{"as_of":"2026-08-09T15:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:16ccd91b5178338c0c0eca5f50c46fbcd7d277aa565d2c85675fc7523fe0b429","coverage":[{"denominator":34,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":34,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T15:01:05.271053Z","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":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:03:05.859450Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-19T14:22:23.848578Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"cited_work":{"arxiv_id":"2502.01567","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.01567","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scalable language models with posterior inference of latent thought vectors.arXiv preprint arXiv:2502.01567","venue":null,"work_id":"d18b09dc-7de8-456f-be99-737f5c25e298","year":null},"citing_paper":{"arxiv_id":"2505.17384","last_updated":"2026-04-14T11:59:44Z","snapshot_observed_at":"2026-07-31T16:20:27.798904Z","submitted_at":"2025-05-23T01:45:47Z","title":"Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-19T14:20:49.548475Z"},"links":{"cited_paper":"/paper/2502.01567","citing_paper":"/paper/2505.17384"},"observation_digest":"sha256:aea2674a5cb32f50efec75e7fd1a85d8acaf01810eff47e528870c5ff0b6b4f2","observation_id":"e25ad007-d75b-489f-98a5-7d324ccc3324","resolution":{"observed_at":"2026-05-19T14:22:23.851235Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.01567","snapshot_observed_at":"2026-08-07T14:03:05.859450Z","title":"Scalable language models with posterior inference of latent thought vectors,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.20223","last_updated":"2025-05-26T17:06:00Z","snapshot_observed_at":"2026-08-08T00:05:56.709460Z","submitted_at":"2025-05-26T17:06:00Z","title":"Chain-of-Thought for Autonomous Driving: A Comprehensive Survey and Future Prospects","version":1},"reference_index":160,"source":"pdf_text","source_observed_at":"2026-08-07T14:03:05.859450Z"},"links":{"cited_paper":"/paper/2502.01567","citing_paper":"/paper/2505.20223"},"observation_digest":"sha256:8d049bbf0186097dd8bde5d2a652e7896196b02bb6a24a5f01461c83a54279a7","observation_id":"9e42fc98-d58f-4f0d-bbf6-de0b0f04539d","resolution":{"observed_at":"2026-08-07T14:03:05.859450Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.01567","snapshot_observed_at":"2026-08-07T10:42:40.135106Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.04611","last_updated":"2025-06-05T04:02:17Z","snapshot_observed_at":"2026-08-09T14:45:17.460081Z","submitted_at":"2025-06-05T04:02:17Z","title":"Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-07T10:42:40.135106Z"},"links":{"cited_paper":"/paper/2502.01567","citing_paper":"/paper/2506.04611"},"observation_digest":"sha256:80d06b9b83954019f3791b0780598869998e5fbd8f2c87854a9c53971df21401","observation_id":"d49249a7-0d70-47bd-9856-88bbec989c46","resolution":{"observed_at":"2026-08-07T10:42:40.135106Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.01567","snapshot_observed_at":"2026-08-05T11:39:36.620227Z","title":"Scalable language models with posterior inference of latent thought vectors","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.02350","last_updated":"2025-09-02T14:16:02Z","snapshot_observed_at":"2026-08-09T03:56:11.167539Z","submitted_at":"2025-09-02T14:16:02Z","title":"Implicit Reasoning in Large Language Models: A Comprehensive Survey","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T11:39:36.620227Z"},"links":{"cited_paper":"/paper/2502.01567","citing_paper":"/paper/2509.02350"},"observation_digest":"sha256:a60e815b8ed75cdb15c5155c654f2d29327c0d086b4cb01e365db65721dc6e03","observation_id":"49ce26f3-6e9e-4d3d-bdc6-4868b89b38d6","resolution":{"observed_at":"2026-08-05T11:39:36.620227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.01567/citation-record","integrity":"/paper/2502.01567/integrity","json":"/paper/2502.01567/citation-record.json","paper":"/paper/2502.01567"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T15:01:05.851162Z","title":"In few-shot scenarios, we concatenate examples as prompts and generate responses accordingly","venue":null,"work_id":"3aa523a9-4f06-4e08-a74a-807babd5d4d0","year":2024},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.261874Z"},"links":{"citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:63aacabc7d5233a0a63a7921873f340b57cf4e7835cff06b20a472a9a950b43f","observation_id":"47918210-9e67-4599-82f7-0ddb9f5152fa","resolution":{"observed_at":"2026-08-09T15:01:05.855894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T15:01:05.837025Z","title":"fun” character