{"as_of":"2026-08-04T16:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:75cabd8d8c9b26e8888b5083c710f01b8a82f7e70bc7b44e4d8266551f912d01","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":13,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":13,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":13,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":13,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T01:57:53.449669Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T13:28:18.208570Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2505.17667","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-07-03T13:28:18.208570Z","title":"Qwenlong-l1: Towards long-context large reasoning models with reinforcement learning","venue":null,"work_id":"5eb4668b-c05a-469e-87fa-d57ca82bfefb","year":2025},"citing_paper":{"arxiv_id":"2507.02259","last_updated":"2026-07-29T12:55:39Z","snapshot_observed_at":"2026-08-01T23:32:07.108143Z","submitted_at":"2025-07-03T03:11:50Z","title":"MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-15T11:17:24.406028Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2507.02259"},"observation_digest":"sha256:eb2f3c2539b68f589e15b99c7f2e54221730f06e83979fa30622d3ae0475ac9c","observation_id":"3e123b75-b515-4470-9423-af84373323fd","resolution":{"observed_at":"2026-05-15T11:17:24.509718Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2505.17667","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-07-03T13:28:18.208570Z","title":"Qwenlong-l1: Towards long-context large reasoning models with reinforcement learning","venue":null,"work_id":"5eb4668b-c05a-469e-87fa-d57ca82bfefb","year":2025},"citing_paper":{"arxiv_id":"2508.06471","last_updated":"2025-08-08T17:21:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-08T17:21:06Z","title":"GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-11T17:50:08.399160Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2508.06471"},"observation_digest":"sha256:a0bbb25c3464396b9242df39e9a370ee46b1f8ef17fc24277dfe3a577073436b","observation_id":"8b38a9a7-7814-4433-8295-e3566f2c684b","resolution":{"observed_at":"2026-05-11T17:50:08.524006Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2505.17667","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-07-03T13:28:18.208570Z","title":"Qwenlong-l1: Towards long-context large reasoning models with reinforcement learning","venue":null,"work_id":"5eb4668b-c05a-469e-87fa-d57ca82bfefb","year":2025},"citing_paper":{"arxiv_id":"2604.02371","last_updated":"2026-06-29T16:52:45Z","snapshot_observed_at":"2026-07-13T15:50:48.216413Z","submitted_at":"2026-03-31T04:41:01Z","title":"Internalized Reasoning for Long-Context Visual Document Understanding","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-13T23:53:19.148407Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2604.02371"},"observation_digest":"sha256:3dd208619ee19cace61f250b8b67847c134adb2046beee745baabe3b98115b83","observation_id":"2cbaf1f8-7acd-4ada-b28d-537dea77f30a","resolution":{"observed_at":"2026-05-13T23:53:28.051553Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-07-13T15:50:49.083652Z","title":"Qwenlong-l1: Towards long-context large reasoning models with reinforcement learning, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2604.02371","last_updated":"2026-06-29T16:52:45Z","snapshot_observed_at":"2026-07-13T15:50:48.216413Z","submitted_at":"2026-03-31T04:41:01Z","title":"Internalized Reasoning for Long-Context Visual Document Understanding","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-07-13T15:50:49.083652Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2604.02371"},"observation_digest":"sha256:bfd0ff48fdead60522cac5d5fd6155673c62964b0afb828402481ed67b294462","observation_id":"7416320e-45b1-46f1-b594-5636eb518597","resolution":{"observed_at":"2026-07-13T15:50:49.083652Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2505.17667","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-07-03T13:28:18.208570Z","title":"Qwenlong-l1: Towards long-context large reasoning