{"as_of":"2026-08-07T17:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:fa330a13306d0063090a9fcc86218aba6d452c7e9aa3f7fb8b30465155a96a40","coverage":[{"denominator":58,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":58,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T18:11:18.809262Z","state":"measured"},{"denominator":58,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":58,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"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":[],"links":{"evidence":"/evidence","html":"/paper/2507.09016/citation-record","integrity":"/paper/2507.09016/integrity","json":"/paper/2507.09016/citation-record.json","paper":"/paper/2507.09016"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:11:22.180508Z","title":null,"venue":null,"work_id":"5017dc6d-66d1-41e9-a716-f228d0ff3cef","year":2018},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:15.599561Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:d1de97da76020d7d8427bfa8b31f70ada63d5d37d0f3e3a938324b2422435f9d","observation_id":"58a9ad55-1bfd-4b28-9fa1-d6ff5f56311b","resolution":{"observed_at":"2026-08-06T18:11:22.206826Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.05862","last_updated":"2022-04-12T15:02:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-12T15:02:38Z","title":"Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.05862","snapshot_observed_at":"2026-08-06T18:11:15.660640Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:15.660640Z"},"links":{"cited_paper":"/paper/2204.05862","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:abb2743eb2eda6c3c06b75af11fd080af8d7c85df9c94b6bf3a3f029e650a20a","observation_id":"bad13d35-e8fb-45fa-9dff-417af3d8cee9","resolution":{"observed_at":"2026-08-06T18:11:15.660640Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00782","last_updated":"2024-02-01T17:10:35Z","snapshot_observed_at":"2026-07-06T17:23:51.547578Z","submitted_at":"2024-02-01T17:10:35Z","title":"Dense Reward for Free in Reinforcement Learning from Human Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00782","snapshot_observed_at":"2026-08-06T18:11:15.717117Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:15.717117Z"},"links":{"cited_paper":"/paper/2402.00782","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:d72b6750072e2b321359061feacabfa4e7417c13a2aa9de720ce9d705effd44d","observation_id":"eeafc856-3917-4b89-81e4-fc7dc8fc5775","resolution":{"observed_at":"2026-08-06T18:11:15.717117Z","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":"2026-08-06T18:11:15.800634Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:15.800634Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:4770282f7fc9098982f40aa29598e3113912bd16dcf262515f557e51f9cec53c","observation_id":"2ce24472-7aa7-4a57-9d1a-06ee90b2877c","resolution":{"observed_at":"2026-08-06T18:11:15.800634Z","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":"2026-08-06T18:11:22.101845Z","title":null,"venue":null,"work_id":"9a0b6b6b-4e2f-4dfb-8b37-ef30c14ffeb5","year":2018},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:15.841479Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:f86b737064401b202469c0de7e178a226a4e27c9c3b03a20e1c9b11eadecb20b","observation_id":"386aa479-f503-4569-b69e-638435de6044","resolution":{"observed_at":"2026-08-06T18:11:22.124616Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:11:15.875540Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:15.875540Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:5cb9359fba271d56779c45e6ab7fbcf6ab386c5dedba8fb2704dbed0b4d254d2","observation_id":"3c7686f7-f03c-4fdf-b03f-084adf52cfe8","resolution":{"observed_at":"2026-08-06T18:11:15.875540Z","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":"2026-08-06T18:11:15.937634Z","title":null,"venue":null,"work_id":null,"year":1986},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:15.937634Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:8b0754666b0e01a4fb2f95937a8a85842dad12e89e089eb7e3c9e95964963131","observation_id":"f835b9ad-daf4-451b-b9b1-93e43de86413","resolution":{"observed_at":"2026-08-06T18:11:15.937634Z","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":"2026-08-06T18:11:22.030414Z","title":"o pf, Yannic Kilcher, Dimitri Von R \\","venue":null,"work_id":"cd4751b0-d464-4e64-b51f-fdf0f1cfaefc","year":2023},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.011470Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:c10b602d1c6e7fe75e51782292f421af75436938a8f2780e93c4bdb9e0d1d583","observation_id":"bfe9b88f-4f80-456f-b5be-f7692265f3b8","resolution":{"observed_at":"2026-08-06T18:11:22.063754Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:21.982237Z","title":null,"venue":null,"work_id":"8c500be4-3272-4574-959d-4956f9492f78","year":2025},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.088369Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:6d599f52ace089c2d1c3c84b7d6cc843d3478e6c03e2e11dd618ccb114818d55","observation_id":"51ee4109-ddfe-4878-acfe-5640d9e67efd","resolution":{"observed_at":"2026-08-06T18:11:22.000841Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-06T18:11:16.214877Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.214877Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:9865b2b11c4829fda720c2f5443f4dfbee4a4c1a584b97c7bf8df0253d7cdcbd","observation_id":"1299c575-9187-4e8a-af5f-3eebaa0b1f19","resolution":{"observed_at":"2026-08-06T18:11:16.214877Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-08-06T14:58:42.911363Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-06T18:11:16.251432Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.251432Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:e186227fc71a538e1024fe46ea9803a199a89faaff2f853951b463383d529990","observation_id":"f4bf7a61-d659-4884-8fb0-b09fc171abc6","resolution":{"observed_at":"2026-08-06T18:11:16.251432Z","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":"2026-08-06T18:11:16.262437Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.262437Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:f4ba8ecfe37c02502193caef640fa4504537e2454f847b322ab310f44d1f7143","observation_id":"dbd1009f-985f-4b4c-8c01-8aa5fee58fac","resolution":{"observed_at":"2026-08-06T18:11:16.262437Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1909.08593","last_updated":"2020-01-08T23:02:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-09-18T17:33:39Z","title":"Fine-Tuning Language Models from Human Preferences","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.08593","snapshot_observed_at":"2026-08-06T18:11:16.321723Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.321723Z"},"links":{"cited_paper":"/paper/1909.08593","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:8288ef5590f00339b1899dcfa62f5ce5698c044cf29e50676ee98cf94e1cd6ef","observation_id":"612b616f-b551-4b65-85ba-de4adf22dcd6","resolution":{"observed_at":"2026-08-06T18:11:16.321723Z","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":"2026-08-06T18:11:16.388453Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.388453Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:6b8026a2bf888e093da44f9d2b0b06776a51ca8b68061582198cf903cd63b01c","observation_id":"941c1dc9-e81f-46c1-b7e4-91600236d5f3","resolution":{"observed_at":"2026-08-06T18:11:16.388453Z","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":"2026-08-06T18:11:16.449924Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.449924Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:256b147c25bbb304911620a95b2e9902897ab9987e1e76e02649f931f1da4544","observation_id":"0e7fc508-6a5c-45c1-9d8e-bdbf6c3dc9a8","resolution":{"observed_at":"2026-08-06T18:11:16.449924Z","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":"2026-08-06T18:11:16.504921Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.504921Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:b724573e6015c0c26b97bb93033c7ae457fea6c4c1327e3f4500996fd41a9e01","observation_id":"63410ba1-b633-445c-a2d4-9ea736c354dd","resolution":{"observed_at":"2026-08-06T18:11:16.504921Z","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":"2026-08-06T18:11:21.834618Z","title":"Supervised contrastive learning","venue":null,"work_id":"96c22894-ba33-40c5-a61b-34265d1f9595","year":2020},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.619259Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:c9b4fba69e9a663713f863274885e5e31a09b0984d3ff6dd15b508895ab744c7","observation_id":"ba9dfe0a-dc23-40be-a85c-ad7b0c708e27","resolution":{"observed_at":"2026-08-06T18:11:21.888554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:21.705474Z","title":"Codet5+: Open code large language models for code understanding and generation","venue":null,"work_id":"05b89d19-6ef5-422c-bf6a-570bf5753009","year":2023},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.691299Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:b8513d06e4b9a0edc868b89d4a983ac27f4677f60032379163304884b0383922","observation_id":"9997120e-bcf0-491d-87d1-43bd748fcb81","resolution":{"observed_at":"2026-08-06T18:11:21.753607Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.15647","last_updated":"2024-11-22T05:02:26Z","snapshot_observed_at":"2026-08-04T11:46:49.970828Z","submitted_at":"2023-03-28T00:06:38Z","title":"Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.15647","snapshot_observed_at":"2026-08-06T18:11:16.772525Z","title":"Scaling down to scale up: A guide to parameter-efficient fine-tuning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.772525Z"},"links":{"cited_paper":"/paper/2303.15647","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:55d1f570994ea5294bca36a7d31272cd56389771998fee49ebdcad6889c2161b","observation_id":"e119e292-0593-46ab-983b-5bea322f6833","resolution":{"observed_at":"2026-08-06T18:11:16.772525Z","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":"2026-08-06T18:11:21.626338Z","title":"Low-rank adaptation of large language model rescoring for parameter-efficient speech recognition","venue":null,"work_id":"ef41a967-5a7f-4a67-80a9-285aee6dd85b","year":2023},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.839462Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:f0b820d80baef96782888565c2ae7ddf6d8b12cd87f428e1244a80bc94c5bcc2","observation_id":"9107796e-0247-43f0-9972-49a4f170c20f","resolution":{"observed_at":"2026-08-06T18:11:21.656071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.10512","last_updated":"2023-12-20T20:56:14Z","snapshot_observed_at":"2026-07-06T15:05:16.471478Z","submitted_at":"2023-03-18T22:36:25Z","title":"AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.10512","snapshot_observed_at":"2026-08-06T18:11:16.866634Z","title":"Adaptive budget allocation for parameter-efficient fine-tuning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.866634Z"},"links":{"cited_paper":"/paper/2303.10512","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:0e1e3aab912c5ac77084c2b0f306251fc8cf1f28429bc8905256851a2bd207d6","observation_id":"fa131fcd-4231-409b-8c0b-29a5b8628640","resolution":{"observed_at":"2026-08-06T18:11:16.866634Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08691","last_updated":"2021-09-02T17:34:41Z","snapshot_observed_at":"2026-08-06T15:24:34.790850Z","submitted_at":"2021-04-18T03:19:26Z","title":"The Power of Scale for Parameter-Efficient Prompt Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08691","snapshot_observed_at":"2026-08-06T18:11:16.937150Z","title":"The power of scale for parameter-efficient prompt tuning","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.937150Z"},"links":{"cited_paper":"/paper/2104.08691","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:fcd4d46c931b8c2bf3955258901d625d0548d86f9dbf3a80be42883503709971","observation_id":"af2dc072-2580-4a74-96d3-01141b8b2eca","resolution":{"observed_at":"2026-08-06T18:11:16.937150Z","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":"2026-08-06T18:11:21.557642Z","title":"Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning","venue":null,"work_id":"6d83c5b7-04cb-46fd-8260-0314462eaf49","year":1950},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:16.982332Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:36f26430fff633910653caa6e3eaf39bf2718009eaa7fb27872d4304dd5c30c6","observation_id":"987f26ad-a495-4ad0-b150-688fc7bb624a","resolution":{"observed_at":"2026-08-06T18:11:21.589692Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1909.09436","last_updated":"2020-06-08T09:09:28Z","snapshot_observed_at":"2026-08-06T10:54:14.530969Z","submitted_at":"2019-09-20T11:52:45Z","title":"CodeSearchNet Challenge: Evaluating the State of Semantic Code Search","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1909.09436","snapshot_observed_at":"2026-08-06T18:11:17.047310Z","title":"Codesearchnet challenge: Evaluating the state of semantic code