Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-10T17:26:11.910714Z
Paper Citation Record · LEDGER
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding?
As of 21 August 2026, this Paper Citation Record lists 73 of 73 outbound references and 0 inbound Pith citation observations for arXiv:2608.06972.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
73 of 73 outbound references displayed
- verified exact0
- verified fuzzy42
- unresolved29
- parse uncertain2
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 3d437431-681e-492c-b760-186839dfed9c · outbound
This paper cites Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) , year=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) , year=
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:13.091088Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation dc5e2627-0b39-4858-a3c6-b3f1935944d5 · outbound
This paper cites Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics , pages=
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:13.079764Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b37ec440-13c5-4fb0-8656-09ddc400d975 · outbound
This paper cites 2025 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2025 , eprint=
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:13.069900Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ae260262-65ba-47e6-9437-c485fa9fb3cf · outbound
This paper cites VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? VLM2Vec: Training Vision-Language Models for Massive Multimodal Embedding Tasks
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.602519Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d6a95a4d-b402-454d-bdad-a7f2135d10ff · outbound
This paper cites 2025 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2025 , eprint=
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:13.059589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation dc2d5340-985e-46b7-92ae-b9100cfa2224 · outbound
This paper cites VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.612452Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7fb3e493-60ff-4384-be79-69702d6bc62a · outbound
This paper cites BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.617640Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7fbc9656-8c91-437f-9585-05dabd74a26d · outbound
This paper cites 2024 , address=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2024 , address=
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:13.049150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d61ddcb1-e4cc-498d-88a0-eae3e4089fee · outbound
This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.628335Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9233f4c7-295d-4faa-b330-bbc4e5186548 · outbound
This paper cites Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.634399Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dcfc8665-751d-4737-b4a7-ca2bc7fc8aa8 · outbound
This paper cites Qwen3 Technical Report.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Qwen3 Technical Report
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.640176Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2b132907-f8d2-410c-b7d6-7653b4b96f4d · outbound
This paper cites Qwen3-VL Technical Report.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Qwen3-VL Technical Report
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.646578Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6c28d092-43b4-4f94-91c2-228d81914677 · outbound
This paper cites 2511.00405 , archivePrefix=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2511.00405 , archivePrefix=
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.651192Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0be5e604-3c19-47b2-960a-382f4d9527a2 · outbound
This paper cites 2602.13823 , archivePrefix=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2602.13823 , archivePrefix=
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.655250Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7fffc8c3-df8b-4815-becf-641267b98427 · outbound
This paper cites What you can cram into a single.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? What you can cram into a single
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:13.037206Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation e18b30c2-c425-496b-8c04-3959e16f3888 · outbound
This paper cites an unresolved cited work.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Unresolved cited work
Reference 16
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T17:26:13.024372Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation a69a715d-f547-4f78-9a3b-b29ac74547ad · outbound
This paper cites an unresolved cited work.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T17:26:13.011236Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 9c36ae24-a589-4f48-a3d7-b78cc8eb7075 · outbound
This paper cites Transactions of the Association for Computational Linguistics , volume=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Transactions of the Association for Computational Linguistics , volume=
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.996047Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d3c8dab3-7942-4b50-9896-a2441cdae73d · outbound
This paper cites Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages=
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.981579Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6cfe000f-4db2-437f-b3f6-6caf4a16f5df · outbound
This paper cites Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.969644Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f3ac8587-aa1b-4080-a022-a10195ad9ae6 · outbound
This paper cites Findings of the Association for Computational Linguistics: ACL 2023 , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Findings of the Association for Computational Linguistics: ACL 2023 , pages=
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.957067Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c30a6537-63fd-45e5-876a-433c95725e4f · outbound
This paper cites 2025 , address=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2025 , address=
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.944789Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 609421b7-c284-47ce-b064-67403a35355e · outbound
This paper cites 2025 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2025 , eprint=
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.933523Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d903e2b6-b610-41d6-a05e-bafa2589746b · outbound
This paper cites 2026 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2026 , eprint=
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.921173Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation a7ec1f13-22af-4e95-8d85-7bbbb3b7164c · outbound
This paper cites Proceedings of the First Workshop on Large Language Model Memorization (L2M2) , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the First Workshop on Large Language Model Memorization (L2M2) , pages=