that’s been given yet another new set of episodes. “I’m just a masterful man,","venue":null,"work_id":"77e2ce46-0499-4a2f-adcb-34bfe637cd16","year":1991},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.266296Z"},"links":{"citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:366db516b464710c40b5567d06055698052e8943144d57dd0ca9ecfebc79c5d5","observation_id":"f3b9d8f1-0675-4647-9a46-6a42c54d6c14","resolution":{"observed_at":"2026-08-09T15:01:05.841364Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-09T15:01:05.160271Z","title":"Deepseek-r1: In- centivizing reasoning capability in llms via reinforcement learning.arXiv preprint arXiv:2501.12948,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.160271Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:cfa3b8982fcec846df1d8dd6c047cbeeaac2ddd8355a321712e500b6c15f657a","observation_id":"2131f2ea-f922-4644-8027-e9af76d3903d","resolution":{"observed_at":"2026-08-09T15:01:05.160271Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.06769","last_updated":"2025-11-03T00:53:34Z","snapshot_observed_at":"2026-08-07T06:05:27.895209Z","submitted_at":"2024-12-09T18:55:56Z","title":"Training Large Language Models to Reason in a Continuous Latent Space","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.06769","snapshot_observed_at":"2026-08-09T15:01:05.169286Z","title":"Training large language models to reason in a continuous latent space.arXiv preprint arXiv:2412.06769,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.169286Z"},"links":{"cited_paper":"/paper/2412.06769","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:509e7f723ee2f2cf8bd75144d1eab32fdc4b783b9745c689d92ec0ef76389021","observation_id":"a166d50b-2105-4ccf-b3e8-1020969f7731","resolution":{"observed_at":"2026-08-09T15:01:05.169286Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2203.15556","last_updated":"2022-03-29T13:38:03Z","snapshot_observed_at":"2026-07-06T12:54:11.616335Z","submitted_at":"2022-03-29T13:38:03Z","title":"Training Compute-Optimal Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.15556","snapshot_observed_at":"2026-08-09T15:01:05.173729Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.173729Z"},"links":{"cited_paper":"/paper/2203.15556","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:959c10b025bb1f74395e93659dbef18214229920cfaf7ca94370a06de583b43f","observation_id":"f606d417-b5cf-4959-9989-95ebe7855bff","resolution":{"observed_at":"2026-08-09T15:01:05.173729Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1904.09751","last_updated":"2020-02-14T21:56:30Z","snapshot_observed_at":"2026-07-06T07:47:32.745963Z","submitted_at":"2019-04-22T07:17:18Z","title":"The Curious Case of Neural Text Degeneration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.09751","snapshot_observed_at":"2026-08-09T15:01:05.178020Z","title":"The curious case of neural text degeneration.arXiv preprint arXiv:1904.09751,","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.178020Z"},"links":{"cited_paper":"/paper/1904.09751","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:453f3ad95ddab65748c8b84fd8f45aff0196a8646c575ba4c44571eede946a63","observation_id":"a76d1cfb-9435-4986-9376-a79120a6715b","resolution":{"observed_at":"2026-08-09T15:01:05.178020Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.10989","last_updated":"2025-01-24T00:14:55Z","snapshot_observed_at":"2026-07-06T19:33:26.078722Z","submitted_at":"2024-10-14T18:17:01Z","title":"Liger Kernel: Efficient Triton Kernels for LLM Training","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.10989","snapshot_observed_at":"2026-08-09T15:01:05.182144Z","title":"Liger kernel: Efficient triton kernels for llm training.arXiv preprint arXiv:2410.10989,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.182144Z"},"links":{"cited_paper":"/paper/2410.10989","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:a83f18eb879749bea06d5dc41f52de43b002d83dbad36d889a7b7ef2a365b939","observation_id":"d224d447-6fda-448c-9547-b0828a2722bc","resolution":{"observed_at":"2026-08-09T15:01:05.182144Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-09T15:01:05.190581Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.190581Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:cc546dc6d2f76ce21dc08a4c2e889ba4dcf95a97711424bd0a8cc7d622fedc09","observation_id":"f5356ca2-44fa-413e-acdd-0bebac170d18","resolution":{"observed_at":"2026-08-09T15:01:05.190581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.11522","last_updated":"2022-10-20T18:46:31Z","snapshot_observed_at":"2026-07-06T14:08:26.493996Z","submitted_at":"2022-10-20T18:46:31Z","title":"Composing