{"as_of":"2026-08-01T16:03:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:70b7edb362091d6f800388582b03f864371ae0a5b1a5533457e8c0527521c8a1","coverage":[{"denominator":37,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-12T07:15:01.508458Z","state":"measured"},{"denominator":38,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":38,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-01T06:32:01.292127+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":"2026-07-12T07:15:01.508458Z","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":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.02757","snapshot_observed_at":"2026-07-12T07:15:01.508458Z","title":"Recent work incorporates explicit language tag sig- nals and language-aware decoding [14]","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"cited_paper":"/paper/2607.02757","citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:764c074c86764fa5d2ef63385223e875723aff75996dcbcf99a81549a23c3cb1","observation_id":"01b5f94d-e747-4ff6-9c9e-21a41db3b28a","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2607.02757/citation-record","integrity":"/paper/2607.02757/integrity","json":"/paper/2607.02757/citation-record.json","paper":"/paper/2607.02757"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-12T07:15:01.508458Z","title":"listen again and fix","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:747ed7bddacddf1ab3c28562c99b27a12a89c778d473eef122888d7bdeba323a","observation_id":"d24bcbce-16b7-40d0-a531-63bb7535ae3a","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2607.02757","snapshot_observed_at":"2026-07-12T07:15:01.508458Z","title":"Recent work incorporates explicit language tag sig- nals and language-aware decoding [14]","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"cited_paper":"/paper/2607.02757","citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:764c074c86764fa5d2ef63385223e875723aff75996dcbcf99a81549a23c3cb1","observation_id":"01b5f94d-e747-4ff6-9c9e-21a41db3b28a","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"The audio contains speech mixing Japanese and English","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:d60f35117999283abde31e7b7cb9f16c5003614e1dfad9a3986a31ecb92470fc","observation_id":"ec56a61c-f75c-450b-bf33-de506c8cb87e","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Datasets CS-FLEURS.CS-FLEURS [11] is a massively multilingual code-switched speech dataset built on FLEURS [15], covering 52 languages across 113 code-switched pairs","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:6f96866752dbcc6c5aa4ccc8aca53a50c4d8434df78cdb401b27f4561ab44bff","observation_id":"8ac1d728-cb69-4cbb-9316-0ab0dd9b6e4c","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Even at 10% data, RLVR matches or surpasses LoRA trained on the full dataset","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:05f4fe65fa8204fbe32c4b09875a2489e03e7ed1647a16c1a864ea1e57804723","observation_id":"ea481424-64dd-44b1-a632-ae16e21d94bf","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"seventy km","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:bdd39b211a089255a1bb0aaed7fa0dbb8bf203cf7c8ad7c5c3a571ff0ef98328","observation_id":"ae7af0ab-50dc-4a02-83a1-cefcdc0475ff","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-07-12T07:15:01.508458Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:c710f3c0786cf3f6ab9d3fc8b0cc0d6efaeeb0d423c10202f9e662bca55288ab","observation_id":"9a69c9d3-2ddc-40bf-8765-26ce48735f5c","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Additionally, LLMs were used for spellchecking and suggesting edits to further improve the flu- ency and conciseness of the paper during the drafting process","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:dc8b327cb8dc9c4aad5d4a4b3ca8b674ca2e10a3a02f617977bdc3fe818c3492","observation_id":"40d07c3e-e878-4b1c-9b86-8a49d2deb4d3","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Sometimes I’ll start a sentence in Spanish y termino en español: Toward a typology of code-switching,","venue":null,"work_id":null,"year":1980},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:c3d1f854997c59d3d45e6baaf9b00dfc77a7dd3813834195b5ec379bb9ddfc38","observation_id":"3b272bbe-be45-49fb-9198-6de3f70178be","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"A survey of code-switching: Linguistic and social perspectives for language technologies,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:87693c6f51964e4489e516f29e714debc1f35031446df11879065bdf55e846fe","observation_id":"837764ec-c1dd-4595-a4d0-2b010d2a2597","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"The decades progress on code-switching research in NLP: A systematic sur- vey on trends and challenges,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:85b97f6ed388150b59835a7a0d75a47cbda3a40a0bea83b8f0aec1d7854c03e2","observation_id":"9ff58691-c757-4d73-9ad8-21a94007ef32","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.00784","last_updated":"2020-07-22T23:55:01Z","snapshot_observed_at":"2026-07-06T07:43:00.418471Z","submitted_at":"2019-03-25T14:36:50Z","title":"A