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.909102Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 66a32cd7-29d8-4508-97d4-814d36ae4349 · outbound
This paper cites Training.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Training
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.894345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation f9e05479-c3ac-4b9e-b8dc-c826dda9c493 · outbound
This paper cites Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.882307Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b0ad1d23-64de-4637-bcb1-3d146cf6e6c8 · outbound
This paper cites 2024 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2024 , eprint=
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.870256Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 16135dec-6647-4216-ae5e-a9f618e1a9d2 · outbound
This paper cites Advances in Neural Information Processing Systems , volume=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Advances in Neural Information Processing Systems , volume=
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.858835Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ba16f95c-9db8-42b1-af5e-a45d3db61009 · outbound
This paper cites xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.717175Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 66884b74-5c5b-4a5d-bf49-d0bb536dfee7 · outbound
This paper cites Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.846701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation cd5f9abd-40ee-44d2-8356-853af701fe9b · outbound
This paper cites 2023 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2023 , eprint=
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.832405Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 2826901a-c46f-4c4c-a848-e2324f2b8bcd · outbound
This paper cites MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agents.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agents
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.735151Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4fdd20af-b46f-4f7c-aa4b-2490d0434b51 · outbound
This paper cites 2509.24704 , archivePrefix=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2509.24704 , archivePrefix=
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.739757Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed38b128-f319-4acc-9d8f-363c10505e3c · outbound
This paper cites 2026 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2026 , eprint=
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.819860Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 7f38d49f-5725-4321-82af-599e51f73c8d · outbound
This paper cites 2023 , address=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2023 , address=
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.806775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0994c461-38ba-44a3-bafe-42d328486982 · outbound
This paper cites Findings of the Association for Computational Linguistics: ACL 2024 , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Findings of the Association for Computational Linguistics: ACL 2024 , pages=
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.793764Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 03308778-b5d2-4b33-ab7d-86e2c2751cef · outbound
This paper cites 2025 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2025 , eprint=
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.781211Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 81450917-1643-4620-9c26-7ed8a7763726 · outbound
This paper cites LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.764483Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2bff9aef-661a-4f59-a739-bb04839d09e0 · outbound
This paper cites 2024 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2024 , eprint=
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.769038Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation df769c9a-1ced-4d63-970b-3e382c1630a6 · outbound
This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.773084Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation affff6c1-e348-46b9-81c2-e4cff0d294ec · outbound
This paper cites 2026 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2026 , eprint=
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.761181Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation fabe7f36-f330-4887-b6b4-24d5a6ccbc7d · outbound
This paper cites 2024 , eprint=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2024 , eprint=
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.748166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 4143face-03f4-4deb-ab87-f5c588fc523f · outbound
This paper cites Findings of the Association for Computational Linguistics: EMNLP 2025 , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Findings of the Association for Computational Linguistics: EMNLP 2025 , pages=
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.734981Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 234d1c92-518f-4fd0-bf63-d59946a5e0df · outbound
This paper cites Advances in Neural Information Processing Systems , volume=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Advances in Neural Information Processing Systems , volume=
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.720461Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 137c5645-4e00-44df-9f29-f9b8e9f3561f · outbound
This paper cites Learning Transferable Visual Models From Natural Language Supervision.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Learning Transferable Visual Models From Natural Language Supervision
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.795985Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 978bdfed-1be3-48ab-a286-847bc487ad93 · outbound
This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.707862Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation ceea000a-919c-46c3-ba87-4f7de30548a3 · outbound
This paper cites 2024 , url=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2024 , url=
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.694694Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 6f170ba0-74ba-4f7a-a9c9-69ff0b17cfa5 · outbound
This paper cites an unresolved cited work.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Unresolved cited work
Reference 49
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T17:26:12.680859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation da33016a-e459-41a6-8b69-183fef5fead2 · outbound
This paper cites Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , pages=
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.669024Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 5999e893-bb1b-42a9-8fb7-0041ae31177e · outbound
This paper cites an unresolved cited work.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Unresolved cited work
