{"as_of":"2026-08-10T12:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:137cef321245f058e657e9b43e6c376dc437b021fd4bd6328173630d4b5545a6","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:53:39.287913Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-07T13:53:39.287913Z","title":"Preprint, arXiv:2410.02052","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20660","last_updated":"2025-05-27T03:09:06Z","snapshot_observed_at":"2026-08-09T14:28:44.499196Z","submitted_at":"2025-05-27T03:09:06Z","title":"BacktrackAgent: Enhancing GUI Agent with Error Detection and Backtracking Mechanism","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:53:39.287913Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2505.20660"},"observation_digest":"sha256:d4747a5dc2707feed44a88c1359bb19bd62d43ef3b92b24627f4ee1fccb6a596","observation_id":"5ad50331-6544-4eba-a402-6834e9913981","resolution":{"observed_at":"2026-08-07T13:53:39.287913Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-07T13:32:47.661243Z","title":"Exact: Teaching ai agents to explore with reflective-mcts and exploratory learning.arXiv preprint arXiv:2410.02052, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.21499","last_updated":"2025-05-27T17:59:05Z","snapshot_observed_at":"2026-08-07T13:24:27.400642Z","submitted_at":"2025-05-27T17:59:05Z","title":"AdInject: Real-World Black-Box Attacks on Web Agents via Advertising Delivery","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T13:32:47.661243Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2505.21499"},"observation_digest":"sha256:9a40629605b96f8df2e613247a5e4a162a097f2a391819ad57e8453807c8e377","observation_id":"8259e65d-1d8b-4d59-bd4e-360872caf8b8","resolution":{"observed_at":"2026-08-07T13:32:47.661243Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-07T10:28:42.798474Z","title":"Exact: Teaching ai agents to explore with reflective-mcts and exploratory learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.05213","last_updated":"2025-06-05T16:27:49Z","snapshot_observed_at":"2026-08-08T16:04:48.106610Z","submitted_at":"2025-06-05T16:27:49Z","title":"LLM-First Search: Self-Guided Exploration of the Solution Space","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T10:28:42.798474Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2506.05213"},"observation_digest":"sha256:9f8fa93fc38e2b029ac75d71a27d2ec59af019178064abcad1e53e8aee720b68","observation_id":"6642296e-aac2-4649-bc11-e0baa96ce5c7","resolution":{"observed_at":"2026-08-07T10:28:42.798474Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-07T05:27:50.242692Z","title":"Exact: Teachingaiagentstoexplorewithreflective-mctsandexploratorylearning.ArXiv, abs/2410.02052,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.07976","last_updated":"2025-06-10T12:50:18Z","snapshot_observed_at":"2026-08-07T20:50:35.036523Z","submitted_at":"2025-06-09T17:50:02Z","title":"Thinking vs. Doing: Agents that Reason by Scaling Test-Time Interaction","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:50.242692Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2506.07976"},"observation_digest":"sha256:740fb82fcb306ecb6f8ec7e66469baf11c725f8ee0270ddc73dea0c69e01b191","observation_id":"851db09b-90e5-403f-b4e4-5bf910310f59","resolution":{"observed_at":"2026-08-07T05:27:50.242692Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-06T20:18:15.711419Z","title":"Exact: Teaching ai agents to explore with reflective-mcts and exploratory learning, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.03327","last_updated":"2025-07-04T06:23:06Z","snapshot_observed_at":"2026-08-07T11:24:12.298323Z","submitted_at":"2025-07-04T06:23:06Z","title":"Read Quietly, Think Aloud: Decoupling Comprehension and Reasoning in LLMs","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T20:18:15.711419Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2507.03327"},"observation_digest":"sha256:072c9f48b6ad8d3256d13acb80c079c1d09681a7b33a4c282b6e73156a52a32e","observation_id":"d0cc6e5c-f391-486f-8671-1b93e15810d9","resolution":{"observed_at":"2026-08-06T20:18:15.711419Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-06T16:12:51.405901Z","title":"Exact: Teaching AI agents to explore with reflective-mcts and exploratory learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14293","last_updated":"2025-07-18T18:06:27Z","snapshot_observed_at":"2026-08-06T15:57:20.673152Z","submitted_at":"2025-07-18T18:06:27Z","title":"WebGuard: Building a Generalizable Guardrail for Web