{"as_of":"2026-08-08T17:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:65cd3c56ae2c853de4c2466a2d766fbed91ac33bcf7f74410b15f75f28564175","coverage":[{"denominator":52,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":52,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-27T23:27:57.034391Z","state":"measured"},{"denominator":52,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":52,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2606.06273/citation-record","integrity":"/paper/2606.06273/integrity","json":"/paper/2606.06273/citation-record.json","paper":"/paper/2606.06273"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T23:27:57.034391Z","title":"Deep joint source- channel coding for wireless image transmission,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:9f8a37ad24e235dcb9d589cab686d5bbabf21183165e4fd83bdd6e7ca5a62630","observation_id":"2ad9f1be-d893-44c2-a516-4213343f39bf","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Alternate learning- based SNR-adaptive sparse semantic visual transmission,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:95b004d6b649a8c3a3176d0b43f434e321e0467c80d1b951651d59d672182c6c","observation_id":"b62a73c2-c223-44fd-abcf-92c706ec1e24","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"DeepMA: End-to-end deep multiple access for wireless image transmission in semantic communication,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:f41c4ec42d75094966e12555b2078985034974043e32c72b8879edba085daaea","observation_id":"5f16ee57-b7dc-4639-8082-fa5c7f6b7f19","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Lightweight joint source-channel coding for semantic communications,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:883b5877f32e899eae152c2466396f1aa256212a2f5646f195bd850aa08380d6","observation_id":"4ac95f3b-4d38-4ecf-a2d6-124a66f68843","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Language modeling is compression,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:e861cb8b3fbdabace743681aecd6f6a84fe088091bd87772c39221d4d79db12d","observation_id":"2c99e64d-aeeb-49f8-972d-835787c4f250","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.09937","last_updated":"2024-08-19T13:55:42Z","snapshot_observed_at":"2026-08-06T17:08:05.625315Z","submitted_at":"2024-04-15T17:03:41Z","title":"Compression Represents Intelligence Linearly","version":2},"cited_work":{"arxiv_id":"2404.09937","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2404.09937","snapshot_observed_at":"2026-07-02T22:17:25.634233Z","title":"Compres- sion represents intelligence linearly.arXiv preprint arXiv:2404.09937","venue":null,"work_id":"5d1e6c8b-d47b-4996-9f0f-b7c08a38751a","year":2024},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"cited_paper":"/paper/2404.09937","citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:8dc95c783c170ae0b089c526352fbc4197cb2f1a4dd7e6c6e879c5eeb06854dd","observation_id":"e98a9ef4-92f4-4aec-9f5b-9624aead304b","resolution":{"observed_at":"2026-07-02T15:47:06.427612Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T23:27:57.034391Z","title":"Lossless data compression by large models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:715bbbf9e083848f1d7e81e3a8eba2cd9d3782e7e13e8fba2f248aa63db97c6e","observation_id":"ffe504ec-d3da-4159-ae42-242299a233c8","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.16163","last_updated":"2025-02-22T09:36:03Z","snapshot_observed_at":"2026-08-07T17:56:42.224641Z","submitted_at":"2025-02-22T09:36:03Z","title":"Large Language Model for Lossless Image Compression with Visual Prompts","version":1},"cited_work":{"arxiv_id":"2502.16163","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.16163","snapshot_observed_at":"2026-07-10T11:07:01.941036Z","title":"Large Language Model for Lossless Image Compression with Visual Prompts","venue":"eess.IV","work_id":"9948fd08-fa47-45b7-8abe-5f4270488e45","year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"cited_paper":"/paper/2502.16163","citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:6576033a7bc8319ff56c2ee8ccf83de497b2a0c2a46a64588990f992e2b35ae7","observation_id":"82eb44c0-7b2e-4232-8b37-f3c91122cef9","resolution":{"observed_at":"2026-07-02T15:47:06.430215Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T23:27:57.034391Z","title":"Large language models for lossless image compression: Next-pixel prediction in language space is all you need,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:3ba14fa95eab3faec713c8162d3176860bc183cf3c61e7068a44394478603959","observation_id":"afee12a6-001a-4993-a040-bfb30f778e4d","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Separate source channel coding is still what you need: An LLM-based