models with reinforcement learning","venue":null,"work_id":"5eb4668b-c05a-469e-87fa-d57ca82bfefb","year":2025},"citing_paper":{"arxiv_id":"2604.07981","last_updated":"2026-04-09T08:51:47Z","snapshot_observed_at":"2026-08-02T08:53:17.527801Z","submitted_at":"2026-04-09T08:51:47Z","title":"A Decomposition Perspective to Long-context Reasoning for LLMs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T18:05:34.666937Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2604.07981"},"observation_digest":"sha256:b2d331bb0829e9ff49714b6fc9af1cb1b5c0e4d5d0b7aef05e806913968adf41","observation_id":"12109965-067d-4e1f-af18-3eafcfa9dc17","resolution":{"observed_at":"2026-05-11T05:31:00.039292Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2505.17667","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-07-03T13:28:18.208570Z","title":"Qwenlong-l1: Towards long-context large reasoning models with reinforcement learning","venue":null,"work_id":"5eb4668b-c05a-469e-87fa-d57ca82bfefb","year":2025},"citing_paper":{"arxiv_id":"2604.14922","last_updated":"2026-04-16T12:06:59Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-16T12:06:59Z","title":"LongAct: Harnessing Intrinsic Activation Patterns for Long-Context Reinforcement Learning","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-05-10T11:17:43.769244Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2604.14922"},"observation_digest":"sha256:a86830b4a8c7f70ac9e4b1be72bb6975f4b8e054ed01381bb35bfb3d8f178a27","observation_id":"36cfaa94-33ae-4009-9417-ef4af0b4d499","resolution":{"observed_at":"2026-05-10T11:20:10.482511Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2505.17667","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-07-03T13:28:18.208570Z","title":"Qwenlong-l1: Towards long-context large reasoning models with reinforcement learning","venue":null,"work_id":"5eb4668b-c05a-469e-87fa-d57ca82bfefb","year":2025},"citing_paper":{"arxiv_id":"2604.17535","last_updated":"2026-04-19T16:53:56Z","snapshot_observed_at":"2026-07-06T23:04:37.370465Z","submitted_at":"2026-04-19T16:53:56Z","title":"OPSDL: On-Policy Self-Distillation for Long-Context Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-10T06:07:36.830550Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2604.17535"},"observation_digest":"sha256:dc21c84e0d350d07803a67439f48ee2f186cb8a696eba608b5853a3b9d24eed4","observation_id":"a4c46b9d-afc2-44c0-8e74-c1e1e34d5cff","resolution":{"observed_at":"2026-05-10T06:11:20.402410Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2505.17667","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-07-03T13:28:18.208570Z","title":"Qwenlong-l1: Towards long-context large reasoning models with reinforcement learning","venue":null,"work_id":"5eb4668b-c05a-469e-87fa-d57ca82bfefb","year":2025},"citing_paper":{"arxiv_id":"2605.04831","last_updated":"2026-05-06T12:28:17Z","snapshot_observed_at":"2026-07-06T23:17:33.252539Z","submitted_at":"2026-05-06T12:28:17Z","title":"StoryAlign: Evaluating and Training Reward Models for Story Generation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-08T17:29:13.549559Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2605.04831"},"observation_digest":"sha256:61305643917250503f17fdc3738d2c7a5a561811e4db5b447edf665df42ce6e3","observation_id":"6e5e2916-47b9-4935-9b3a-d04314fb4766","resolution":{"observed_at":"2026-05-11T17:31:07.683022Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2505.17667","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-07-03T13:28:18.208570Z","title":"Qwenlong-l1: Towards long-context large reasoning models with reinforcement learning","venue":null,"work_id":"5eb4668b-c05a-469e-87fa-d57ca82bfefb","year":2025},"citing_paper":{"arxiv_id":"2605.12227","last_updated":"2026-06-16T16:53:23Z","snapshot_observed_at":"2026-07-06T23:23:59.123377Z","submitted_at":"2026-05-12T15:04:18Z","title":"A Recipe for Long-Context Reasoning in Large Language Models via On-Policy Optimization and