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.820331Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 059494a7-0ff3-476f-aaee-ec2f4f7c2b27 · outbound
This paper cites 2025 , url=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2025 , url=
Reference 52
- Resolution
- parse uncertain
- no resolver link, observed 2026-08-10T17:26:11.825107Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 61b58fa3-f014-4f11-bf77-f711ab6a691e · outbound
This paper cites Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the IEEE/CVF International Conference on Computer Vision , pages=
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.641433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 735a8cf2-57f3-4e9c-a3f0-108c3b5287e1 · outbound
This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.833434Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f34c628c-af02-435c-a0e3-ba64a62f7f5f · outbound
This paper cites an unresolved cited work.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Unresolved cited work
Reference 55
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T17:26:12.629311Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 79e3672e-ba22-492f-9cc2-e65722866235 · outbound
This paper cites an unresolved cited work.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Unresolved cited work
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.841114Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6dd0eda9-5e0e-4681-bfdd-4649f5e87b23 · outbound
This paper cites an unresolved cited work.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Unresolved cited work
Reference 57
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T17:26:12.610238Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 106c122e-551d-4572-ba7d-4f1e56cd096e · outbound
This paper cites 2022 , address=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2022 , address=
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.597736Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 877c1200-1088-404c-8e25-59c51994a809 · outbound
This paper cites an unresolved cited work.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Unresolved cited work
Reference 59
- Resolution
- parse uncertain
- no resolver link, observed 2026-08-10T17:26:11.851836Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6edebeb6-960f-4a1d-8278-055105ddce6c · outbound
This paper cites 2025 , address=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2025 , address=
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.576176Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation b00c98df-2240-4acb-9f83-0752b7689a61 · outbound
This paper cites 2002 , address=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2002 , address=
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.563064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation c5fcfc5b-3fda-4b07-95a9-9c13ba348f95 · outbound
This paper cites Lawrence and Parikh, Devi , booktitle=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Lawrence and Parikh, Devi , booktitle=
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.550709Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 49521f3e-89e4-405b-84a6-d3e1d6d71b29 · outbound
This paper cites Microsoft.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Microsoft
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.537867Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 978fc593-a293-462e-a8ed-41e1336d453c · outbound
This paper cites Proceedings of the Sixth Workshop on Statistical Machine Translation , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the Sixth Workshop on Statistical Machine Translation , pages=
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.523179Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 929a9e97-e7d0-4d3d-b1c6-270ebc044393 · outbound
This paper cites 2004 , address=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? 2004 , address=
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.875039Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 185aae7f-be0f-4726-960d-7da0107e1e6e · outbound
This paper cites Findings of the Association for Computational Linguistics: EMNLP 2023 , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Findings of the Association for Computational Linguistics: EMNLP 2023 , pages=
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.501617Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation de6dcdb4-4bb6-4e7d-a7c0-1c0228e18b38 · outbound
This paper cites DeCap: Decoding CLIP Latents for Zero-Shot Captioning via Text-Only Training.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? DeCap: Decoding CLIP Latents for Zero-Shot Captioning via Text-Only Training
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.883749Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23c01663-730c-4f84-901e-25dcf7df9ed9 · outbound
This paper cites Implicit Inversion turns.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Implicit Inversion turns
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.488128Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 40e85c06-1a8c-4b62-aa53-4485b6b4ebca · outbound
This paper cites Proceedings of the 37th Annual Allerton Conference on Communication, Control, and Computing , pages=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Proceedings of the 37th Annual Allerton Conference on Communication, Control, and Computing , pages=
Reference 69
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.892259Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 54d82c16-9aa3-41b1-ab42-830c78f7a030 · outbound
This paper cites an unresolved cited work.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Unresolved cited work
Reference 70
- Resolution
- unresolved
- raw_fallback, observed 2026-08-10T17:26:12.466716Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation acfe559d-d714-4ffa-ba50-b1f8b2d2e4af · outbound
This paper cites International Conference on Learning Representations , year=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? International Conference on Learning Representations , year=
Reference 71
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:26:11.902242Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fbfd33d4-60bf-425f-9738-8f7d67c90582 · outbound
This paper cites , journal=.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? , journal=
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.444222Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 360ab4e9-2cef-4673-9bf0-e96ca78c0626 · outbound
This paper cites Text-Only Training for Image Captioning using Noise-Injected.
Generative Embedding Benchmark: How Much Information Survives in a Dense Embedding? Text-Only Training for Image Captioning using Noise-Injected
Reference 73
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-10T17:26:12.430218Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Pith citing papers
No inbound Pith citation observations are available.