rethinking,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:b2e53cfd1acd443d4c15912b234f329cf6176cee288e96e902f9bd933590e797","observation_id":"6d4e892a-c75c-47da-b0e7-760ee0ae14fc","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Error correction code transformer,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:4f983277aae71a5919b15449c4c9c7064ea07b78ba9ae11f2a2c7266b8f3170f","observation_id":"7c1053a7-802c-44a3-b904-8ad8ffbe105b","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"A foundation model for error correction codes,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:69ba60fa251f42f01cf81bf1b5e65f9508913d506875c1a00d87f801a0b0e961","observation_id":"a4fb3644-dbe7-438d-b84a-93405daf13aa","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"U-shaped error correction code transform- ers,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:fc4211500333bc7a9b6accf93c7c3abbea38091b6d9577dd33f0af346352bf67","observation_id":"e723dfe2-cdf0-4e54-a80e-7e9b4ac745bd","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Self- critical alternate learning-based semantic broadcast communication,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:4c30d59aa27b44678b34eeb6d9e10e5df35fd5a783f077e6387a3425d40f3e30","observation_id":"e63077e8-5eb9-4f72-8777-316a9015f378","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Semantic communications using foundation models: Design approaches and open issues,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:c45c472be629d4b06770aa39ac398c56637c25e3d5e8cd0f09e3ebfadcea3c32","observation_id":"4e14c722-5b3a-48b5-b40e-914c8d66f1f9","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Large AI model-based semantic communications,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:90613002d6c571899d384572ac7acfcfc0c45b087c8879ba1b858350d39d7060","observation_id":"055154ec-464e-4a9c-8b80-948fa9896696","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Generative AI-driven semantic communication networks: Architecture, technologies and applications,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:23558b6cf3ed5e1ecdc8cb3f458cfb930c5cb5ee20f067568fb72f48f4772181","observation_id":"189d8450-00f5-41f8-baad-01c0d382070d","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Large AI model empowered multimodal semantic communications,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:647a80ab8e64cc3b01018cfde4dfcbb2ec9a1adc466a1f20f1e78f8a8032504a","observation_id":"14d86e10-b68f-4b7c-9af4-fc4b134aaf1b","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.03112","last_updated":"2026-06-18T07:06:52Z","snapshot_observed_at":"2026-08-06T16:39:05.098401Z","submitted_at":"2026-01-06T15:42:45Z","title":"DiT-JSCC: Rethinking Deep JSCC with Diffusion Transformers and Semantic Representations","version":2},"cited_work":{"arxiv_id":"2601.03112","doi":null,"metadata_source":"pith","pith_arxiv_id":"2601.03112","snapshot_observed_at":"2026-07-02T15:47:06.420541Z","title":"DiT-JSCC: Rethinking Deep JSCC with Diffusion Transformers and Semantic Representations","venue":"eess.IV","work_id":"d3c56b82-8975-4d20-a7fe-5715d466b892","year":2026},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"cited_paper":"/paper/2601.03112","citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:b28dba0fe244a4ac36e3e3e4e837691595629f45b42ed0c5c47e6244c02b200c","observation_id":"aae5ef50-3d65-4104-ad43-137bbe9f9152","resolution":{"observed_at":"2026-07-02T15:47:06.422031Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T23:27:57.034391Z","title":"Low-density parity-check codes,","venue":null,"work_id":null,"year":1962},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:c56c52ddf04deaf7a6b98413032bda868753e61e2c2d69ed9c5f223f3b75ba36","observation_id":"65bac47c-8298-4874-a5d2-9ce79033117d","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Channel polarization: A method for constructing capacity- achieving codes for symmetric binary-input memoryless channels,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:4c49a1a2714a0a1ce1b736e9007491492dbfa6be43a3df3fd04fd8991732f692","observation_id":"463bfa81-92d5-42ff-8a7c-4b5c4d5900a1","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Deep learning methods for improved decoding of linear codes,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:504c18202e848cfa3e9984faa487b315464bcb7bf86706693ead435322720f5d","observation_id":"e6d9e85c-79b0-4d04-b34f-8ed71a4cc44b","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Context-based, adaptive, lossless image coding,","venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:b5419b4c55fbf7a851afd6c157b6eba1e59b3ea90d5bc1d86ac313b7d618d29b","observation_id":"eb4f3031-c211-4092-9cce-c6c9d91ffc98","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"The LOCO-I lossless image compression algorithm: Principles and standardization into