search","venue":null,"work_id":null,"year":1909},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.047310Z"},"links":{"cited_paper":"/paper/1909.09436","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:9af65839baceda240c6b6d01ff0e3e72cad397a8235f95e3c02f903bdafc65d6","observation_id":"e246626b-9c9a-4bcf-991d-41a018edafa1","resolution":{"observed_at":"2026-08-06T18:11:17.047310Z","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":"2026-08-06T18:11:17.061360Z","title":"Retrieval-augmented generation for knowledge-intensive nlp tasks, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.061360Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:2494b9e6b8688eb9cd3c8f1158137206db7cd30ce1f56eb44b657a46068c3f80","observation_id":"70fc65b4-8e97-41f5-a928-3ffebcf67f0a","resolution":{"observed_at":"2026-08-06T18:11:17.061360Z","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":"2026-08-06T18:11:21.482189Z","title":"A neural framework for retrieval and summarization of source code","venue":null,"work_id":"c50f9cfc-5504-4fa3-981d-9ae2364d538c","year":2018},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.129890Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:cc5823d417f001587e25bb6da5f5168a300e66ea3365478973a72fbd640f6cdd","observation_id":"19cb96ec-53e2-430c-b51f-56a5b5bf392b","resolution":{"observed_at":"2026-08-06T18:11:21.516321Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:21.417592Z","title":"Survey of code search based on deep learning","venue":null,"work_id":"1d7223fc-0b49-49e3-b3df-fb4660a0a0c4","year":2023},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.145912Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:ccb7cbae396b87f76530e44798c6d7034642103e4a3ce3a5e9b9cad3fbd7da2b","observation_id":"8e91ad1a-28c4-4ae4-9385-0b0cb8122892","resolution":{"observed_at":"2026-08-06T18:11:21.444372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:21.349979Z","title":"Rosf: Leveraging information retrieval and supervised learning for recommending code snippets","venue":null,"work_id":"854698df-03c2-42dd-a9f6-1cb7c2f14d4f","year":2016},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.162723Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:9d414b7ce6aacea383d0d826ceb81d105fc51ace259895a0d6b9551afd226cc0","observation_id":"79b1bf6f-5d1a-48e2-9116-8e3f5146d2a7","resolution":{"observed_at":"2026-08-06T18:11:21.381720Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:21.281280Z","title":"Sniff: A search engine for java using free-form queries","venue":null,"work_id":"587f6b3d-333d-4652-b43e-326de14d3c39","year":2009},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.216836Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:e2767d160ccaf8c155a925915181f4096ea1bc308ff6c6285b348711b17c2a5b","observation_id":"d0529bbc-fcb9-41b3-871a-d9ef5c0cec66","resolution":{"observed_at":"2026-08-06T18:11:21.308746Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:21.213332Z","title":"Nl-based query refinement and contextualized code search results: A user study","venue":null,"work_id":"70667a46-3679-46e1-91cf-b1086c2a0d7f","year":2014},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.275130Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:109caca6915e9ed11bc0d10bf57d7a95737d9340dae7ca67ac23aa11b7fd5c61","observation_id":"509fd0b6-6135-41c5-bdab-f760b591325b","resolution":{"observed_at":"2026-08-06T18:11:21.240680Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:21.074406Z","title":"Bimodal modelling of source code and natural language","venue":null,"work_id":"03534f7b-5f19-4176-9f51-dfc66556b593","year":2015},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.366319Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:3acc483cf2bb472f9891e285c6545d6337c1ae4d8f00ba90f92d7d8618e40219","observation_id":"dc49fc0d-8ae9-49d8-a472-d9fc3e34745c","resolution":{"observed_at":"2026-08-06T18:11:21.146731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2002.08155","last_updated":"2020-09-18T15:38:12Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-02-19T13:09:07Z","title":"CodeBERT: A Pre-Trained Model for Programming and Natural Languages","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.08155","snapshot_observed_at":"2026-08-06T18:11:17.427396Z","title":"Codebert: A pre-trained model for programming and natural