{"as_of":"2026-08-11T01:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f8cd012fbf6c7ee4f3857b50a9bbf8f8b43b24a4cf5cf5c4b3db4102f86126a8","coverage":[{"denominator":52,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":52,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:13:41.081140Z","state":"measured"},{"denominator":65,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":65,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T13:41:59.147784Z","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":"2026-07-04T13:39:50.583619Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-08-04T08:55:58.708980Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.18383","last_updated":"2026-06-18T07:59:59Z","snapshot_observed_at":"2026-08-08T04:40:12.618095Z","submitted_at":"2025-10-21T08:03:14Z","title":"MENTOR: Reinforcement Learning via Flexible Teacher-Optimized Rewards for Tool-Use Distillation","version":3},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-04T08:55:58.708980Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2510.18383"},"observation_digest":"sha256:b5c2b5206571c5df282f0e7f584b90c9c23f7081d463c1cd831984246dcbc93b","observation_id":"b9cdfc19-79fd-438b-b499-37108b44385d","resolution":{"observed_at":"2026-08-04T08:55:58.708980Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-07-13T19:19:52.557913Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.26779","last_updated":"2026-05-31T01:38:33Z","snapshot_observed_at":"2026-08-06T23:53:55.163569Z","submitted_at":"2026-03-25T01:17:13Z","title":"Limits of Spatial Imagery Reasoning in Frontier LLM Models","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-13T19:19:52.557913Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2603.26779"},"observation_digest":"sha256:e2b6e092be26d9fcfe2e6d18070faaf121dc34c7d391b15e5014b2fef0e92a18","observation_id":"b12e3467-f880-4618-9804-96f11ab326a2","resolution":{"observed_at":"2026-07-13T19:19:52.557913Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":"2506.14728","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-07-04T13:39:50.583619Z","title":"Agentdistill: Training-free agent distillation with gener- alizable mcp boxes","venue":null,"work_id":"cdbcddc9-75ef-44de-8735-629463effa85","year":2025},"citing_paper":{"arxiv_id":"2604.06091","last_updated":"2026-05-02T14:33:16Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-07T17:04:21Z","title":"Social Dynamics as Critical Vulnerabilities that Undermine Objective Decision-Making in LLM Collectives","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T18:43:50.143866Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2604.06091"},"observation_digest":"sha256:91eaae8e58ad06e0717e86f0ab07a2a76bdeb79322a3d0015b9bfd94adcfabc9","observation_id":"cd630497-c1d1-488f-94a8-f4c66399a60c","resolution":{"observed_at":"2026-05-11T00:00:57.105348Z","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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":"2506.14728","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-07-04T13:39:50.583619Z","title":"Agentdistill: Training-free agent distillation with gener- alizable mcp boxes","venue":null,"work_id":"cdbcddc9-75ef-44de-8735-629463effa85","year":2025},"citing_paper":{"arxiv_id":"2605.07180","last_updated":"2026-05-08T03:18:40Z","snapshot_observed_at":"2026-08-10T21:41:30.191085Z","submitted_at":"2026-05-08T03:18:40Z","title":"Learning Agent Routing From Early Experience","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-05-11T01:15:07.381414Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2605.07180"},"observation_digest":"sha256:3c3d28fee5ae18e276b0283e2684c13a99e7cf6f9009c3590aa41b24d2fa7233","observation_id":"ff2e6df0-3fdf-4514-b7d1-39f8e5d60074","resolution":{"observed_at":"2026-05-11T04:35:57.749352Z","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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":"2506.14728","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-07-04T13:39:50.583619Z","title":"Agentdistill: Training-free agent distillation with gener- alizable mcp boxes","venue":null,"work_id":"cdbcddc9-75ef-44de-8735-629463effa85","year":2025},"citing_paper":{"arxiv_id":"2605.07358","last_updated":"2026-05-26T05:21:04Z","snapshot_observed_at":"2026-07-06T23:19:46.018236Z","submitted_at":"2026-05-08T07:10:26Z","title":"A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-05-11T01:47:39.926540Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2605.07358"},"observation_digest":"sha256:ed1a11cbaaaa82c55b50183a2b8d858fedd0b3e2637fb985bc3972d49d87a816","observation_id":"60e5ff4a-dbf4-4815-96fa-c979439eada3","resolution":{"observed_at":"2026-05-11T04:20:56.933868Z","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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":"2506.14728","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-07-04T13:39:50.583619Z","title":"Agentdistill: Training-free agent distillation with gener- alizable mcp boxes","venue":null,"work_id":"cdbcddc9-75ef-44de-8735-629463effa85","year":2025},"citing_paper":{"arxiv_id":"2605.07358","last_updated":"2026-05-26T05:21:04Z","snapshot_observed_at":"2026-07-06T23:19:46.018236Z","submitted_at":"2026-05-08T07:10:26Z","title":"A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-05-20T23:15:44.550045Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2605.07358"},"observation_digest":"sha256:5b1be56c6b61deb265c5f998b23f83eb1877d81de15353433379fa002edf3316","observation_id":"21ebe58b-5982-4443-af5f-bcdc8d34069d","resolution":{"observed_at":"2026-05-20T23:19:14.965828Z","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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":"2506.14728","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-07-04T13:39:50.583619Z","title":"Agentdistill: Training-free agent distillation with gener- alizable mcp boxes","venue":null,"work_id":"cdbcddc9-75ef-44de-8735-629463effa85","year":2025},"citing_paper":{"arxiv_id":"2605.07358","last_updated":"2026-05-26T05:21:04Z","snapshot_observed_at":"2026-07-06T23:19:46.018236Z","submitted_at":"2026-05-08T07:10:26Z","title":"A Comprehensive Survey on Agent Skills: Taxonomy, Techniques, and