JPEG- LS,","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:7efa98ad8b22ee90353497f240ccfadd3bdd01d9ffe6628bf39708d3b3931e83","observation_id":"bd81dbfa-fdcf-4ce4-b009-abf77ff8e966","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"JPEG XL next-generation image com- pression architecture and coding tools,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:1f52450db386d61f737aeec67ec72410541fc741a419db054da0628475809c8b","observation_id":"4e82207c-b4c5-483d-a391-86870c23e567","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Practical full resolution learned lossless image compression,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:c1a6b1b5802d0b7e4ba2372bb98c8c7ac2ee0edb5937da463fbd036a8858726a","observation_id":"094d0b3c-e855-42d4-a8dc-d10f4668bd3e","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Integer discrete flows and lossless compression,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:51fa1fab0e9d8c4f48eb330d0a8fc805125718c247a16b2881e1b719090e1c07","observation_id":"f015457c-df4a-4181-b998-3e31b9a653db","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"PILC: Practical image lossless compression with an end-to-end GPU oriented neural framework,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:75f24ee211971cefde221be901352f26683ba941abd2cea12bb6c246ba46fe22","observation_id":"0fad5be9-9980-4a1f-bda7-ac163c433b9d","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Learned lossless image compression based on bit plane slicing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:227cec81c03144b16a87bf253628a9539c418c2eff2274b33d6507a32fb80f00","observation_id":"39c95469-0f2d-44cb-922f-9607363dd7ad","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"CALLIC: Content adaptive learning for lossless image compression,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:5cb891484b7fcdb277e79204d0267704bfb2460392d4edc83b9131e24436e344","observation_id":"525d3e06-651c-4d83-b420-67f26c7d6c29","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Deep lossy plus residual coding for lossless and near-lossless image compression,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:fdd29db60606eb248afcdcd949d7c5e027dbff89301ac39f76b2a83689705fa0","observation_id":"88a6b8ba-22b5-481f-a487-c85dd9a41aa5","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Fitted neural lossless image compres- sion,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:2f1c34da47954fcf63d3a8865d23315a6a8b9da2da095735f2ee92075add6b1c","observation_id":"971df6c6-410d-4e88-b24a-255d6092853c","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Generalized Kraft inequality and arithmetic coding,","venue":null,"work_id":null,"year":1976},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:b95ecff258e7545100528c531d3cd39b190aa6af948d1068b7f7d70decedc12f","observation_id":"baccc29e-f84b-4a60-8024-af2ff25a676f","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Arithmetic coding for data compression,","venue":null,"work_id":null,"year":1987},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:5958cac426a0d8bf2d50733ffa2b1f145732570f13fbd80018c7846093fe616c","observation_id":"0b437aad-7eeb-4de9-be13-8588835db61e","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Arithmetic coding for data compression,","venue":null,"work_id":null,"year":1994},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:83c38bf6bc41398cb04dc5413c3468d05a8191beb805a2883eb1f0240dc7e83d","observation_id":"290b8f3d-b3ac-4b5a-b4db-7c21c7a95083","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.04050","last_updated":"2023-06-26T18:03:12Z","snapshot_observed_at":"2026-07-31T06:49:30.094166Z","submitted_at":"2023-06-06T22:42:00Z","title":"LLMZip: Lossless Text Compression using Large Language Models","version":2},"cited_work":{"arxiv_id":"2306.04050","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2306.04050","snapshot_observed_at":"2026-07-04T09:59:44.821549Z","title":"Llmzip: Lossless text compression using large language models","venue":null,"work_id":"0f7dd525-bd90-401f-954b-510af707beb6","year":2023},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"cited_paper":"/paper/2306.04050","citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:bc0fb8901e12ae18349057b8d1d952ae38e8119ebb04f042582ee7882f6bc260","observation_id":"c0ab4fe2-82ef-4884-afc7-3aa89e975ce2","resolution":{"observed_at":"2026-07-02T15:47:06.424884Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-06-27T23:27:57.034391Z","title":"Generative pretraining from pixels,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:754d4767d44598e1a54d9dbe7caaf88ae54ef81df56069a5c930a2c6217fce0b","observation_id":"2db9f3ba-8f32-4182-bb7e-432894b5a968","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Structured denoising diffusion models in discrete state-spaces,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:e97c4708579009deb742914df97e304f7eb6ecf84cda768138efba11b79df0f0","observation_id":"26a5a4fc-00d0-4ca9-ae8e-f1451427e296","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Diffusion-LM