{"as_of":"2026-08-04T19:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ab9e4821b3741510a45f9b8d78ea2c29962fbe113e735a77e424bca7690cb79c","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-11T01:18:35.684352Z","state":"measured"},{"denominator":45,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":45,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-30T11:04:02.181424Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.06903","snapshot_observed_at":"2026-07-30T11:04:02.181424Z","title":"Paetzold , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27183","last_updated":"2026-07-29T17:53:01Z","snapshot_observed_at":"2026-08-02T23:25:15.665223Z","submitted_at":"2026-07-29T17:53:01Z","title":"Pangram 4 Technical Report","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-07-30T11:04:02.181424Z"},"links":{"cited_paper":"/paper/2605.06903","citing_paper":"/paper/2607.27183"},"observation_digest":"sha256:a997f606e56ad8b02d9d0e81cfbd11e5e20666e61fb3a751e54b40b1ac7b3166","observation_id":"43887a0b-e4f4-4aad-964a-b96a4f2d5fa9","resolution":{"observed_at":"2026-07-30T11:04:02.181424Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2605.06903/citation-record","integrity":"/paper/2605.06903/integrity","json":"/paper/2605.06903/citation-record.json","paper":"/paper/2605.06903"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2602.13042","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-03T17:18:44.331236Z","title":"arXiv preprint arXiv:2602.13042 , year=","venue":null,"work_id":"aa1b69cf-0b54-4ddb-8d30-c40097425786","year":2026},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:cdbbbd37960162a930cb2309022b750a24d6b5791fbd9e95679ec357b0d54c32","observation_id":"044dd01a-6b32-4cdf-87fb-b2cd5f7e999b","resolution":{"observed_at":"2026-05-11T04:30:57.375391Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Qwen 3.6 Plus","venue":null,"work_id":"8ae85285-5519-4d90-a8c0-1667f95c7fa6","year":2026},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:cf5b2aa575dd8db7586749e93ee273a60731ee1f8b2656fc7265d8c9feedb6c5","observation_id":"c4e8d8d8-c67c-46fb-be1b-cea36b143d3d","resolution":{"observed_at":"2026-05-14T16:57:29.529268Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Claude Haiku 4.5","venue":null,"work_id":"3e4a2671-8946-438d-be64-8739d82f7212","year":2025},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:af86990942ca10dc8d004b9f9bfa329afac7f97bf4c70833cec6f1e4a825f159","observation_id":"4d9095e7-7138-4c91-92cd-a5168282bf38","resolution":{"observed_at":"2026-05-14T16:57:29.523299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Fast-DetectGPT: Efficient zero-shot detection of machine-generated text via conditional probability curvature","venue":null,"work_id":"dbf32a6d-6af9-4b37-bf39-69f735cc3d8a","year":2024},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:bff46748e9b1ed0f9c9077aa7f248e7e047e80ffc131d326e9e9334d761a17b0","observation_id":"57cb8868-b464-418a-b410-2baa4d7485bd","resolution":{"observed_at":"2026-05-14T16:57:29.520222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2509.18880","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Diversity boosts AI-generated text detection","venue":null,"work_id":"9c5d2fad-7fdf-43da-8b8d-75f17362257a","year":2025},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:26c93b06c199e39e405e62f62c70cb26ac2465ce17cfb594352ffd820af4878e","observation_id":"7d3b6b9e-ed3f-4400-8d88-f972a97d0448","resolution":{"observed_at":"2026-05-11T04:30:57.363276Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning to rank using gradient descent","venue":null,"work_id":"788a7b07-7122-4b90-9926-86cc77744c81","year":2005},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:352fe022b8458fa53a4624388a11c6e91636bfa49dbb9061f9fcd34c5db0f5d8","observation_id":"2fa3cb9b-bb87-4b62-9cb9-1171dd9868e9","resolution":{"observed_at":"2026-05-14T16:57:29.508244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"RepreGuard: Detecting LLM-generated