Applications","version":3},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-06-30T23:23:42.883286Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2605.07358"},"observation_digest":"sha256:9879ce68e24c103f24318569f47302e142b4f4520acf151958a0a473e041e0fe","observation_id":"f70fc99e-1935-41a3-957d-31160fc6c87d","resolution":{"observed_at":"2026-06-30T23:25:07.396202Z","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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":"2506.14728","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-07-04T13:39:50.583619Z","title":"Agentdistill: Training-free agent distillation with gener- alizable mcp boxes","venue":null,"work_id":"cdbcddc9-75ef-44de-8735-629463effa85","year":2025},"citing_paper":{"arxiv_id":"2605.07725","last_updated":"2026-08-03T03:33:59Z","snapshot_observed_at":"2026-08-09T22:35:00.024991Z","submitted_at":"2026-05-08T13:30:42Z","title":"SOD: Step-wise On-policy Distillation for Small Language Model Agents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-11T02:25:59.056181Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2605.07725"},"observation_digest":"sha256:b543c08d620d5db709e11f449a9e884d3b456a09850635d403d70d3ad1c0ff93","observation_id":"78e615e7-2449-4ac4-aa66-e2da5269144a","resolution":{"observed_at":"2026-05-11T03:40:54.398511Z","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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-08-04T05:20:45.006003Z","title":"Agentdistill: Training-free agent distillation with generalizable mcp boxes.arXiv preprint arXiv:2506.14728, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.07725","last_updated":"2026-08-03T03:33:59Z","snapshot_observed_at":"2026-08-09T22:35:00.024991Z","submitted_at":"2026-05-08T13:30:42Z","title":"SOD: Step-wise On-policy Distillation for Small Language Model Agents","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-04T05:20:45.006003Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2605.07725"},"observation_digest":"sha256:9da43396a96aeeeebbfc4d51880abd3d8414e836793546175cace870ef832712","observation_id":"9b4be4b9-947e-4fa0-84f5-a8bf8541b995","resolution":{"observed_at":"2026-08-04T05:20:45.006003Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":"2506.14728","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-07-04T13:39:50.583619Z","title":"Agentdistill: Training-free agent distillation with gener- alizable mcp boxes","venue":null,"work_id":"cdbcddc9-75ef-44de-8735-629463effa85","year":2025},"citing_paper":{"arxiv_id":"2606.26669","last_updated":"2026-06-25T07:02:32Z","snapshot_observed_at":"2026-07-29T15:47:51.578239Z","submitted_at":"2026-06-25T07:02:32Z","title":"SKILL-DISCO: Distilling and Compiling Agent Traces into Reusable Procedural Skills","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-06-26T05:03:35.457624Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2606.26669"},"observation_digest":"sha256:3e22a12574409a53404f71350aef85109515b7c05bc427f21a2bb98ba102fa68","observation_id":"3926dbe7-7995-4e3d-a6e7-c4548323d02d","resolution":{"observed_at":"2026-07-04T13:39:50.585265Z","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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-08-01T19:47:37.868208Z","title":"Agentdistill: Training-free agent distillation with generalizable mcp boxes.arXiv preprint arXiv:2506.14728, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.16851","last_updated":"2026-07-18T15:23:45Z","snapshot_observed_at":"2026-08-07T22:19:21.531544Z","submitted_at":"2026-07-18T15:23:45Z","title":"AgentBrew: Lifelong Knowledge Brewing from Strong Teachers to Weak LLM Agents","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T19:47:37.868208Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2607.16851"},"observation_digest":"sha256:399aa2f08cb56fbb13d0c5f04a68a33f70b2bfac1d4a939a3919b31ac24b7358","observation_id":"08c2aabf-7d06-41c1-bab8-e2337eb7ef2b","resolution":{"observed_at":"2026-08-01T19:47:37.868208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-08-02T08:56:35.330429Z","title":"(2025).AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes.CoRR, abs/2506.14728.https://doi.org/10.48550/arXiv.2506.14728","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19395","last_updated":"2026-07-03T05:07:22Z","snapshot_observed_at":"2026-08-07T06:27:15.086404Z","submitted_at":"2026-07-03T05:07:22Z","title":"From Trajectories to Prefixes: Reusing Teacher Trajectories via Replayed Prefixes and Online Continuation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T08:56:35.330429Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2607.19395"},"observation_digest":"sha256:24aafc59cbf26cca1b7c7767ea6c65d8ca583d3658cd8073e0c580a8803d9631","observation_id":"df8384d3-58dc-4826-b17d-b39bfb9a2bcf","resolution":{"observed_at":"2026-08-02T08:56:35.330429Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.14728","snapshot_observed_at":"2026-08-10T13:41:59.147784Z","title":"arXiv preprint arXiv:2506.14728 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.07169","last_updated":"2026-08-07T12:43:00Z","snapshot_observed_at":"2026-08-11T00:13:09.815827Z","submitted_at":"2026-08-07T12:43:00Z","title":"Agent Memory Distillation: Empowering Small LLM Agents with Hierarchical Teacher Memory","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-10T13:41:59.147784Z"},"links":{"cited_paper":"/paper/2506.14728","citing_paper":"/paper/2608.07169"},"observation_digest":"sha256:59427a644776623d88cd67e5f75e5fcffae4813605efd6b23d302f07c0b147b6","observation_id":"b31989bc-dffa-42da-a2ab-444e87f86a04","resolution":{"observed_at":"2026-08-10T13:41:59.147784Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.14728/citation-record","integrity":"/paper/2506.14728/integrity","json":"/paper/2506.14728/citation-record.json","paper":"/paper/2506.14728"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-07T00:13:34.046574Z","title":"Distilling the knowledge in a neural network.arXiv preprint arXiv:1503.02531, 2015","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:34.046574Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:86e838074f1a3d511a5b4ba0501dfa615a0f50fd727bea3b2dfe8e1314458ade","observation_id":"c47fe6fb-562c-4de0-8aac-0a6a5c27eca8","resolution":{"observed_at":"2026-08-07T00:13:34.046574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.01108","last_updated":"2020-03-01T02:57:50Z","snapshot_observed_at":"2026-08-07T19:07:36.327251Z","submitted_at":"2019-10-02T17:56:28Z","title":"DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.01108","snapshot_observed_at":"2026-08-07T00:13:34.154762Z","title":"Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter.arXiv