Agents","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T16:12:51.405901Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2507.14293"},"observation_digest":"sha256:a758c71a60d8ce29535c76efa88295c14a79a98852c6550985c3d3ba28ed79aa","observation_id":"434daac8-3b2d-44cc-90b4-ef956887eeee","resolution":{"observed_at":"2026-08-06T16:12:51.405901Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":"2410.02052","doi":"10.48550/arxiv.2410.02052","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://doi.org/10.48550/arXiv.2410.02052","venue":"arXiv (Cornell University)","work_id":"d3b3bb3b-7600-447d-9ca6-3410f73f8085","year":2024},"citing_paper":{"arxiv_id":"2601.22149","last_updated":"2026-04-17T18:27:53Z","snapshot_observed_at":"2026-08-03T05:49:10.484175Z","submitted_at":"2026-01-29T18:59:07Z","title":"DynaWeb: Model-Based Reinforcement Learning of Web Agents","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-16T09:33:30.444057Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2601.22149"},"observation_digest":"sha256:fbdfbbc10b422fe061c04cac35b3079fe4c006ca0c73e808da1f00e1a210c2bd","observation_id":"b328ce80-862c-4359-9441-dda5420da59d","resolution":{"observed_at":"2026-05-16T09:37:41.525346Z","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":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":"2410.02052","doi":"10.48550/arxiv.2410.02052","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://doi.org/10.48550/arXiv.2410.02052","venue":"arXiv (Cornell University)","work_id":"d3b3bb3b-7600-447d-9ca6-3410f73f8085","year":2024},"citing_paper":{"arxiv_id":"2602.15353","last_updated":"2026-07-28T05:57:03Z","snapshot_observed_at":"2026-08-02T22:56:56.297957Z","submitted_at":"2026-02-17T04:47:29Z","title":"NeuroSymActive: Differentiable Neural-Symbolic Reasoning with Active Exploration for Knowledge Graph Question Answering","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-15T22:09:30.370382Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2602.15353"},"observation_digest":"sha256:a2409637451018d966a51e8245d0d7a0aa233d358d33b5890ab84f4346d40036","observation_id":"aaafc7a5-4901-4ec2-9cfa-8384fd0545d7","resolution":{"observed_at":"2026-05-15T22:10:21.489868Z","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":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-02T22:57:01.410852Z","title":"Exact: Teaching ai agents to explore with reflective-mcts and exploratory learning.arXiv preprint arXiv:2410.02052, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.15353","last_updated":"2026-07-28T05:57:03Z","snapshot_observed_at":"2026-08-02T22:56:56.297957Z","submitted_at":"2026-02-17T04:47:29Z","title":"NeuroSymActive: Differentiable Neural-Symbolic Reasoning with Active Exploration for Knowledge Graph Question Answering","version":4},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-02T22:57:01.410852Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2602.15353"},"observation_digest":"sha256:3440e2979b6ead5c1f0f92a35205a85317e651c65e4a0dbfd77c60286813f902","observation_id":"2689092c-8f3f-4fc9-89c3-711016301144","resolution":{"observed_at":"2026-08-02T22:57:01.410852Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.02052","last_updated":"2025-02-27T20:13:19Z","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning","version":5},"cited_work":{"arxiv_id":"2410.02052","doi":"10.48550/arxiv.2410.02052","metadata_source":"arxiv_reference","pith_arxiv_id":"2410.02052","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://doi.org/10.48550/arXiv.2410.02052","venue":"arXiv (Cornell University)","work_id":"d3b3bb3b-7600-447d-9ca6-3410f73f8085","year":2024},"citing_paper":{"arxiv_id":"2604.17180","last_updated":"2026-04-19T00:47:24Z","snapshot_observed_at":"2026-08-03T03:46:10.762878Z","submitted_at":"2026-04-19T00:47:24Z","title":"BranchBench: Aligning Database Branching with Agentic Demands","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-10T06:12:46.899179Z"},"links":{"cited_paper":"/paper/2410.02052","citing_paper":"/paper/2604.17180"},"observation_digest":"sha256:f2fa5c345dec28b8577571e1c8f0b7bc9fc5581221fed057864e6800afe7a776","observation_id":"34c2382a-11c0-4cf4-aadf-e349f1fc95a3","resolution":{"observed_at":"2026-05-10T06:31:31.286110Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2410.02052/citation-record","integrity":"/paper/2410.02052/integrity","json":"/paper/2410.02052/citation-record.json","paper":"/paper/2410.02052"},"outbound":[],"paper":{"arxiv_id":"2410.02052","last_updated":"2025-02-27T20:13:19Z","latest_version":5,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T14:28:14.551525Z","submitted_at":"2024-10-02T21:42:35Z","title":"ExACT: Teaching AI Agents to Explore with Reflective-MCTS and Exploratory Learning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2410.02052."}