languages","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.427396Z"},"links":{"cited_paper":"/paper/2002.08155","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:9a2a1a9a225bf24f4139dc84eeaa214370fc7e22f3e67d650c3e5dacc91fe750","observation_id":"3f01c3ea-7025-44a7-a973-522dd045b633","resolution":{"observed_at":"2026-08-06T18:11:17.427396Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.08366","last_updated":"2021-09-13T05:48:51Z","snapshot_observed_at":"2026-07-06T09:56:32.308108Z","submitted_at":"2020-09-17T15:25:56Z","title":"GraphCodeBERT: Pre-training Code Representations with Data Flow","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.08366","snapshot_observed_at":"2026-08-06T18:11:17.505853Z","title":"Graphcodebert: Pre-training code representations with data flow","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.505853Z"},"links":{"cited_paper":"/paper/2009.08366","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:dc1eaf254b25696c4f89a981d448aae0296e46df02eeb9be3077fa3aae23643f","observation_id":"de7cba3b-e59b-42fe-b552-9f9c8d951b86","resolution":{"observed_at":"2026-08-06T18:11:17.505853Z","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":"2026-08-06T18:11:20.951725Z","title":"Comparison of graph embeddings for source code with text models based on cnn and codebert architectures","venue":null,"work_id":"1e7c16f9-5f13-41fb-ac97-68408727286f","year":2023},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.539931Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:18055bd223e5be613c9cf9d71d0a001624f36d0d7084f732c6a54aa19be136aa","observation_id":"0cb873f5-3d83-4e10-8219-2fbb9a90f47d","resolution":{"observed_at":"2026-08-06T18:11:21.011856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:20.833684Z","title":"A novel neural source code representation based on abstract syntax tree","venue":null,"work_id":"475ce944-6d3b-4c67-912d-c0ddeedfcbb5","year":2019},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.584552Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:d469d366feffe45553f474d0981e11766ef8549ca06419fff4a14b612d41168e","observation_id":"bb92ce0a-c8c9-420a-b5c4-d82a5f126286","resolution":{"observed_at":"2026-08-06T18:11:20.869716Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2006.05405","last_updated":"2021-05-13T03:41:22Z","snapshot_observed_at":"2026-08-05T13:28:04.337023Z","submitted_at":"2020-06-09T17:09:29Z","title":"Retrieval-Augmented Generation for Code Summarization via Hybrid GNN","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.05405","snapshot_observed_at":"2026-08-06T18:11:17.652951Z","title":"Retrieval-augmented generation for code summarization via hybrid gnn","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.652951Z"},"links":{"cited_paper":"/paper/2006.05405","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:f8a221e5bac544338bda77b2bde0f902b1d8b0dbfa58a40c5225d07c86e7151b","observation_id":"fa3f9530-f6c6-4b31-880c-146378ec7203","resolution":{"observed_at":"2026-08-06T18:11:17.652951Z","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":"2026-08-06T18:11:20.738702Z","title":"Multimodal representation for neural code search","venue":null,"work_id":"2fae7a74-de70-4679-acf4-2e1b6e5c0024","year":2021},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.717699Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:0ba2a1af8597a1a03ea5cfb0469058724617c7a40230d290f88f1ea6d5c0b210","observation_id":"1a02622e-c26b-4341-9f7a-adebede6942b","resolution":{"observed_at":"2026-08-06T18:11:20.776229Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.10005","last_updated":"2022-01-24T23:36:20Z","snapshot_observed_at":"2026-07-06T12:30:51.934079Z","submitted_at":"2022-01-24T23:36:20Z","title":"Text and Code Embeddings by Contrastive Pre-Training","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.10005","snapshot_observed_at":"2026-08-06T18:11:17.742416Z","title":"Text and code embeddings by contrastive pre-training","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.742416Z"},"links":{"cited_paper":"/paper/2201.10005","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:8075a6a63416b7ded47cd959bf0eb8c96d91555177262e77559e424587d74a99","observation_id":"9e3e14a9-44e7-4517-84b0-d3266b8d988e","resolution":{"observed_at":"2026-08-06T18:11:17.742416Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.12148","last_updated":"2023-12-19T13:31:24Z","snapshot_observed_at":"2026-07-06T17:05:19.007669Z","submitted_at":"2023-12-19T13:31:24Z","title":"Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.12148","snapshot_observed_at":"2026-08-06T18:11:17.796208Z","title":"Parameter-efficient