Ensembles of Pre-trained Models via Iterative Consensus","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.11522","snapshot_observed_at":"2026-08-09T15:01:05.202223Z","title":"B., Torralba, A., and Mor- datch, I","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.202223Z"},"links":{"cited_paper":"/paper/2210.11522","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:1f31df8c44cc16b3e0308c85a131046db40ed9c6f6397b26a910cbc08073d615","observation_id":"7b13c84c-e0aa-449b-8573-99527c256095","resolution":{"observed_at":"2026-08-09T15:01:05.202223Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-09T15:01:05.206152Z","title":"Decoupled weight decay regularization.arXiv preprint arXiv:1711.05101,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.206152Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:6815218baf48af3156cb8029f62a4d8b6740718abca8ae8303cebdfe011e8f3b","observation_id":"bf1983ca-20a9-41b7-97fc-f743e1bf083a","resolution":{"observed_at":"2026-08-09T15:01:05.206152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1606.06031","last_updated":"2016-06-20T09:37:17Z","snapshot_observed_at":"2026-08-05T16:27:22.031013Z","submitted_at":"2016-06-20T09:37:17Z","title":"The LAMBADA dataset: Word prediction requiring a broad discourse context","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.06031","snapshot_observed_at":"2026-08-09T15:01:05.214438Z","title":"N., Bernardi, R., Pezzelle, S., Baroni, M., Boleda, G., and Fern´andez, R","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.214438Z"},"links":{"cited_paper":"/paper/1606.06031","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:5c4ca334af6a32ed7d37e1e545fddd409bfbfd412d0b5559b3ee0d67e0f815a9","observation_id":"b763a548-4fe1-4e87-9bef-5fcf155f397c","resolution":{"observed_at":"2026-08-09T15:01:05.214438Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.07524","last_updated":"2024-11-10T20:34:34Z","snapshot_observed_at":"2026-08-05T04:09:52.581952Z","submitted_at":"2024-06-11T17:51:40Z","title":"Simple and Effective Masked Diffusion Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.07524","snapshot_observed_at":"2026-08-09T15:01:05.218562Z","title":"S., Arriola, M., Schiff, Y ., Gokaslan, A., Marro- quin, E., Chiu, J","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.218562Z"},"links":{"cited_paper":"/paper/2406.07524","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:d4070e64637803171f5ef0569336bf5b7680a893fa9b0f4002617b45301d0c1a","observation_id":"b9f09519-df2b-49eb-b759-fe0dc96910dc","resolution":{"observed_at":"2026-08-09T15:01:05.218562Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.08821","last_updated":"2024-12-15T21:20:12Z","snapshot_observed_at":"2026-08-06T10:11:02.511531Z","submitted_at":"2024-12-11T23:36:20Z","title":"Large Concept Models: Language Modeling in a Sentence Representation Space","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.08821","snapshot_observed_at":"2026-08-09T15:01:05.226828Z","title":"R., et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.226828Z"},"links":{"cited_paper":"/paper/2412.08821","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:2f600ecc6271154b0ccee89c41008a11dc842aebd03a7193f0116486d6b88159","observation_id":"bc3ecd11-5c56-4595-8170-ce2a11bbe5f1","resolution":{"observed_at":"2026-08-09T15:01:05.226828Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.01153","last_updated":"2023-08-05T05:48:41Z","snapshot_observed_at":"2026-07-06T15:36:52.977284Z","submitted_at":"2023-06-01T21:23:13Z","title":"Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference","version":2},"cited_work":{"arxiv_id":"2306.01153","doi":null,"metadata_source":"pith","pith_arxiv_id":"2306.01153","snapshot_observed_at":"2026-08-09T15:01:05.339496Z","title":"Diverse and Faithful Knowledge-Grounded Dialogue Generation via Sequential Posterior Inference","venue":"cs.CL","work_id":"e8079b84-2fc7-491c-a313-a956efc6aaaf","year":2023},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.239142Z"},"links":{"cited_paper":"/paper/2306.01153","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:adb8303906803d8be51ff4097618f1a4f76cfc704d4d236c283eac7e73c75bc1","observation_id":"4bc0e6b7-763e-405c-bb20-618690b081e1","resolution":{"observed_at":"2026-08-09T15:01:05.346873Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.05895","last_updated":"2023-10-04T22:00:21Z","snapshot_observed_at":"2026-07-06T13:20:02.689470Z","submitted_at":"2022-06-13T03:41:31Z","title":"Latent Diffusion Energy-Based Model for Interpretable Text