text by revealing hidden representation patterns.Transactions of the Association for Computational Linguistics, 13:1812–1831","venue":null,"work_id":"a9f4bef0-267f-4c1e-ac6f-b690865f1fc4","year":2025},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:d69ef9ae24184935bd487a0a7b05e7d3917653a64b29661dcc152759aba03358","observation_id":"9cce0565-72c5-439d-8358-fcfd165057d3","resolution":{"observed_at":"2026-05-14T16:57:29.393384Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Machine-generated text detection prevents language model collapse","venue":null,"work_id":"3a8bf5d7-63f4-41c4-9a40-767445007123","year":2025},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:d0e95d983911c1c657bf81fcf72d7135623d54d4a967bbe4162d43b32022f744","observation_id":"c7f419ec-76ea-4e08-a243-e6b6158cedb1","resolution":{"observed_at":"2026-05-14T16:57:29.424516Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"RAID: A shared benchmark for robust evaluation of machine-generated text detectors","venue":null,"work_id":"fc95847a-1750-4f8b-906d-84835f00bdf4","year":2024},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:34ab47065157f5f60d7fc24f8a9a0b2f09b40b7235b1a877251cc47c386de9f4","observation_id":"a2b3ae23-acec-4642-a7b7-3ca61cdf5f1d","resolution":{"observed_at":"2026-05-14T16:57:29.383879Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"GLTR: Statistical detection and visualization of generated text","venue":null,"work_id":"acaaf5b7-20ac-4d06-8805-2b428806d26a","year":2019},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:4a6f94da5075e54598ac6d2a1e021f164570a5399563b6be83cdfd5342937eaf","observation_id":"73e219a1-d31e-43f0-874d-e17cbcb75717","resolution":{"observed_at":"2026-05-14T16:57:29.498206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Gemini 3 Flash","venue":null,"work_id":"6bf5aebb-7565-4ba4-a0fb-73b4236f7f92","year":2025},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:2144ecd724290f992e533c3a48d6ea63b75a25cd35abf3236ca2bbd0abec410b","observation_id":"29eb9702-b103-4dcd-8d49-df0e48e5a2e8","resolution":{"observed_at":"2026-05-14T16:57:29.505029Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.07597","last_updated":"2023-01-18T15:23:25Z","snapshot_observed_at":"2026-08-03T05:43:17.235179Z","submitted_at":"2023-01-18T15:23:25Z","title":"How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection","version":1},"cited_work":{"arxiv_id":"2301.07597","doi":"10.48550/arxiv.2301.07597","metadata_source":"pith","pith_arxiv_id":"2301.07597","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"How close is chatgpt to human experts? comparison corpus, evaluation, and detection","venue":"cs.CL","work_id":"3f328a6b-2c17-4f7d-bfeb-c1237c3ed241","year":2023},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"cited_paper":"/paper/2301.07597","citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:64929e81de3cfff527f64f73cb1b949e90780cea03128889eb370cdd3b1f5163","observation_id":"29c4a5f2-c5d8-4192-bdae-6af6a8b5185d","resolution":{"observed_at":"2026-05-11T04:30:57.334104Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"DeTeCtive: detecting AI-generated text via multi-level contrastive learning","venue":null,"work_id":"190c7fc0-20d5-4c9a-8b4b-3efd15f85b5e","year":2024},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:8e7988ce53d5159ce10a0e79f7a81f5276f1ff84f450d2d5518a84d751ea9347","observation_id":"6a425a8b-03f4-45ef-a8bd-d20a337282ae","resolution":{"observed_at":"2026-05-14T16:57:29.411563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Spotting LLMs with binoculars: zero-shot detection of machine-generated text","venue":null,"work_id":"0858391b-f3f1-48da-81cd-14d8113ed71d","year":2024},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:142f4a47a260b58406949d9a9ad34b5e0f71392c194131c06c4ac7a966edbf42","observation_id":"d74aee32-a573-47e1-b1f6-27dcf7fa925d","resolution":{"observed_at":"2026-05-14T16:57:29.511205Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1703.07737","last_updated":"2017-11-21T15:35:07Z","snapshot_observed_at":"2026-08-04T09:19:45.912586Z","submitted_at":"2017-03-22T16:34:29Z","title":"In