fine-tuning methods for pretrained language models: A critical review and assessment","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.796208Z"},"links":{"cited_paper":"/paper/2312.12148","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:c95b4461eeb14f420cc8231c3a02ef309ad54d3c8f576069d16b865673f278eb","observation_id":"17def1db-fb88-4ee0-b33e-bf52a3515e17","resolution":{"observed_at":"2026-08-06T18:11:17.796208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.10462","last_updated":"2024-12-27T05:30:00Z","snapshot_observed_at":"2026-07-06T16:08:21.060375Z","submitted_at":"2023-08-21T04:31:06Z","title":"Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.10462","snapshot_observed_at":"2026-08-06T18:11:17.856541Z","title":"Exploring parameter-efficient fine-tuning techniques for code generation with large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.856541Z"},"links":{"cited_paper":"/paper/2308.10462","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:d713dc7c65632c574bdd3af979b1656856a255fd2e875dec5dcc403f113ead0b","observation_id":"49e62bf0-285a-4e4e-b3e8-64db6a7303db","resolution":{"observed_at":"2026-08-06T18:11:17.856541Z","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":"2026-08-06T18:11:20.611438Z","title":"No more fine-tuning? an experimental evaluation of prompt tuning in code intelligence","venue":null,"work_id":"34ceb5ce-2c2a-4540-b3c9-22c6674011ed","year":2022},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.906366Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:fd1a834c385156e49fe689d29b44f57f29b047db56a97a2353acc5520149b528","observation_id":"61f498a0-9176-4fe0-bb0f-98179a828d02","resolution":{"observed_at":"2026-08-06T18:11:20.666704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.00859","last_updated":"2021-09-02T12:21:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-09-02T12:21:06Z","title":"CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.00859","snapshot_observed_at":"2026-08-06T18:11:17.942358Z","title":"Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.942358Z"},"links":{"cited_paper":"/paper/2109.00859","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:6f8a635c4bc10778d91daa0e52f56606fd15cb79817ad93ffda4a658aa1da61f","observation_id":"2e9e1ddc-8667-44b0-a21a-6536d793b22c","resolution":{"observed_at":"2026-08-06T18:11:17.942358Z","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":"2026-08-06T18:11:20.502232Z","title":"Self-supervised learning: Generative or contrastive","venue":null,"work_id":"c3c650c6-da59-4261-a854-d52664975ccb","year":2021},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:17.988530Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:e189fa093207abbb23fe12ba3f50d927a71dded45353c749c5c445e7880f84a9","observation_id":"9e5292aa-ba79-4cc5-97db-9a4a50115d96","resolution":{"observed_at":"2026-08-06T18:11:20.540095Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:20.365071Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":"6a5c80b5-05e3-410b-99e2-532d4e8d104f","year":2021},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.077457Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:d79c7ce8a493da31371075ec68e2a95440b7687985efdffde22bc7922b9e09a6","observation_id":"d2e86f54-df81-41b2-aa97-e404d266d946","resolution":{"observed_at":"2026-08-06T18:11:20.449645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:20.251186Z","title":"Contrastive multiview coding","venue":null,"work_id":"78189878-e1ba-48cd-a53f-95b8e6ed809c","year":2020},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.140889Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:66d2dfde6f2b2e1a1861d30229a61cdc4d5356f773bb1ca071e534ea56a7f1c0","observation_id":"45a60847-61cf-4f7a-bc67-400d61bc2081","resolution":{"observed_at":"2026-08-06T18:11:20.291113Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:20.145276Z","title":"Graph contrastive learning with