Modeling","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.05895","snapshot_observed_at":"2026-08-09T15:01:05.243346Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.243346Z"},"links":{"cited_paper":"/paper/2206.05895","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:6b557d9dc5bc4cca3f53bc631a6bc630dbfdd8346f898164ba60650f0ef4640e","observation_id":"4a02d970-02cd-4efa-a578-c9696ea5a715","resolution":{"observed_at":"2026-08-09T15:01:05.243346Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.02908","last_updated":"2025-04-30T08:39:26Z","snapshot_observed_at":"2026-08-09T12:40:33.547471Z","submitted_at":"2024-09-04T17:48:19Z","title":"Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.02908","snapshot_observed_at":"2026-08-09T15:01:05.247908Z","title":"Masked diffusion models are secretly time- agnostic masked models and exploit inaccurate categori- cal sampling.arXiv preprint arXiv:2409.02908,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.247908Z"},"links":{"cited_paper":"/paper/2409.02908","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:fc4ef9af0cdbb41f6a13b29103d4a1ded6fccdb0c01ca8569535d23d1a7ec2f6","observation_id":"413b2549-8f82-4d19-a993-0faba2be9ff5","resolution":{"observed_at":"2026-08-09T15:01:05.247908Z","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":"2026-08-09T15:01:05.865734Z","title":"We use Adam to update the latent thought vectors without introducing additional inductive bias in the optimization","venue":null,"work_id":"18bda85e-e049-40a4-8f6c-2619a52a361a","year":2024},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.257585Z"},"links":{"citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:ddcc1739af61e5344a08f19aa551c48daff41bd3f458a0806e7e22b78282493e","observation_id":"28c93f00-72ea-4034-8651-ad35208d72cd","resolution":{"observed_at":"2026-08-09T15:01:05.870237Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T15:01:05.822141Z","title":"less-attractive","venue":null,"work_id":"6be75ad9-7bba-4e2b-b48c-a8957f39bccd","year":2005},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.271053Z"},"links":{"citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:5a255bab9b5379f64e1213be882aaf72e290d634fcab7897d15a2220f9fafd26","observation_id":"06185b02-ac01-47be-bc8d-c026240b8f4d","resolution":{"observed_at":"2026-08-09T15:01:05.826985Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T15:01:05.879908Z","title":"We use the GPT-2 tokenizer for OpenWebText, adding a single[EOS] token","venue":null,"work_id":"9fceba73-eb54-4b03-8d62-56d60fdbd100","year":2024},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":256,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.252703Z"},"links":{"citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:779c78cc4b48a30a51d87e2520d679972fe8ed214d5532423580bc8002e70e4e","observation_id":"bfa18bc6-8eb3-43a2-b16e-addaa6761b32","resolution":{"observed_at":"2026-08-09T15:01:05.884256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1702.01806","last_updated":"2017-06-14T01:00:18Z","snapshot_observed_at":"2026-07-06T05:29:01.228177Z","submitted_at":"2017-02-06T22:08:46Z","title":"Beam Search Strategies for Neural Machine Translation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1702.01806","snapshot_observed_at":"2026-08-09T15:01:05.150115Z","title":"and Al-Onaizan, Y","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":1975,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.150115Z"},"links":{"cited_paper":"/paper/1702.01806","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:aeddbf04e4582123876bc4a2af4aad48571c81c17079e5b2af34f91b66aabdcb","observation_id":"97714a98-e2ed-4c5d-93a7-c1b946988718","resolution":{"observed_at":"2026-08-09T15:01:05.150115Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1609.07843","last_updated":"2016-09-26T04:06:13Z","snapshot_observed_at":"2026-07-06T05:12:10.387914Z","submitted_at":"2016-09-26T04:06:13Z","title":"Pointer Sentinel Mixture Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.07843","snapshot_observed_at":"2026-08-09T15:01:05.210379Z","title":"Pointer sentinel mixture models.arXiv preprint arXiv:1609.07843,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":1995,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.210379Z"},"links":{"cited_paper":"/paper/1609.07843","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:144d04dcf96ffb666530f5755d542b9e0176a8cb73cfec9c17b9970a66f89efa","observation_id":"651c72da-0c68-406c-8418-9d71c39ce34a","resolution":{"observed_at":"2026-08-09T15:01:05.210379Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-07-06T08:52:12.656082Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-09T15:01:05.186246Z","title":"B., Chess, B., Child, R., Gray, S., Radford, A., Wu, J., and