preprint arXiv:1910.01108, 2019","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:34.154762Z"},"links":{"cited_paper":"/paper/1910.01108","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:49afc7bf422f7619e412214083c4e87cd2c2818259d2de54629cb2074272b73c","observation_id":"eb1e1f3f-01c1-4aff-89d8-618a295b99b4","resolution":{"observed_at":"2026-08-07T00:13:34.154762Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1908.09355","last_updated":"2019-08-25T16:13:24Z","snapshot_observed_at":"2026-08-10T17:57:35.491764Z","submitted_at":"2019-08-25T16:13:24Z","title":"Patient Knowledge Distillation for BERT Model Compression","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.09355","snapshot_observed_at":"2026-08-07T00:13:34.333057Z","title":"Patient knowledge distillation for bert model compression.arXiv preprint arXiv:1908.09355, 2019","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:34.333057Z"},"links":{"cited_paper":"/paper/1908.09355","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:c2b1116af78c18cfb71683e855a0e82a94a31585f9893bbfdb845db5ea40035b","observation_id":"9b38405d-135d-4eb8-af14-40f04c586881","resolution":{"observed_at":"2026-08-07T00:13:34.333057Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1909.10351","last_updated":"2020-10-16T02:12:46Z","snapshot_observed_at":"2026-08-10T14:27:02.964369Z","submitted_at":"2019-09-23T13:05:35Z","title":"TinyBERT: Distilling BERT for Natural Language Understanding","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.10351","snapshot_observed_at":"2026-08-07T00:13:34.496625Z","title":"Tinybert: Distilling bert for natural language understanding.arXiv preprint arXiv:1909.10351, 2019","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:34.496625Z"},"links":{"cited_paper":"/paper/1909.10351","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:53e89ab2e524ac747261b92d381f1338001cd3713a4ce2d44d88454b5a682fac","observation_id":"feab6543-dc02-436a-9418-2ff401b5f011","resolution":{"observed_at":"2026-08-07T00:13:34.496625Z","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":"2026-08-07T00:13:34.647744Z","title":"Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.Advances in neural information processing systems, 33:5776–5788, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:34.647744Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:14bd6c56c967f8a2307b2c01f77048077662198d57b4446456eb1a8a5d706d48","observation_id":"c292c6f2-37e3-4c60-8566-692fb0130774","resolution":{"observed_at":"2026-08-07T00:13:34.647744Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.02984","last_updated":"2020-04-14T23:54:36Z","snapshot_observed_at":"2026-08-06T09:03:09.275283Z","submitted_at":"2020-04-06T20:20:58Z","title":"MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.02984","snapshot_observed_at":"2026-08-07T00:13:34.807151Z","title":"Mobilebert: a compact task-agnostic bert for resource-limited devices.arXiv preprint arXiv:2004.02984, 2020","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:34.807151Z"},"links":{"cited_paper":"/paper/2004.02984","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:15787a9233e3cf273755b466fff80c9c10ea86ac97f7fcd69b6237ca0684408e","observation_id":"83eb7cac-4b89-4da7-b39f-a5780946122b","resolution":{"observed_at":"2026-08-07T00:13:34.807151Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.06629","last_updated":"2023-06-11T09:17:21Z","snapshot_observed_at":"2026-08-10T07:19:34.576664Z","submitted_at":"2023-06-11T09:17:21Z","title":"GKD: A General Knowledge Distillation Framework for Large-scale Pre-trained Language Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.06629","snapshot_observed_at":"2026-08-07T00:13:35.022808Z","title":"Gkd: A general knowledge distillation framework for large-scale pre-trained language model.arXiv preprint arXiv:2306.06629, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:35.022808Z"},"links":{"cited_paper":"/paper/2306.06629","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:435a2b642d381e8d40919d8dd4e8ebbee599e062118577c78e2e2271eca9a53c","observation_id":"4c853567-8e2b-49f7-a6ac-aaeb6d06d783","resolution":{"observed_at":"2026-08-07T00:13:35.022808Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.10071","last_updated":"2023-06-13T10:55:29Z","snapshot_observed_at":"2026-08-10T22:46:11.246410Z","submitted_at":"2022-12-20T08:24:45Z","title":"Large Language Models Are Reasoning Teachers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.10071","snapshot_observed_at":"2026-08-07T00:13:35.227419Z","title":"Large language models are reasoning teachers.arXiv preprint arXiv:2212.10071, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:35.227419Z"},"links":{"cited_paper":"/paper/2212.10071","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:8496f593e6cb9aa5a8bdfbf564e20517f89841b3f5feb3fd5e9f664ef4adff57","observation_id":"a784fce5-b071-4cb1-acd7-c4d772b27063","resolution":{"observed_at":"2026-08-07T00:13:35.227419Z","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":"2026-08-07T00:13:35.387261Z","title":"Distilling reasoning capabilities into smaller language models.Findings of the Association for Computational Linguistics: ACL 2023, pages 7059–7073, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:35.387261Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:aded0dabbb52037932c6cc325d4c521d87423ed891c05fa6cf0b78699bfc5fe3","observation_id":"891b6600-a31c-489a-908d-0e5f9b141caf","resolution":{"observed_at":"2026-08-07T00:13:35.387261Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.14050","last_updated":"2024-04-15T21:58:27Z","snapshot_observed_at":"2026-08-10T11:18:03.963963Z","submitted_at":"2023-06-24T20:15:07Z","title":"Symbolic Chain-of-Thought Distillation: Small Models Can Also \"Think\" Step-by-Step","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.14050","snapshot_observed_at":"2026-08-07T00:13:35.505844Z","title":"Symbolic chain-of- thought distillation: Small models can also\" think\" step-by-step.arXiv preprint