Distillation","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-05-13T05:29:00.576006Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2605.12227"},"observation_digest":"sha256:75b8f194534730de686cc0cfbe97f3204034940d208e3f84b89ba8625779292b","observation_id":"e6d73681-e8af-4b44-bf0c-fa94aad81275","resolution":{"observed_at":"2026-05-13T05:32:19.432348Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2505.17667","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-07-03T13:28:18.208570Z","title":"Qwenlong-l1: Towards long-context large reasoning models with reinforcement learning","venue":null,"work_id":"5eb4668b-c05a-469e-87fa-d57ca82bfefb","year":2025},"citing_paper":{"arxiv_id":"2607.02073","last_updated":"2026-07-02T12:11:49Z","snapshot_observed_at":"2026-08-01T01:57:32.190005Z","submitted_at":"2026-07-02T12:11:49Z","title":"Evidence-State Rewards for Long-Context Reasoning","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-03T13:25:14.844589Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2607.02073"},"observation_digest":"sha256:fa12eecdc5ec54dd8f133ca1a490e49d4e3247addbac47530cf4439ffd17a103","observation_id":"c837ddf0-367f-4f48-9c06-6fa5362361eb","resolution":{"observed_at":"2026-07-03T13:28:18.210189Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-08-01T12:46:03.589144Z","title":"Fanqi Wan, Weizhou Shen, Shengyi Liao, Yingcheng Shi, Chenliang Li, Ziyi Yang, Ji Zhang, Fei Huang, Jingren Zhou, and Ming Yan","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.19345","last_updated":"2026-07-31T16:09:53Z","snapshot_observed_at":"2026-08-04T16:30:54.379761Z","submitted_at":"2026-07-21T17:59:21Z","title":"Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T12:46:03.589144Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2607.19345"},"observation_digest":"sha256:5968b0b46f062a65498757c5d6a7b278b281839be06f82847e3878303ee8bc2c","observation_id":"4e9f7c26-e957-4b75-b019-4d3c7c6d1dbf","resolution":{"observed_at":"2026-08-01T12:46:03.589144Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-08-03T01:57:53.449669Z","title":"Fanqi Wan, Weizhou Shen, Shengyi Liao, Yingcheng Shi, Chenliang Li, Ziyi Yang, Ji Zhang, Fei Huang, Jingren Zhou, and Ming Yan","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.19345","last_updated":"2026-07-31T16:09:53Z","snapshot_observed_at":"2026-08-04T16:30:54.379761Z","submitted_at":"2026-07-21T17:59:21Z","title":"Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-03T01:57:53.449669Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2607.19345"},"observation_digest":"sha256:48416a085a833f436a5cd23e8b0438bfe6a82b1bb76c35032c5928187169d11e","observation_id":"9f3e8f69-c2da-48ed-90f6-f9289cc9115d","resolution":{"observed_at":"2026-08-03T01:57:53.449669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.17667","snapshot_observed_at":"2026-08-01T09:18:46.780870Z","title":"2025.Qwenlong- l1: Towards long-context large reasoning models with reinforcement learning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20833","last_updated":"2026-07-29T08:05:59Z","snapshot_observed_at":"2026-08-02T12:08:43.253190Z","submitted_at":"2026-07-23T01:41:17Z","title":"REFACT: Adaptive Fact Restatement for Compact and Faithful Chain-of-Thought Reasoning","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T09:18:46.780870Z"},"links":{"cited_paper":"/paper/2505.17667","citing_paper":"/paper/2607.20833"},"observation_digest":"sha256:115392372b786a2a5677b80b004d88f35b81d6acb32ec15f134a56a35eb6ef88","observation_id":"ed144155-1032-4489-b5af-d358ca4d980e","resolution":{"observed_at":"2026-08-01T09:18:46.780870Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2505.17667/citation-record","integrity":"/paper/2505.17667/integrity","json":"/paper/2505.17667/citation-record.json","paper":"/paper/2505.17667"},"outbound":[],"paper":{"arxiv_id":"2505.17667","last_updated":"2025-05-27T09:39:47Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T21:29:11.652211Z","submitted_at":"2025-05-23T09:31:55Z","title":"QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning"},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2505.17667."}