Amodei, D","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":1999,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.186246Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:584aaf37d463bffbb0853ba4b72ee205df41c6f6d8ada877526331ab10328ba4","observation_id":"f6e34359-9983-46a1-8ec6-0c839a17effa","resolution":{"observed_at":"2026-08-09T15:01:05.186246Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.02311","last_updated":"2022-10-05T06:02:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-05T16:11:45Z","title":"PaLM: Scaling Language Modeling with Pathways","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.02311","snapshot_observed_at":"2026-08-09T15:01:05.129491Z","title":"Palm: Scaling language modeling with pathways.arXiv preprint arXiv:2204.02311,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.129491Z"},"links":{"cited_paper":"/paper/2204.02311","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:69e4604f983952280717342b8ae20b779cd2b437edf9e65feb284baec66d7661","observation_id":"ac13b224-6796-47ec-8b00-7e628bb32c61","resolution":{"observed_at":"2026-08-09T15:01:05.129491Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6114","last_updated":"2022-12-10T21:04:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2013-12-20T20:58:10Z","title":"Auto-Encoding Variational Bayes","version":11},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6114","snapshot_observed_at":"2026-08-09T15:01:05.194331Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2014,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.194331Z"},"links":{"cited_paper":"/paper/1312.6114","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:1e4be76759066ffe8a4b5601b8bebd966f7c16c3dbb371cced2e89e2bff802ea","observation_id":"ec2b4b00-78aa-42f9-b752-1dd13239ac47","resolution":{"observed_at":"2026-08-09T15:01:05.194331Z","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":"2026-08-09T15:01:05.911853Z","title":"Optimus: Organizing sentences via pre-trained modeling of a latent space","venue":null,"work_id":"039b5bd0-55ca-4773-925c-4a2878502696","year":2020},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2015,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.198194Z"},"links":{"citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:7279275f984355f0cf0b8448337c2a0eca8d0a458d28cc03ab5ac00973cab386","observation_id":"8edcab5b-0283-4454-b449-265e5cd9432c","resolution":{"observed_at":"2026-08-09T15:01:05.916810Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T15:01:05.926557Z","title":"B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., et al","venue":null,"work_id":"bc93afe5-6c87-448c-a1f7-3fd06cfc17b6","year":1901},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.119815Z"},"links":{"citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:cd9fade2f96aa35e67075efaac17ae14215d5165bd81b22f21adf2297695a03a","observation_id":"047850c2-b628-4520-9f00-33e4e334b73b","resolution":{"observed_at":"2026-08-09T15:01:05.931326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-09T15:01:05.895880Z","title":"and Durrett, G","venue":null,"work_id":"e3e22eb0-2d0b-44c5-acf9-f710155a26bd","year":2018},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.230956Z"},"links":{"citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:a253f41a0155b99a47ae173c78fc219675169279732a0b92b3fc72290c506941","observation_id":"bce9f314-294a-47ea-807c-68344e126e0e","resolution":{"observed_at":"2026-08-09T15:01:05.901288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1603.08983","last_updated":"2017-02-21T16:21:21Z","snapshot_observed_at":"2026-08-04T14:24:45.814840Z","submitted_at":"2016-03-29T22:09:00Z","title":"Adaptive Computation Time for Recurrent Neural Networks","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1603.08983","snapshot_observed_at":"2026-08-09T15:01:05.155615Z","title":"Adaptive computation time for recurrent neural networks.arXiv preprint arXiv:1603.08983,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.155615Z"},"links":{"cited_paper":"/paper/1603.08983","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:df6b4d7b02792f5c9c6d943474e92f27ba5a9446eaf4af50cad9634a4731c91a","observation_id":"490708b0-aed4-4a40-8c6b-8bd953fe8e88","resolution":{"observed_at":"2026-08-09T15:01:05.155615Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.3005","last_updated":"2014-03-04T18:30:26Z","snapshot_observed_at":"2026-08-05T11:04:54.095339Z","submitted_at":"2013-12-11T00:25:57Z","title":"One Billion Word Benchmark for Measuring Progress in Statistical Language