augmentations","venue":null,"work_id":"3989d92b-7dfc-45c8-ad1f-8a390ff0196b","year":2020},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.179294Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:8d4e69ece8e7c2b9b233dae4ef1771a28f09936eb8f5c181e7ee08c5c7dc6be3","observation_id":"3be8b282-83bb-489e-ae3c-edbade85d49e","resolution":{"observed_at":"2026-08-06T18:11:20.196780Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:19.947275Z","title":"Contrastive learning with cross-modal knowledge mining for multimodal human activity recognition","venue":null,"work_id":"653490b7-e954-473c-964e-252c9d62adfa","year":2022},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.226374Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:b902bc8ec28b17a6756a80fcc6a9a8e709134a36eb37c40140e47cc58cc86e71","observation_id":"73a98453-35a0-43fe-b913-ad29c2dd8679","resolution":{"observed_at":"2026-08-06T18:11:20.037329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T18:11:18.283931Z","title":"A simple framework for contrastive learning of visual representations","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.283931Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:65bbff46fd0afe87a6a75db0e107c485b3832bc4c9a55373fc44d7e807b40041","observation_id":"3be1af22-f55b-4e56-9205-63d2ccf3f465","resolution":{"observed_at":"2026-08-06T18:11:18.283931Z","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":"2026-08-06T18:11:19.755945Z","title":"Self-supervised contrastive bert fine-tuning for fusion-based reviewed-item retrieval","venue":null,"work_id":"18b07495-f6ba-420b-9fbc-be3d96c91f3f","year":2023},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.309893Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:5acc0433e50e9d8ad4731bbc45ab2660ca39eac82609c2805e1cfb31c2a734af","observation_id":"c1506646-8bc8-4ca8-8670-5c042bd0b330","resolution":{"observed_at":"2026-08-06T18:11:19.844853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:19.630798Z","title":"Clip4clip: An empirical study of clip for end to end video clip retrieval and captioning","venue":null,"work_id":"08c61cc7-bef2-46ca-8535-0f6e9055ca7e","year":2022},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.413392Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:601ab2e397f4b65ee91424bee830cf553496542dc8c71f92743b17fd5fbeabdf","observation_id":"46e9afbc-46ee-4521-9e77-7935e11ed7e1","resolution":{"observed_at":"2026-08-06T18:11:19.697973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.08474","last_updated":"2022-06-16T22:49:39Z","snapshot_observed_at":"2026-07-06T13:21:49.288193Z","submitted_at":"2022-06-16T22:49:39Z","title":"XLCoST: A Benchmark Dataset for Cross-lingual Code Intelligence","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.08474","snapshot_observed_at":"2026-08-06T18:11:18.458825Z","title":"Xlcost: A benchmark dataset for cross-lingual code intelligence","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.458825Z"},"links":{"cited_paper":"/paper/2206.08474","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:4a86af4e8660aef13429e1b8eeac282e123e35294b22baaf63a59571f5b6a961","observation_id":"8369c4c5-dc60-42d0-862f-72a384503002","resolution":{"observed_at":"2026-08-06T18:11:18.458825Z","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":"2026-08-06T18:11:19.484431Z","title":"Staqc: A systematically mined question-code dataset from stack overflow","venue":null,"work_id":"8a767942-6b81-458b-a75d-cb8fd3fe602a","year":2018},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.513215Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:79cccb590b929336c87826575fc4c3dd05ad510e5b3da5d8e7bd697261a8bc7a","observation_id":"b51eae7b-fbe3-4bb3-97f7-f1b1a133b19f","resolution":{"observed_at":"2026-08-06T18:11:19.570350Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.01710","last_updated":"2021-10-04T20:48:31Z","snapshot_observed_at":"2026-07-06T11:54:19.474059Z","submitted_at":"2021-10-04T20:48:31Z","title":"PyTorrent: A Python Library Corpus for Large-scale Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.01710","snapshot_observed_at":"2026-08-06T18:11:18.552851Z","title":"Pytorrent: A python library corpus for large-scale