arXiv:2306.14050, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:35.505844Z"},"links":{"cited_paper":"/paper/2306.14050","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:98a8cb3a7fe470d3cf4fb0da3ae52340ea7652d1e597ae9d9a72ca45a0d29d58","observation_id":"55fbda0d-6636-4dc9-97e0-9359a8b58afd","resolution":{"observed_at":"2026-08-07T00:13:35.505844Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.06726","last_updated":"2022-10-13T04:50:02Z","snapshot_observed_at":"2026-07-06T14:04:32.971017Z","submitted_at":"2022-10-13T04:50:02Z","title":"Explanations from Large Language Models Make Small Reasoners Better","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.06726","snapshot_observed_at":"2026-08-07T00:13:35.654099Z","title":"Explanations from large language models make small reasoners better.arXiv preprint arXiv:2210.06726, 2022","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:35.654099Z"},"links":{"cited_paper":"/paper/2210.06726","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:8f6996abb3772a504b40d51380734f25fd6344b0d71e38945570eba1dab1974b","observation_id":"0cf34416-9442-4a7d-af8c-865bf438c4a4","resolution":{"observed_at":"2026-08-07T00:13:35.654099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16064","last_updated":"2024-05-25T05:27:38Z","snapshot_observed_at":"2026-08-03T17:12:46.984636Z","submitted_at":"2024-05-25T05:27:38Z","title":"Keypoint-based Progressive Chain-of-Thought Distillation for LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.16064","snapshot_observed_at":"2026-08-07T00:13:35.793826Z","title":"Keypoint-based progressive chain-of-thought distillation for llms.arXiv preprint arXiv:2405.16064, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:35.793826Z"},"links":{"cited_paper":"/paper/2405.16064","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:abe61b4015e636b92c2688a345bfff044040bbcf83b95654562326d20a0de812","observation_id":"58262a93-84e9-4392-ba4e-8089c71c5556","resolution":{"observed_at":"2026-08-07T00:13:35.793826Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.13820","last_updated":"2026-05-27T17:51:12Z","snapshot_observed_at":"2026-08-07T15:42:44.031154Z","submitted_at":"2025-05-20T02:01:55Z","title":"Structured Agent Distillation for Large Language Model","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.13820","snapshot_observed_at":"2026-08-07T00:13:35.958845Z","title":"Structured agent distillation for large language model.arXiv preprint arXiv:2505.13820, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:35.958845Z"},"links":{"cited_paper":"/paper/2505.13820","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:3eea85fa2aa748c659b3e4fbb8b349faaf8150d7bd3e32ba58ce7db08ebb6e5e","observation_id":"2a6b8ecd-3139-48df-9533-36419677a6dd","resolution":{"observed_at":"2026-08-07T00:13:35.958845Z","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":"2026-08-07T00:13:36.114206Z","title":"Distilling llm agent into small models with retrieval and code tools.arXiv preprint arXiv:2505.17612, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:36.114206Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:80b032700dd626f1521537d6478876d8ad93c0bb343bb79d89ffb4bce650a6c4","observation_id":"cb61dce6-e024-4972-b3cd-1253fc7ba4e3","resolution":{"observed_at":"2026-08-07T00:13:36.114206Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01620","last_updated":"2024-06-07T18:13:16Z","snapshot_observed_at":"2026-08-09T21:00:34.616174Z","submitted_at":"2024-02-02T18:35:14Z","title":"MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01620","snapshot_observed_at":"2026-08-07T00:13:36.272245Z","title":"Magdi: Structured distillation of multi-agent interaction graphs improves reasoning in smaller language models.arXiv preprint arXiv:2402.01620, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:36.272245Z"},"links":{"cited_paper":"/paper/2402.01620","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:07b6f33c391af642d23561101f0e796bd8b5be1ba8cb457a298161a006b0665c","observation_id":"d0281c93-37c8-4c9f-a42f-59d15e3596cf","resolution":{"observed_at":"2026-08-07T00:13:36.272245Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.02749","last_updated":"2024-05-04T20:34:06Z","snapshot_observed_at":"2026-08-07T10:09:20.500918Z","submitted_at":"2024-05-04T20:34:06Z","title":"Sub-goal Distillation: A Method to Improve Small Language Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.02749","snapshot_observed_at":"2026-08-07T00:13:36.374303Z","title":"Sub-goal distillation: A method to improve small language agents.arXiv preprint arXiv:2405.02749, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:36.374303Z"},"links":{"cited_paper":"/paper/2405.02749","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:b9e54ccd93086e8e2dd21efb7ca5aa121460420cacbe4e7798b8cd7cfe46a3e4","observation_id":"5bf58615-9a2b-4f50-8897-8d1fa84422d8","resolution":{"observed_at":"2026-08-07T00:13:36.374303Z","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":"2026-08-07T00:13:45.423960Z","title":"Introducing the model context protocol","venue":null,"work_id":"0dd8fc62-3a2b-440c-bccc-b77619389d34","year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:36.527929Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:690897d1cfad3e233725d603b1a8d88ffa1ffcb0f17f95ab2b469002eaa710ef","observation_id":"6a394f9d-bfd7-46fd-9c18-ce08ad94db00","resolution":{"observed_at":"2026-08-07T00:13:45.549466Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.23278","last_updated":"2025-10-07T07:13:32Z","snapshot_observed_at":"2026-07-06T21:00:55.979837Z","submitted_at":"2025-03-30T01:58:22Z","title":"Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.23278","snapshot_observed_at":"2026-08-07T00:13:36.663271Z","title":"Model context protocol (mcp): Landscape, security threats, and future research directions.arXiv preprint arXiv:2503.23278, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:36.663271Z"},"links":{"cited_paper":"/paper/2503.23278","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:0d424eac06ac68a6f3b0c5ea5584772d266a249cae571613ac23c28424c27e92","observation_id":"69ed8d5b-22f9-4e8f-9f48-916b0e16c637","resolution":{"observed_at":"2026-08-07T00:13:36.663271Z","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":"2026-08-07T00:13:36.779013Z","title":"Mcip: Protecting mcp safety via model contextual integrity protocol.arXiv preprint arXiv:2505.14590, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:36.779013Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:f52dbaa67801c7977c14d9a3c71f5835e5da38cf6ed186b586918c4a69a00922","observation_id":"d970619a-9907-43b5-8c64-7531c88fe872","resolution":{"observed_at":"2026-08-07T00:13:36.779013Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.20286","last_updated":"2025-05-26T17:58:53Z","snapshot_observed_at":"2026-08-07T15:21:20.945396Z","submitted_at":"2025-05-26T17:58:53Z","title":"Alita: Generalist Agent Enabling Scalable Agentic Reasoning with Minimal Predefinition and Maximal Self-Evolution","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.20286","snapshot_observed_at":"2026-08-07T00:13:36.922278Z","title":"Alita: Generalist agent enabling scalable agentic reasoning with minimal predefinition and maximal self-evolution.arXiv preprint arXiv:2505.20286, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:36.922278Z"},"links":{"cited_paper":"/paper/2505.20286","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:c068eaf4fd6421dbc6e364591b11c66e4694d7cf66982558d68fa75baa60f589","observation_id":"6eb47a7c-dab2-4f4e-a89a-3a3cf2d421ec","resolution":{"observed_at":"2026-08-07T00:13:36.922278Z","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":"2026-08-07T00:13:45.071406Z","title":"Alpaca: A strong, replicable instruction-following model.Stanford Center for Research on F oundation Models","venue":null,"work_id":"ddb36d85-095f-4e3c-8114-ea3b3ea13a75","year":2023},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:37.077279Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:7b450a3483eb79ebc4d6642397073dbdf1ef34729d46d5e0a2d675543e17714f","observation_id":"d0cc2725-659f-43ed-81af-a7bc4c14db95","resolution":{"observed_at":"2026-08-07T00:13:45.242869Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.02707","last_updated":"2023-06-05T08:58:39Z","snapshot_observed_at":"2026-08-09T03:29:22.849759Z","submitted_at":"2023-06-05T08:58:39Z","title":"Orca: Progressive Learning from Complex Explanation Traces of GPT-4","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.02707","snapshot_observed_at":"2026-08-07T00:13:37.195721Z","title":"Orca: Progressive learning from complex explanation traces of gpt-4.arXiv preprint arXiv:2306.02707, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:37.195721Z"},"links":{"cited_paper":"/paper/2306.02707","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:75f7faf18eebc540eaa9d0ec9ff8d8509e5494684455c9612dd6cedea4cf5492","observation_id":"f6d1fc01-67db-426b-8b1a-e0d5c71247bc","resolution":{"observed_at":"2026-08-07T00:13:37.195721Z","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":"2026-08-07T00:13:44.801420Z","title":"Super- correct: Advancing small llm reasoning with thought template distillation and self-correction","venue":null,"work_id":"8da01fa8-3608-46d8-841f-9ae2c40730ec","year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:37.368467Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:58ae77b7c22be1ba4abc7d34ec3781946f11fcc4f1c72c16d99bd392592fe83c","observation_id":"1bfbdf59-b78a-47f6-8dd4-987c8ea142d5","resolution":{"observed_at":"2026-08-07T00:13:44.914845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.03348","last_updated":"2024-06-09T14:24:54Z","snapshot_observed_at":"2026-08-09T02:13:56.068839Z","submitted_at":"2024-03-05T22:21:45Z","title":"Learning to Maximize Mutual Information for Chain-of-Thought Distillation","version":3},"cited_work":{"arxiv_id":"2403.03348","doi":null,"metadata_source":"pith","pith_arxiv_id":"2403.03348","snapshot_observed_at":"2026-08-07T00:13:42.562561Z","title":"Learning to Maximize Mutual Information for Chain-of-Thought Distillation","venue":"cs.CL","work_id":"006c9cf9-37a1-4f97-9d8e-9ff6ffe78f90","year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:37.512272Z"},"links":{"cited_paper":"/paper/2403.03348","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:efc6ff4bec59a724001164efe43ddafc158c8f18ca116cc1029e51ecff611521","observation_id":"89e91865-13aa-42c3-a132-9c4650471936","resolution":{"observed_at":"2026-08-07T00:13:42.642732Z","resolver_source":"local_arxiv","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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.01879","last_updated":"2023-08-30T21:28:01Z","snapshot_observed_at":"2026-08-06T01:14:28.656007Z","submitted_at":"2023-05-03T03:47:00Z","title":"SCOTT: Self-Consistent Chain-of-Thought Distillation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.01879","snapshot_observed_at":"2026-08-07T00:13:37.673295Z","title":"Scott: Self-consistent chain-of-thought distillation.arXiv preprint arXiv:2305.01879, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:37.673295Z"},"links":{"cited_paper":"/paper/2305.01879","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:27519f430bfc410ec3cbdfa907d4e105025a3c45e0e98032e0ea1961c3474630","observation_id":"af3ce0f4-1eb5-4a29-a41a-b445202ece30","resolution":{"observed_at":"2026-08-07T00:13:37.673295Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.18642","last_updated":"2025-05-24T11:04:52Z","snapshot_observed_at":"2026-08-10T10:44:49.845729Z","submitted_at":"2025-05-24T11:04:52Z","title":"Skip-Thinking: Chunk-wise Chain-of-Thought Distillation Enable Smaller Language Models to Reason Better and Faster","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.18642","snapshot_observed_at":"2026-08-07T00:13:37.810334Z","title":"Skip-thinking: Chunk-wise chain-of-thought distillation enable smaller language models to reason better and faster.arXiv preprint arXiv:2505.18642, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:37.810334Z"},"links":{"cited_paper":"/paper/2505.18642","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:aff605c80bfb03d4ecfc8a0b14de264b1cf8a8c9f98770b8740eb493e4fc0e68","observation_id":"d0a7bef4-9d7f-4a31-ae40-eb5e419f8910","resolution":{"observed_at":"2026-08-07T00:13:37.810334Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06772","last_updated":"2025-03-11T02:46:19Z","snapshot_observed_at":"2026-08-09T17:57:00.989532Z","submitted_at":"2025-02-10T18:51:47Z","title":"ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.06772","snapshot_observed_at":"2026-08-07T00:13:37.937008Z","title":"Reasonflux: Hierarchical llm reasoning via scaling thought templates.arXiv preprint arXiv:2502.06772, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:37.937008Z"},"links":{"cited_paper":"/paper/2502.06772","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:f0edce7d6d241ffc9431d0068ff35502e0289a9e7999d09cb1b58766348a5cdb","observation_id":"9ac12107-4011-4a08-a43f-6fcdd513b5e9","resolution":{"observed_at":"2026-08-07T00:13:37.937008Z","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":"2026-08-07T00:13:44.581094Z","title":"Unicott: A unified framework for structural chain-of-thought distillation","venue":null,"work_id":"bdaed9d2-52c3-4cba-a862-41957a60d567","year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:38.056446Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:80defda37d8da32725bc16314985a82832f9284a0ae667982f20a03316687ca6","observation_id":"f10de3b3-cf47-4236-865f-1219861123a4","resolution":{"observed_at":"2026-08-07T00:13:44.641417Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.10534","last_updated":"2023-06-05T19:16:25Z","snapshot_observed_at":"2026-08-07T23:10:09.561610Z","submitted_at":"2022-12-20T18:46:08Z","title":"DISCO: Distilling Counterfactuals with Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.10534","snapshot_observed_at":"2026-08-07T00:13:38.229405Z","title":"Disco: Distilling counterfactuals with large language models.arXiv preprint arXiv:2212.10534, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:38.229405Z"},"links":{"cited_paper":"/paper/2212.10534","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:444c9bde4f72ff5a29f381ca5c0ff790352dfc11764ab7f58ad9ca12dc8152b0","observation_id":"e1e73f3d-37d2-4fc7-a746-3bdba3fb80a5","resolution":{"observed_at":"2026-08-07T00:13:38.229405Z","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":"2026-08-07T00:13:44.452923Z","title":"Specializing smaller language models towards multi-step reasoning","venue":null,"work_id":"3036411e-e511-4c2a-91d5-dc7868e44eb4","year":2023},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:38.366203Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:aee13e5f95af0a7628805b0c2dcc58183612eced4e28eaccf17346f5cf9e7dfd","observation_id":"c09af58c-2728-42d0-87b9-1f6df2bcf652","resolution":{"observed_at":"2026-08-07T00:13:44.496702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.15189","last_updated":"2022-09-30T02:30:15Z","snapshot_observed_at":"2026-08-04T09:41:45.042008Z","submitted_at":"2022-09-30T02:30:15Z","title":"Learning by Distilling Context","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.15189","snapshot_observed_at":"2026-08-07T00:13:38.518193Z","title":"Learning by distilling context.arXiv preprint arXiv:2209.15189, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:38.518193Z"},"links":{"cited_paper":"/paper/2209.15189","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:87098ad16225bbb5baf28dd092af8090eac8f4d1191216d992c1c9f4fb9fc5fc","observation_id":"fda6bd76-14b3-4ca1-ba50-712198c84b62","resolution":{"observed_at":"2026-08-07T00:13:38.518193Z","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":"2026-08-07T00:13:38.694864Z","title":"Efficient llm context distillation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:38.694864Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:f2f7d10fad411d9e0bf8e83455ee93e6b6cf8a595649590bb5d13ae2821d4118","observation_id":"f324b8e3-faf4-4f7c-b7ae-0e6e587678e9","resolution":{"observed_at":"2026-08-07T00:13:38.694864Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.10670","last_updated":"2022-12-20T22:11:35Z","snapshot_observed_at":"2026-08-10T02:12:11.712418Z","submitted_at":"2022-12-20T22:11:35Z","title":"In-context Learning Distillation: Transferring Few-shot Learning Ability of Pre-trained Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.10670","snapshot_observed_at":"2026-08-07T00:13:38.817872Z","title":"In-context learning distillation: Transferring few-shot learning ability of pre-trained language models.arXiv preprint arXiv:2212.10670, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:38.817872Z"},"links":{"cited_paper":"/paper/2212.10670","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:65283954802d88a79332d50ea6dd8a7d8bbccdf98c3d511d6b6073b0a15f74e0","observation_id":"c18673d4-5a6e-4120-8364-9706559b0ca6","resolution":{"observed_at":"2026-08-07T00:13:38.817872Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.13243","last_updated":"2024-12-17T18:49:21Z","snapshot_observed_at":"2026-07-06T20:08:48.064792Z","submitted_at":"2024-12-17T18:49:21Z","title":"In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.13243","snapshot_observed_at":"2026-08-07T00:13:38.924089Z","title":"In-context learning distillation for efficient few-shot fine-tuning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:38.924089Z"},"links":{"cited_paper":"/paper/2412.13243","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:39d51a8c4f17bbf200c7594cacd2d57594925db88a05119c3011bacd0c38a37c","observation_id":"830b141c-608c-4e24-b460-41728c4a8649","resolution":{"observed_at":"2026-08-07T00:13:38.924089Z","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":"2026-08-07T00:13:44.288592Z","title":"Knowledge distilla- tion from language-oriented to emergent communication for multi-agent remote control","venue":null,"work_id":"cbdebb02-9de4-4831-b115-52b6c2a8aaef","year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:39.005529Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:eb94297799e11de25ebfde042e4f10826a64ef18a56c5d4d818c4a0eba1a9e97","observation_id":"aaca27e1-db15-48de-b5f3-26108e673bf0","resolution":{"observed_at":"2026-08-07T00:13:44.353460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.11499","last_updated":"2024-12-16T07:18:02Z","snapshot_observed_at":"2026-07-06T20:07:32.814148Z","submitted_at":"2024-12-16T07:18:02Z","title":"Embodied CoT Distillation From LLM To Off-the-shelf Agents","version":1},"cited_work":{"arxiv_id":"2412.11499","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.11499","snapshot_observed_at":"2026-08-07T00:13:41.751345Z","title":"Embodied CoT Distillation From LLM To Off-the-shelf