Defense of the Triplet Loss for Person Re-Identification","version":4},"cited_work":{"arxiv_id":"1703.07737","doi":null,"metadata_source":"pith","pith_arxiv_id":"1703.07737","snapshot_observed_at":"2026-07-04T14:39:57.480607Z","title":"In Defense of the Triplet Loss for Person Re-Identification","venue":"cs.CV","work_id":"a72dd8f5-38f0-4656-b761-3af761bac9ef","year":2017},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"cited_paper":"/paper/1703.07737","citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:8dc168df25789e0ed0ad0c6a7d5d590a753cc7886cd777b0b2a4ede1fcfab3a3","observation_id":"a6a24425-dfaa-4db4-ab77-82a97e715bad","resolution":{"observed_at":"2026-05-11T04:30:57.354057Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"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":"1503.02531","doi":"10.1109/cvpr52733.2024.01515","metadata_source":"pith","pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Distilling the Knowledge in a Neural Network","venue":"stat.ML","work_id":"d927ab1f-17b8-4002-9d09-c3d55764fbad","year":2015},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:2b5045862b4d38a28391eecb265cef90e6108d4a6954f659dcd6bfe66c493bde","observation_id":"6ddbe502-cf84-4dd0-8167-ee81ec1966cf","resolution":{"observed_at":"2026-05-11T04:30:57.298903Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"RADAR: robust AI-text detection via adversarial learning","venue":null,"work_id":"97b65caa-22a9-45eb-a526-b2d4a7d1cc21","year":2023},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:321cbc2ce77007f4a8aed8c3e11cc0e7563f40f2349d1e7bbfd7c3ca936d50fc","observation_id":"bf65c8c0-1941-4359-b84f-160000323670","resolution":{"observed_at":"2026-05-14T16:57:29.469654Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.05407","last_updated":"2019-02-25T14:18:11Z","snapshot_observed_at":"2026-07-31T19:09:21.589864Z","submitted_at":"2018-03-14T17:09:27Z","title":"Averaging Weights Leads to Wider Optima and Better Generalization","version":3},"cited_work":{"arxiv_id":"1803.05407","doi":"10.48550/arxiv.1803.05407","metadata_source":"pith","pith_arxiv_id":"1803.05407","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Averaging Weights Leads to Wider Optima and Better Generalization","venue":"cs.LG","work_id":"a7c6bded-245c-4243-8969-f16b6ac407ba","year":2018},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"cited_paper":"/paper/1803.05407","citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:db215da70e85c75a50554cf289348a66444697d099fafe8a9e4171a43a9ea442","observation_id":"c613f24e-2e8e-413f-9d75-77dc0773b3d0","resolution":{"observed_at":"2026-05-11T04:30:57.327867Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-05-23T20:53:38.184761+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T20:53:38.184761+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multi-task learning using uncertainty to weigh losses for scene geometry and semantics","venue":null,"work_id":"aecdcef1-e4d3-414f-9a3b-2aca4279ad54","year":2018},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:e4aa9c3fef67d2f9c85f2db403db0d9d859eb66e1844f37c8178df1988b5ab47","observation_id":"3054f8e3-8e9d-4962-b309-06845d0213ed","resolution":{"observed_at":"2026-05-14T16:57:29.473171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Paraphras- ing evades detectors of AI-generated text, but retrieval is an effective defense.Advances in neural information processing systems, 36:27469–27500","venue":null,"work_id":"d8e49330-d733-4a52-b175-c4651eb18910","year":2023},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:fa09daac172c556d92e4fd1736f4de4946cf6d3924c323ad848197af695e26fb","observation_id":"06add45c-f432-4bff-ae09-b4d0fe12a2a5","resolution":{"observed_at":"2026-05-14T16:57:29.347522Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"MAGE: Machine-generated text