Survey of Code-switched Speech and Language Processing","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.00784","snapshot_observed_at":"2026-07-12T07:15:01.508458Z","title":"A survey of code-switched speech and language processing,","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"cited_paper":"/paper/1904.00784","citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:97afbbbe65dfbb70327d596f7183544c5fac7b2242cb4b986ec2003eaafc5474","observation_id":"f18363fc-2449-495b-bbf9-46ae75bbb15c","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Robust speech recognition via large-scale weak su- pervision,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:bc3aad710c78011b1bb1aa4614936bcffd528047f9b605c33fa00a4fad845970","observation_id":"51f7e4aa-e133-4b84-b5de-3dc92def8156","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"wav2vec 2.0: A framework for self-supervised learning of speech representa- tions,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:5d7b8512f8f47576d5de58686b986c975855b19b7991fd836cd1e762e618b3e0","observation_id":"bb7f02bc-cb29-4b60-9b4a-10ec8365d201","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Qwen-Audio: Advancing universal audio under- standing via unified large-scale audio-language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:4357e1514ea2fe3680a27a323687341620c5453f57f24449b38a74d7b5d9af61","observation_id":"7ed4656e-5f9d-4181-9c93-d1090a8bfaf4","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Sequence level training with recurrent neural networks,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:03e016396f52167d05c9d8b600d0de2749ca66292a3e7d963f83726f67765f0e","observation_id":"c082e8ef-2c74-4fdc-8a11-76162e19c524","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Reducing language confusion for code-switching speech recognition with token-level language diarization,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:735efffb127e12f2cf0b10333c6e992aab5459e288e12ac357e7bae57ef7436b","observation_id":"b6331c25-20c7-4c8a-9590-45618c512166","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"DeepSeekMath: Pushing the limits of mathemati- cal reasoning in open language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:0bd3a9385605978bf983bf756ced4391aba0b57b1560565b191c9d82e2d02517","observation_id":"28ffd3a2-5a4f-4dee-b3f4-1773656634dc","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"CS-FLEURS: A massively multilingual and code- switched speech dataset,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:f52e7c67e536b792ba93140c80cab953f76edf1cec402d48e5952dfa1a2865a9","observation_id":"c42c6355-e94c-4b0c-91dc-7a62b01cd9ee","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"SwitchLingua: The first large-scale multilingual and multi-ethnic code-switching dataset,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:e56932783e5e3d30ca29a9642cc21b08b5abc1bde8a6c65c3d77e3d37537659e","observation_id":"730b778f-b456-4763-b0df-d6efc364aa1d","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Code- switching in automatic speech recognition: The issues and future directions,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:80edfcd1f6338d69d482d56b1747db483c74016e81698381e489d2cb9ead379a","observation_id":"777e5f9c-007c-4029-8884-76a2f097fcf4","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Text-derived language identity incorpora- tion for end-to-end code-switching speech recognition,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:5c6d6dca712829c46649b0a69362f0480a9351c070928dcee3228172728be1e2","observation_id":"3495ed74-a4a9-4346-ad6a-220371ff37ab","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"FLEURS: Few-shot learning evaluation of universal representations of speech,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:48dad9490f34ed6cb889579d8674220f60c9cd1cf764836fc593c62af8b061e7","observation_id":"f68f5c38-8bf4-4289-aaaa-84978d58357d","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Instruction-following speech recognition,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:4ce81cc0663e5d4b836ca30e7e72bf30d404c734825d7f8617ad1ba33df1291d","observation_id":"0d3837f2-af50-4f68-8777-4c2535585df2","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"On exposure bias, hallucination and domain shift in neural machine translation,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:59423c20256fcb091c8a3bfde1abc4ef36c9ed45bdc97af2d25f18a3fb7a4437","observation_id":"baf90410-87e7-46b7-9ed2-ae1e2d22e866","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Minimum word error rate training for attention-based sequence-to-sequence models,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:f1028899c19aa1662fe2a5757daa5704f7f43ea5f3b42813766fb67e4e2db8a0","observation_id":"651f3032-a6e4-4816-9baa-539e931c306b","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Optimizing