Agents","venue":"cs.AI","work_id":"63d931fc-0b46-45ce-a2d5-6d3d7e4c90ea","year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:39.118642Z"},"links":{"cited_paper":"/paper/2412.11499","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:f038d7a15789915000100425754467619706c8f41355ec80932a0e2b5351417b","observation_id":"0feecf44-495e-4e64-8733-1c715c94da7d","resolution":{"observed_at":"2026-08-07T00:13:41.854064Z","resolver_source":"local_arxiv","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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.23885","last_updated":"2025-06-11T01:42:53Z","snapshot_observed_at":"2026-08-07T22:31:50.319614Z","submitted_at":"2025-05-29T17:51:58Z","title":"OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.23885","snapshot_observed_at":"2026-08-07T00:13:39.194980Z","title":"Owl: Optimized workforce learning for general multi-agent assistance in real-world task automation.arXiv preprint arXiv:2505.23885, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:39.194980Z"},"links":{"cited_paper":"/paper/2505.23885","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:c62da14bc548dbc27bb21c7c8c33c2a99222cadbd0d9d66edaa82bb5fdb718e7","observation_id":"2f2376da-c7ce-4ee9-97d7-a0d8e0782a53","resolution":{"observed_at":"2026-08-07T00:13:39.194980Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.17288","last_updated":"2024-04-29T18:38:26Z","snapshot_observed_at":"2026-07-06T16:25:34.527871Z","submitted_at":"2023-09-29T14:46:30Z","title":"AutoAgents: A Framework for Automatic Agent Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.17288","snapshot_observed_at":"2026-08-07T00:13:39.304616Z","title":"Autoagents: A framework for automatic agent generation.arXiv preprint arXiv:2309.17288, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:39.304616Z"},"links":{"cited_paper":"/paper/2309.17288","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:405cba9e19d770e76ce091ada8617fee442f5fabe3408c93e285cd75699c77c2","observation_id":"54b2e3f0-b546-462f-8b93-9931aa217ecc","resolution":{"observed_at":"2026-08-07T00:13:39.304616Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.15665","last_updated":"2025-05-11T07:56:18Z","snapshot_observed_at":"2026-07-06T19:36:49.949466Z","submitted_at":"2024-10-21T06:09:30Z","title":"Long Term Memory: The Foundation of AI Self-Evolution","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.15665","snapshot_observed_at":"2026-08-07T00:13:39.441986Z","title":"Long term memory: The foundation of ai self-evolution.arXiv preprint arXiv:2410.15665, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:39.441986Z"},"links":{"cited_paper":"/paper/2410.15665","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:904f39e5f6d5bb7c16b545b897912bcc413e3e0dd5974007a4a4fa67cca33300","observation_id":"777652d0-e7e8-4b7b-8870-5e34b4bd4c97","resolution":{"observed_at":"2026-08-07T00:13:39.441986Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14767","last_updated":"2024-05-27T12:43:42Z","snapshot_observed_at":"2026-07-06T18:18:47.640933Z","submitted_at":"2024-05-23T16:35:20Z","title":"FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14767","snapshot_observed_at":"2026-08-07T00:13:39.565126Z","title":"Finrobot: an open-source ai agent platform for financial applications using large language models.arXiv preprint arXiv:2405.14767, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:39.565126Z"},"links":{"cited_paper":"/paper/2405.14767","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:252933da505d2a263d630801d7c552a46dfc640d2cd00c8eb77d57e3e2d6d7bc","observation_id":"c9ca9bc0-a5c2-4787-b710-06d16fc3bc0e","resolution":{"observed_at":"2026-08-07T00:13:39.565126Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.06590","last_updated":"2025-01-11T17:10:30Z","snapshot_observed_at":"2026-08-10T20:54:48.881388Z","submitted_at":"2025-01-11T17:10:30Z","title":"ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.06590","snapshot_observed_at":"2026-08-07T00:13:39.683134Z","title":"Chemagent: Self-updating library in large language models improves chemical reasoning.arXiv preprint arXiv:2501.06590, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:39.683134Z"},"links":{"cited_paper":"/paper/2501.06590","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:fde6f5369eef472d8563b42c8e5b2f0ad5201bce567fa51b633c7f8b072766d4","observation_id":"a135c201-56fb-4233-a629-916e364d4a5a","resolution":{"observed_at":"2026-08-07T00:13:39.683134Z","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":"2026-08-07T00:13:44.138432Z","title":"Clinicalagent: Clinical trial multi-agent system with large language model-based reasoning","venue":null,"work_id":"f8a6b8cc-eceb-4c21-93ef-cb2dd9e99210","year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:39.806565Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:aa36f6400e8c66cbc4834dd2ac021daf944128e2d47428ec1e0049bb4e01cfc7","observation_id":"0ca0d60a-1d3a-4bef-838f-615c1377aca1","resolution":{"observed_at":"2026-08-07T00:13:44.215254Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.13010","last_updated":"2024-05-24T11:47:24Z","snapshot_observed_at":"2026-07-06T17:05:56.282078Z","submitted_at":"2023-12-20T13:22:41Z","title":"AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.13010","snapshot_observed_at":"2026-08-07T00:13:39.962963Z","title":"Agentcoder: Multi-agent- based code generation with iterative testing and optimisation.arXiv preprint arXiv:2312.13010, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:39.962963Z"},"links":{"cited_paper":"/paper/2312.13010","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:257352567c67ac5cf27a0a7c5084747be91b5c89866b10af87106ebcd9387e77","observation_id":"379f2157-a833-4a53-b1f7-e6f8344d5614","resolution":{"observed_at":"2026-08-07T00:13:39.962963Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10022","last_updated":"2024-07-13T22:46:02Z","snapshot_observed_at":"2026-08-07T08:30:02.165133Z","submitted_at":"2024-07-13T22:46:02Z","title":"AtomAgents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligence","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10022","snapshot_observed_at":"2026-08-07T00:13:40.022859Z","title":"Atomagents: Alloy design and discovery through physics-aware multi-modal multi-agent artificial intelligence.arXiv preprint