detection in the wild","venue":null,"work_id":"e0c52a6c-f18f-4c24-9ac2-0d443c4e63f5","year":2024},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:d7874bf027a48c75631c13955c2b458e4734500574e0a73ce48b2f98a71b185f","observation_id":"c05f7437-2ace-4288-9fa8-07eb6f59aa98","resolution":{"observed_at":"2026-05-14T16:57:29.459723Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"GPT detectors are biased against non-native english writers.Patterns, 4(7)","venue":null,"work_id":"9665a171-4afc-4625-b624-a41d665df8a3","year":2023},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:f40caff69c9cbaf3be7749f787dc9a3f72f072995ea8d57525517e75cfbe9277","observation_id":"27da8c53-c8e8-4013-a982-a8ace1052124","resolution":{"observed_at":"2026-05-14T16:57:29.358841Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Uncertainty regularized multi-task learning","venue":null,"work_id":"1e9f69c1-75b3-434f-83d9-4b8c3ebb3165","year":2022},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:e4829e9d58a6d8946f6b90ec0d470e202b149a586e19f3d9ab6b14a0dd646ad2","observation_id":"fb5781c6-637d-4cd0-8c53-33dbca8f5b56","resolution":{"observed_at":"2026-05-14T16:57:29.452582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"DetectGPT: zero-shot machine-generated text detection using probability curvature","venue":null,"work_id":"0c39f438-b099-44d8-bf95-aa5ee6c90a4a","year":2023},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:45cd6c873a3a9a9e4ede4f00824ac082c5aeab4d5bd0ef888d4158f42381c719","observation_id":"5289a095-d3af-4651-8b11-edb24961e453","resolution":{"observed_at":"2026-05-14T16:57:29.465845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"GPT-5.4 Mini","venue":null,"work_id":"46808efc-885a-48a8-804b-ccc86dc9a8d6","year":2026},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:847ca406d1cc8c7c34005990aa98ebc55c80c9f180a31954b009109434fd24c3","observation_id":"cb4ce2f1-4fc2-4d1c-8977-7b8c5a7cbd7c","resolution":{"observed_at":"2026-05-14T16:57:29.350165Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The FineWeb datasets: Decanting the web for the finest text data at scale.Advances in Neural Information Processing Systems, 37:30811–30849","venue":null,"work_id":"f7770577-fd81-4f91-b5b1-fa1b42287f90","year":2024},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:253e3a6dcd63d9de178e2849e35f6673569072f12571166e4433943cfb502ade","observation_id":"dc42a387-2681-4055-9af4-585a1e8769f8","resolution":{"observed_at":"2026-05-14T16:57:29.438245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.13692","last_updated":"2026-04-15T10:14:06Z","snapshot_observed_at":"2026-08-02T10:38:58.587399Z","submitted_at":"2026-04-15T10:14:06Z","title":"Breaking the Generator Barrier: Disentangled Representation for Generalizable AI-Text Detection","version":1},"cited_work":{"arxiv_id":"2604.13692","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.13692","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Breaking the Generator Barrier: Disentangled Representation for Generalizable AI-Text Detection","venue":"cs.CL","work_id":"c67d59b0-88c6-40b1-9077-0bf762f749a0","year":2026},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"cited_paper":"/paper/2604.13692","citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:8ef0afa79a521911c2fe2ce6fab4ddab07e619577a1ca1a1e1908e537355744e","observation_id":"80347850-5594-4b9e-9eb8-b60c6df84fb0","resolution":{"observed_at":"2026-05-11T04:30:57.345944Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"business","venue":null,"work_id":"eb3ac6b0-8b6a-4956-8710-6eca54965cde","year":2025},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:0feb98809070b9f4dfdafda5ae3ba53a311bd8d1dbc0d2f9259bd5ac1ccff64a","observation_id":"6245a587-004d-4141-aff2-1bf6166ef4e8","resolution":{"observed_at":"2026-05-14T16:57:29.445126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Facenet: A unified embedding for face recognition and