expected word error rate via sampling for speech recognition,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:2f1ad8aeeb5a71b46328d65d60b6391054af80f2396f6a751e4f716ea5788df0","observation_id":"e262b8ee-eb1e-417a-9b21-35103cdb1475","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Reinforcement learning with verifiable rewards implicitly incentivizes correct reasoning in base LLMs,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:cfd9388c2b728e5bf75866a86bd8d454ef4670a0f53eaec9d1c6b3276547f836","observation_id":"8d1fefb2-dd1e-400c-bd6f-b18d0d6e2681","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"DeepSeek-R1: Incentivizing reasoning capability in LLMs via reinforcement learning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:797d7769d200f6a47201811d5ac16df5b40dad67458915998d6d55adc21696fe","observation_id":"11e93f2a-ffd2-4d53-83c2-f7af1ae38cbb","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2509.01939","last_updated":"2025-09-02T04:20:12Z","snapshot_observed_at":"2026-07-06T22:22:03.439592Z","submitted_at":"2025-09-02T04:20:12Z","title":"Group Relative Policy Optimization for Speech Recognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2509.01939","snapshot_observed_at":"2026-07-12T07:15:01.508458Z","title":"Group rel- ative policy optimization for speech recognition,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"cited_paper":"/paper/2509.01939","citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:fc6cb51a81891eb148b1c827d0ecb5f6e046e66f07125fc063b495a396bcffa1","observation_id":"2c626588-fa5b-4e4c-a753-1042c39379a1","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Omni-R1: Do you really need audio to fine-tune your audio LLM?","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:1d1940ff271106d997315c1c75fe8b8d402a5e5335763c9e2df56ddc4f5c7878","observation_id":"76fb79d1-d2f3-4329-8e86-85f977044612","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Self-refine: Iterative refinement with self-feedback,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:ac2721832365a85c2da47ef3a6c0e1e43b7ad83b68c5a253606698e7bba5e886","observation_id":"462f70e8-f387-4b5f-9734-750b14fe30cf","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"Word alignment by fine-tuning embed- dings on parallel corpora,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:13d6b09a7f37a0ed261678e77c2a89ff926c0da264fb0a9282c4cf79a789b65e","observation_id":"46778176-6539-4cc8-bb83-01dacf054b4a","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"XTTS: a massively multilingual zero-shot text-to-speech model,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:ac1f0cd2a4b646168a1655157e79db0a63eeb1e94c2d32748c94ad3a0205c15a","observation_id":"52e30960-1f95-40ff-8487-303752a8529b","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"LoRA: Low-rank adaptation of large lan- guage models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:7ed8e2eb46b2c952624e82dd32e7daa73e76e9c30ae5098da67ca670c478efd6","observation_id":"19f880b8-b3a0-4b8e-9b7b-f961f66cf573","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10671","last_updated":"2024-09-10T13:25:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-15T12:35:42Z","title":"Qwen2 Technical Report","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.10671","snapshot_observed_at":"2026-07-12T07:15:01.508458Z","title":"Qwen2 technical report,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"cited_paper":"/paper/2407.10671","citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:c5ff8e30a7b947023c9850397e1e2fdbbcb1bcb46be0f485ec77206eddbf5e5c","observation_id":"fb2d5832-f187-4670-b3f3-b035909d8f83","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","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":"2026-07-12T07:15:01.508458Z","title":"DeepSpeed: System optimizations enable training deep learning models with over 100 billion parameters,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-12T07:15:01.508458Z"},"links":{"citing_paper":"/paper/2607.02757"},"observation_digest":"sha256:f3fd427000f424e3c93e7cadb4c13022d5708150eb571ab532f8cdbff80f9e12","observation_id":"5cb128fe-ccd0-4389-9f2e-71dad2f9c4fa","resolution":{"observed_at":"2026-07-12T07:15:01.508458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.02757","last_updated":"2026-07-02T20:44:53Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-12T07:15:01.305910Z","submitted_at":"2026-07-02T20:44:53Z","title":"Reinforcement Learning for Data-Efficient Code-Switched ASR"},"reference_resolution":{"displayed":37,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":36,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":37},"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":"2026-08-01T06:32:01.292127+00:00","source":"crossref"},{"observed_at":"2026-08-01T06:31:58.492377+00:00","source":"retraction_watch"}],"thesis":"As of 1 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 1 inbound Pith citation observation for arXiv:2607.02757."}