Modeling","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.3005","snapshot_observed_at":"2026-08-09T15:01:05.124950Z","title":"One billion word benchmark for measuring progress in statistical language modeling","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.124950Z"},"links":{"cited_paper":"/paper/1312.3005","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:4f1eaab104092f1278fb6543edf6739dd9ada64b4927ac8e4be1d114bc2a7d28","observation_id":"df42c437-1a43-4ceb-8d7a-1585c04de4e1","resolution":{"observed_at":"2026-08-09T15:01:05.124950Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.05685","last_updated":"2018-05-22T13:06:37Z","snapshot_observed_at":"2026-08-08T21:17:23.383530Z","submitted_at":"2018-04-16T13:55:20Z","title":"A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.05685","snapshot_observed_at":"2026-08-09T15:01:05.139926Z","title":"S., Bui, T., Kim, S., Chang, W., and Goharian, N","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.139926Z"},"links":{"cited_paper":"/paper/1804.05685","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:55df2eb42653488df520e2ad38f964c9853ce6dda76cf7c249ef4686e083d803","observation_id":"8694939a-1715-4d15-aabc-2c4ec6bb743e","resolution":{"observed_at":"2026-08-09T15:01:05.139926Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.15089","last_updated":"2022-12-15T14:27:19Z","snapshot_observed_at":"2026-08-07T07:03:02.158312Z","submitted_at":"2022-11-28T06:08:54Z","title":"Continuous diffusion for categorical data","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.15089","snapshot_observed_at":"2026-08-09T15:01:05.145015Z","title":"H., Doucet, A., Strudel, R., Dyer, C., Durkan, C., et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.145015Z"},"links":{"cited_paper":"/paper/2211.15089","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:9eb82abc57c8b97680c5bd214f420aea9c46b06335ac110338935dc8b678fa40","observation_id":"00a88401-217a-4df4-a926-4e2e282d311f","resolution":{"observed_at":"2026-08-09T15:01:05.145015Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-07T01:45:38.840969Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-09T15:01:05.134171Z","title":"Training verifiers to solve math word problems","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.134171Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:fb2298094ca6fddfbce5548e26e093ca0081c57ec8ced19a41c7aa1075c77376","observation_id":"5be09a95-5478-44ed-8bba-9d3003e7aa58","resolution":{"observed_at":"2026-08-09T15:01:05.134171Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.04329","last_updated":"2025-01-16T08:46:16Z","snapshot_observed_at":"2026-07-06T18:26:42.010940Z","submitted_at":"2024-06-06T17:59:10Z","title":"Simplified and Generalized Masked Diffusion for Discrete Data","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.04329","snapshot_observed_at":"2026-08-09T15:01:05.222724Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.222724Z"},"links":{"cited_paper":"/paper/2406.04329","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:43392ac964ab77492d5451c54d7454ae9d2f898f2de8834143a2f85ec564c466","observation_id":"a644cd8d-c264-4d12-87fc-627414c29743","resolution":{"observed_at":"2026-08-09T15:01:05.222724Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.17432","last_updated":"2023-06-26T22:31:06Z","snapshot_observed_at":"2026-08-08T10:55:08.646488Z","submitted_at":"2022-10-31T16:02:00Z","title":"SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.17432","snapshot_observed_at":"2026-08-09T15:01:05.164553Z","title":"Ssd-lm: Semi- autoregressive simplex-based diffusion language model for text generation and modular control.arXiv preprint arXiv:2210.17432,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-09T15:01:05.164553Z"},"links":{"cited_paper":"/paper/2210.17432","citing_paper":"/paper/2502.01567"},"observation_digest":"sha256:c27ed6d53b9a94fadfd05299ed3d3b56a63c03e5429c86d2e15b77e8fdd4a6df","observation_id":"be0ad11e-0f72-4992-bf5b-e2174b2efc04","resolution":{"observed_at":"2026-08-09T15:01:05.164553Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.01567","last_updated":"2025-06-06T18:40:37Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T14:53:58.786517Z","submitted_at":"2025-02-03T17:50:34Z","title":"Latent Thought Models with Variational Bayes Inference-Time Computation"},"reference_resolution":{"displayed":34,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":25,"verified_exact":1,"verified_fuzzy":8},"total_outbound_references":34},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 4 inbound Pith citation observations for arXiv:2502.01567."}