clustering","venue":null,"work_id":"f3ae963b-c5b6-4172-bfe8-103ad8cd4d06","year":2015},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:24ed0c1c2f98c60e163d134094a43e1aa0f13f6fa452d069f77d86c6ea8b1248","observation_id":"1ebec691-c580-41e8-8b4b-3083912655a8","resolution":{"observed_at":"2026-05-14T16:57:29.477832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.09203","last_updated":"2019-11-13T03:54:12Z","snapshot_observed_at":"2026-08-03T18:37:05.537362Z","submitted_at":"2019-08-24T20:41:40Z","title":"Release Strategies and the Social Impacts of Language Models","version":2},"cited_work":{"arxiv_id":"1908.09203","doi":null,"metadata_source":"pith","pith_arxiv_id":"1908.09203","snapshot_observed_at":"2026-07-09T08:16:05.662858Z","title":"Release Strategies and the Social Impacts of Language Models","venue":"cs.CL","work_id":"d5600a1d-8baa-4d76-a815-1bfc7be1ded0","year":2019},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"cited_paper":"/paper/1908.09203","citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:3a86ef03e375b340b23c7c93572e4e586cc799551e75a1e35903c124c0a7ce03","observation_id":"1ac75f9e-f167-4245-97c1-95f4d3035c61","resolution":{"observed_at":"2026-05-16T16:17:32.011804Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Grammarly AI writing detector","venue":null,"work_id":"06e3e4a7-2dec-4a6d-b397-2a58d101d5e9","year":2026},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:0f8f2bc042c62eb9594ab3576538a346ea63dc07f95fa6ceaa76bf8df43690fd","observation_id":"0e3d165f-4b88-4401-9afa-a5368521639a","resolution":{"observed_at":"2026-05-14T16:57:29.399583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"FAID: Fine-grained AI-generated text detection using multi-task auxiliary and multi-level contrastive learning","venue":null,"work_id":"ee77a51e-435a-4dc0-9c11-8486379b862d","year":2026},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:07a6cc22ccb8eafe02ce3bee8d47254d3c342804c5f082fbf23bba6f891a4fed","observation_id":"0bb39ef8-2282-4933-bd8b-d4628abbdd54","resolution":{"observed_at":"2026-05-14T16:57:29.403211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","venue":null,"work_id":"18f94fe7-0c2e-425f-93c0-62460da15e9a","year":2017},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:f9a127d8095c0599e030b68cf2329cc7d14a98f5df01febc90496b25ddbc3110","observation_id":"80eb9801-3711-4a08-bdd1-29b7f9158cd2","resolution":{"observed_at":"2026-05-14T16:57:29.418341Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Modeling the attack: detecting AI-generated text by quantifying adversarial perturbations","venue":null,"work_id":"741dab05-3e30-4102-ae7a-7751ca405cba","year":2026},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:8215fa5211c8d71d9eda6e3ec60ef556061d38616117e5b25157b28d5e3d12bb","observation_id":"3753b50c-14d9-4927-a868-826825a66386","resolution":{"observed_at":"2026-05-14T16:57:29.432053Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"TURINGBENCH: A benchmark environment for turing test in the age of neural text generation","venue":null,"work_id":"1824e8de-1df5-459a-9e1d-f29dd869ed8a","year":2021},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:98699a9b1a2ba34cdd0cab9d707a6223a7e6f67859e303d28e833a006017995a","observation_id":"0a9f9a90-b62f-4c21-b4e5-f3b14100b987","resolution":{"observed_at":"2026-05-14T16:57:29.354328Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ghostbuster: Detecting text ghost- written by large language models","venue":null,"work_id":"4be682d1-54fe-4866-9d05-8e94152049a1","year":2024},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:7d5a4fcb5e5fbfbf509a19c80afc01c107075ac853d503c00fdb65bedc3c47a0","observation_id":"8a9e7ded-14d2-4a19-b2e5-c200136bfaa3","resolution":{"observed_at":"2026-05-14T16:57:29.380144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"M4GT- Bench: Evaluation benchmark for black-box machine-generated text