language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.552851Z"},"links":{"cited_paper":"/paper/2110.01710","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:43928afc4766f90edaa3b79deb561a2b4c0900e7157d3ceded059b5d7ad6e6d8","observation_id":"0c4c7ec4-d166-400e-829d-0abce00ffad4","resolution":{"observed_at":"2026-08-06T18:11:18.552851Z","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":"2026-08-06T18:11:19.400295Z","title":"Search4code: Code search intent classification using weak supervision","venue":null,"work_id":"7a5030a7-50c0-4ae4-bcc9-630f1b3c92a6","year":2021},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.616064Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:f949b1181c633ba03bfe1fe18fced55c1b54d9204438feca3e336055fea7e3a3","observation_id":"378e84a6-2878-45db-b387-9c224016a3c7","resolution":{"observed_at":"2026-08-06T18:11:19.436726Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.14139","last_updated":"2021-11-28T13:36:24Z","snapshot_observed_at":"2026-07-06T12:12:49.630882Z","submitted_at":"2021-11-28T13:36:24Z","title":"Semantic Code Search for Smart Contracts","version":1},"cited_work":{"arxiv_id":"2111.14139","doi":null,"metadata_source":"pith","pith_arxiv_id":"2111.14139","snapshot_observed_at":"2026-08-06T18:11:18.902052Z","title":"Semantic Code Search for Smart Contracts","venue":"cs.SE","work_id":"fc689561-c13f-4a1a-b7fd-be793e953744","year":2021},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.662649Z"},"links":{"cited_paper":"/paper/2111.14139","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:0afed7b683dc688ce7c2353cf0e60c0c6daacc7258fcb3d13d7d7d8f4bf01bf1","observation_id":"5cf5158a-fd17-4187-9e49-a1bc4a2fc22d","resolution":{"observed_at":"2026-08-06T18:11:18.941088Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T18:11:19.201969Z","title":"Isadetect: Usable automated detection of cpu architecture and endianness for executable binary files and object code","venue":null,"work_id":"76cbac1d-a5d9-4ce2-8851-505cbaf2bfe6","year":2020},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.706136Z"},"links":{"citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:819247ca289618403530c32b72a4e8fdd8d2823ea8171ac10a77cf619cbf7d58","observation_id":"31331050-f27f-4565-a991-4d749c72b6f1","resolution":{"observed_at":"2026-08-06T18:11:19.286269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.14196","last_updated":"2024-01-26T09:23:11Z","snapshot_observed_at":"2026-08-06T22:40:28.707813Z","submitted_at":"2024-01-25T14:17:53Z","title":"DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.14196","snapshot_observed_at":"2026-08-06T18:11:18.757859Z","title":"Deepseek-coder: When the large language model meets programming--the rise of code intelligence","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.757859Z"},"links":{"cited_paper":"/paper/2401.14196","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:e845a48439fb266fa6984925cc2b851739503251042a3700d60c26fa7ff335cc","observation_id":"3a2f4bbb-cc6f-4d56-81c0-f687588a51b6","resolution":{"observed_at":"2026-08-06T18:11:18.757859Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1803.01937","last_updated":"2018-03-05T21:35:04Z","snapshot_observed_at":"2026-08-01T11:54:25.770314Z","submitted_at":"2018-03-05T21:35:04Z","title":"ROUGE 2.0: Updated and Improved Measures for Evaluation of Summarization Tasks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.01937","snapshot_observed_at":"2026-08-06T18:11:18.809262Z","title":"Rouge 2.0: Updated and improved measures for evaluation of summarization tasks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling","version":2},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-06T18:11:18.809262Z"},"links":{"cited_paper":"/paper/1803.01937","citing_paper":"/paper/2507.09016"},"observation_digest":"sha256:0cafb1d21d9786fabca4d750e0824fefa893feee043ac1cfd209d5a199dd568b","observation_id":"636ae2ae-0b51-4828-871c-04b442108990","resolution":{"observed_at":"2026-08-06T18:11:18.809262Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.09016","last_updated":"2025-07-16T09:24:11Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T18:03:53.710746Z","submitted_at":"2025-07-11T20:49:04Z","title":"Enhancing RLHF with Human Gaze Modeling"},"reference_resolution":{"displayed":58,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":32,"verified_exact":1,"verified_fuzzy":25},"total_outbound_references":58},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2507.09016."}