improves controllable text generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:f66d947f4efe61b58f0e14ca72840cbf521c352880e27296f51e774d75b40381","observation_id":"fcd6f72c-5591-4cbc-b5a5-07d0d52e2a09","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Simple and effective masked diffusion language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:693ae284d4e0785fbbee4d346b87a7dfbc224b5edf8d23de94ad30eabd3d2a7e","observation_id":"bc4a36c2-1dd5-4ed1-b5f8-2ade4acc4816","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Block diffusion: Interpolating between autoregressive and diffusion language models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:1c85b418ba6a2016c9aec133c349fe174eaf114fd27834f452aefddd0c9269d2","observation_id":"02d1fab7-8455-42f0-bb0f-fcd881b05ac5","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Large language diffusion models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:27ef40ae822f90b42b1b534824ca9067ec280f5565ea2dfd0489124c2cfd04c1","observation_id":"236390a4-85af-46dc-8222-3d09ef6e7195","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Scaling diffusion language models via adaptation from autoregressive models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:38a65c3350bc9cf0ea369e9f1b13639adf6817dd706e15fcc9b6453cae84a2ab","observation_id":"6746c569-de02-404d-baf5-b8a1ebe99151","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"MaskGIT: Masked generative image transformer,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:57d19624e304280741b0ae4d6b17ee575a53ef4daf98bbccd8d3a1c8fa0ebdfb","observation_id":"8ee2a4e1-176e-44e8-b1f0-02618520aee4","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Halton scheduler for masked generative image transformer,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:30c6a5fe2e764e7904d36a5ab1ddfa58922e1edbfcbda608ffabc59171a3e5fd","observation_id":"94421d46-b18b-4234-9055-3e14d232b243","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":null,"venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:812db5dfa6a621a567832553f91f07023385788592b38175f2e18a53b24ef6e6","observation_id":"1857367f-82a0-41b0-9510-5002e56e6428","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Algorithm 247: Radical-inverse quasi- random point sequence,","venue":null,"work_id":null,"year":1964},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:f659d7e8bc3d6d9a7b691a96ab461c061a1bbb2a046192688b9ddad76964ca12","observation_id":"50ad9b6d-8cc1-48e0-9395-86e1bf405415","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"On calibration of modern neural networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:c731eae94baafdff7eaff2d4f3790c2df425c160d87d48731dacbaa431d95f37","observation_id":"50a49158-a76a-4a19-b651-20ef097b347f","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Learning multiple layers of features from tiny images,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:ca4a9917631dc8f667653c3e9b40d8cde2da386ad6dc35e23b955c7a3930b0eb","observation_id":"6c845f6b-d9b9-4b9c-8164-29bb32c9d749","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"NTIRE 2017 challenge on single image super-resolution: Dataset and study,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:5b027f5e203a4d666aa18b851f666fd62e2234b635b05b52ef5b6250b993737f","observation_id":"6b947436-caa5-4ed2-9a0d-44a608994451","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Kodak lossless true color image suite,","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:34914520fb48d64bea0c672db041535210389dc931a1d325996663d603050897","observation_id":"0defbaff-6250-436a-bfec-7dae675c7a66","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","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":"2026-06-27T23:27:57.034391Z","title":"Block- based adaptive vector lifting schemes for multichannel image coding,","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-06-27T23:27:57.034391Z"},"links":{"citing_paper":"/paper/2606.06273"},"observation_digest":"sha256:ee6b7aa47d355718cbdf56622102df577d04c3c67e27f3c6f0e4618dd6b16887","observation_id":"c7d6aba5-661e-47e2-bd24-ef9aa6745fd0","resolution":{"observed_at":"2026-06-27T23:27:57.034391Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2606.06273","last_updated":"2026-06-04T15:14:31Z","latest_version":1,"primary_category":"cs.IT","snapshot_observed_at":"2026-08-07T16:10:54.746687Z","submitted_at":"2026-06-04T15:14:31Z","title":"Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission"},"reference_resolution":{"displayed":52,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":48,"verified_exact":4,"verified_fuzzy":0},"total_outbound_references":52},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2606.06273."}