arXiv:2407.10022, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:40.022859Z"},"links":{"cited_paper":"/paper/2407.10022","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:ba3aa98a96ba0a1641f7695d7a6099184ab7ed9edc27c3d5453fc80ec9e9cd38","observation_id":"06fd1412-fd8d-4364-b439-17b41e1021f9","resolution":{"observed_at":"2026-08-07T00:13:40.022859Z","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":"2026-08-07T00:13:43.973214Z","title":"Protagents: protein discovery via large language model multi-agent collaborations combining physics and machine learning.Digital Discovery, 3(7):1389–1409, 2024","venue":null,"work_id":"5540385d-1d0a-48aa-9624-6ef87fad4009","year":2024},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:40.123751Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:c15fbc1c05d38058f4f04d9055b66b91947038f03580bff8623ada3782057643","observation_id":"3689c510-3d1f-456a-8e76-75e86693e517","resolution":{"observed_at":"2026-08-07T00:13:44.041533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.20246","last_updated":"2025-06-19T15:42:45Z","snapshot_observed_at":"2026-08-09T21:27:49.188739Z","submitted_at":"2025-05-26T17:22:20Z","title":"On Path to Multimodal Historical Reasoning: HistBench and HistAgent","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.20246","snapshot_observed_at":"2026-08-07T00:13:40.295752Z","title":"On path to multimodal historical reasoning: Histbench and histagent.arXiv preprint arXiv:2505.20246, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:40.295752Z"},"links":{"cited_paper":"/paper/2505.20246","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:f289a63332d872f88e46d6cb73dd33b6725f03451bb253027942329a9bad0290","observation_id":"c15b03d3-e3b3-4b99-8f34-2ddb2d552fd8","resolution":{"observed_at":"2026-08-07T00:13:40.295752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.09689","last_updated":"2025-04-29T22:29:52Z","snapshot_observed_at":"2026-08-07T16:06:06.954752Z","submitted_at":"2025-04-13T18:47:22Z","title":"EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safety","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.09689","snapshot_observed_at":"2026-08-07T00:13:40.412249Z","title":"Emoagent: Assessing and safeguarding human-ai interaction for mental health safety.arXiv preprint arXiv:2504.09689, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:40.412249Z"},"links":{"cited_paper":"/paper/2504.09689","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:8297a0dc617533768aba5651e6b4e6574c1d7dc02dfbea8e3e800d0a372c29d3","observation_id":"35496410-0001-437a-a02b-6d0b998ee4c6","resolution":{"observed_at":"2026-08-07T00:13:40.412249Z","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":"2026-08-07T00:13:40.562225Z","title":"‘smo- lagents‘: a smol library to build great agentic systems","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:40.562225Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:c905dbdd90b548bdbfd1172a246cdda6b8afc10328ffab2c3648ace6abea691f","observation_id":"5965c5b2-182f-4eef-935a-caf105837165","resolution":{"observed_at":"2026-08-07T00:13:40.562225Z","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":"2026-08-07T00:13:43.809775Z","title":"Math twenty four (24 -game) dataset","venue":null,"work_id":"af6f5e67-47fc-4cdf-8ca8-c8d2a375d3d6","year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:40.711362Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:2bb0901e66b051be47361982fcda570dc91d06baa9492e342a2b87d72585dc51","observation_id":"7e3f7701-4150-4c28-9cef-c3607b890e87","resolution":{"observed_at":"2026-08-07T00:13:43.859421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.10286","last_updated":"2020-03-07T17:55:41Z","snapshot_observed_at":"2026-07-06T09:06:42.071993Z","submitted_at":"2020-03-07T17:55:41Z","title":"PathVQA: 30000+ Questions for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.10286","snapshot_observed_at":"2026-08-07T00:13:40.882095Z","title":"Pathvqa: 30000+ questions for medical visual question answering.arXiv preprint arXiv:2003.10286, 2020","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:40.882095Z"},"links":{"cited_paper":"/paper/2003.10286","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:86f4c2d900b097c46f732d194af893116e94da04a764ec1717d1838c136bbc2b","observation_id":"c5ba3a17-d132-48a4-99f3-47af384cb57b","resolution":{"observed_at":"2026-08-07T00:13:40.882095Z","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":"2026-08-07T00:13:40.970589Z","title":"Slake: A semantically-labeled knowledge- enhanced dataset for medical visual question answering","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:40.970589Z"},"links":{"citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:727c8c38546ebeefd15539397ddd65683ff16f0198677fa77bcb25fe6df7ee0e","observation_id":"21544595-8612-403b-aabd-5a6a2a78b03e","resolution":{"observed_at":"2026-08-07T00:13:40.970589Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11271","last_updated":"2026-04-13T23:08:01Z","snapshot_observed_at":"2026-08-03T02:43:16.180683Z","submitted_at":"2025-02-16T21:18:47Z","title":"OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11271","snapshot_observed_at":"2026-08-07T00:13:41.081140Z","title":"Octotools: An agentic framework with extensible tools for complex reasoning.arXiv preprint arXiv:2502.11271, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T00:13:41.081140Z"},"links":{"cited_paper":"/paper/2502.11271","citing_paper":"/paper/2506.14728"},"observation_digest":"sha256:5d169e017c616bfcd55edf61a7d15bba117d611663eea2136e18221b90903389","observation_id":"18732e9a-a776-4c55-a718-0992234bcca4","resolution":{"observed_at":"2026-08-07T00:13:41.081140Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.14728","last_updated":"2025-06-17T17:08:32Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-07T14:16:24.457276Z","submitted_at":"2025-06-17T17:08:32Z","title":"AgentDistill: Training-Free Agent Distillation with Generalizable MCP Boxes"},"reference_resolution":{"displayed":52,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":41,"verified_exact":2,"verified_fuzzy":9},"total_outbound_references":52},"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 11 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 13 inbound Pith citation observations for arXiv:2506.14728."}