detection","venue":null,"work_id":"49338d6c-6407-46f4-8619-15d721a3813e","year":2024},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:82d7d8fd3f10a6d2e87e33e2e4164a66fe8299094d2a399cc2284d2cbed750c2","observation_id":"4ca32c64-c1d6-47ca-9349-378f8707be8a","resolution":{"observed_at":"2026-05-14T16:57:29.366884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Smarter, better, faster, longer: A modern bidirectional encoder for fast, memory efficient, and long context finetuning and inference","venue":null,"work_id":"7a98e32c-b5ad-4db7-8cfc-f868404f6039","year":2025},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:326126d01506c2f4167114d8091212db46e2175d9ca316208ea581b460caf3a9","observation_id":"747f0e04-d0d0-4814-bacb-f35d1ba11a19","resolution":{"observed_at":"2026-05-14T16:57:29.362109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Seq vs seq: An open suite of paired encoders and decoders.The Fourteenth International Conference on Learning Representations","venue":null,"work_id":"af70a9dd-ef5d-4c3b-9ec6-39d2cea1100d","year":2026},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:d3456de1d2a514ae56d5a3fd1e2ae4338283570797f76c6cc125f17d200db921","observation_id":"9d30a379-7041-4a11-90f0-486712528924","resolution":{"observed_at":"2026-05-14T16:57:29.396557Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Advancing machine-generated text detection from an easy to hard supervision perspective","venue":null,"work_id":"1ccbf1fc-7b75-4e22-b591-80b9874dd4c5","year":2025},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:e97ed761487b33a5fcf9876164742a45b77ad6c1b167a684637f7e08592e67aa","observation_id":"ccb14f18-bd70-418f-a753-9fc7d1ecb9e1","resolution":{"observed_at":"2026-05-14T16:57:29.389930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"DetectRL: Benchmarking LLM-generated text detection in real-world scenarios.Advances in Neural Information Processing Systems, 37:100369–100401","venue":null,"work_id":"2dbf15ff-2e38-407e-bbae-c542084316f5","year":2024},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:340b968b5595eb55479fdad80e22db285f50914f9c42d35afbca04335dee3d90","observation_id":"67118a27-3e7b-4400-8968-b685ec780f3e","resolution":{"observed_at":"2026-05-14T16:57:29.376963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"LLMDet: A third party large language models generated text detection tool","venue":null,"work_id":"94cdc338-a3db-4095-9814-c0f88885be7d","year":2023},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:ee55884ed5332dc8043be71110c8d4b2ffe885888652704239f2ec23356060b8","observation_id":"5d231e49-85d7-4199-8321-0d54f2020888","resolution":{"observed_at":"2026-05-14T16:57:29.514791Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Human texts are outliers: Detecting LLM-generated texts via out-of-distribution detection","venue":null,"work_id":"58a645fa-8d0e-4a26-a5fb-7a04703d177c","year":2025},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:31f3295e9409c28058090909534317f7b906a18666b428573a169209c22cd160","observation_id":"74b03e12-b021-4f66-a970-e53fd48347c4","resolution":{"observed_at":"2026-05-14T16:57:29.428633Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"I ’d imagine it has something to do with availability","venue":null,"work_id":"178b887c-644b-4d39-ae72-affdde1db9b3","year":2024},"citing_paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-11T01:18:35.684352Z"},"links":{"citing_paper":"/paper/2605.06903"},"observation_digest":"sha256:891c90431ea294a941046edcb44b4e42082932f16c198c2994fca4f77df9d22c","observation_id":"911c8078-6888-4978-bfc2-8adbed7ff84e","resolution":{"observed_at":"2026-05-14T16:57:29.485984Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2605.06903","last_updated":"2026-05-07T20:05:38Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T23:19:20.674889Z","submitted_at":"2026-05-07T20:05:38Z","title":"MELD: Multi-Task Equilibrated Learning Detector for AI-Generated Text"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":8,"verified_fuzzy":36},"total_outbound_references":44},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2605.06903."}