57:50.843278Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning","version":3},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-10T21:57:50.843278Z"},"links":{"citing_paper":"/paper/2501.03226"},"observation_digest":"sha256:dfc5eccea7295f6c4e0feec75f8abca2339e833c7b79f95179c9a316fb5c267b","observation_id":"1f6ff3a9-681c-4a16-b456-f8edba9aa03d","resolution":{"observed_at":"2026-08-10T21:57:50.843278Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.03226","last_updated":"2025-02-17T06:27:16Z","latest_version":3,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-11T02:32:28.940981Z","submitted_at":"2025-01-06T18:59:13Z","title":"BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoning"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":41,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":41},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 2 inbound Pith citation observations for arXiv:2501.03226."}