Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T17:23:16.335985Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2608.01979.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T17:23:16.335985Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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
52 of 52 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 8f9e7c20-679b-4990-acc4-9dfa85b50310 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages =
Reference 1
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Observation 902236a9-bb7f-4284-b18b-dd8197834550 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Scene Text Visual Question Answering , booktitle =
Reference 2
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Observation d58060be-1622-4ec4-9d08-57a113189909 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs 2024 , howpublished =
Reference 3
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Observation 4a9290b9-0fb4-441d-9ce0-c111292a5b09 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs 2019 International Conference on Document Analysis and Recognition (ICDAR) , pages =
Reference 4
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Observation f71cb57c-2418-4be8-bd2f-f9b793d1fa09 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Unresolved cited work
Reference 5
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Observation 00536d71-db08-43c7-b9c9-9d97b1c892fa · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the AAAI Conference on Artificial Intelligence , volume=
Reference 6
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Observation f6b5f369-d12e-4297-b3e7-68f9c8070272 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs G$^2$TR: Generation-Guided Visual Token Reduction for Separate-Encoder Unified Multimodal Models
Reference 7
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Observation 009147b5-26c1-4b3b-a45b-a792df01a27e · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision , pages =
Reference 8
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Observation 101befc7-c6f3-4d30-ac98-2129812b6496 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Findings of the Association for Computational Linguistics: ACL 2022 , pages =
Reference 9
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Observation 37191fb7-bd59-421d-8d64-0cfcecf53cc3 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Computer Vision -- ECCV 2020 , pages =
Reference 10
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Observation 80f70ecc-109d-4d29-992a-4f3f815c1239 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Science China Information Sciences , volume =
Reference 11
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Observation e7b92d26-7f26-4394-a719-9e30eebff866 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning
Reference 12
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Observation b96a303f-5579-4ef9-8d47-82a7f6e9de61 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Computer Vision -- ECCV 2024 , pages =
Reference 13
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Observation af204b94-4cd4-4e3f-91de-fc9cdbedc8e3 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding
Reference 14
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Observation 0ec51c70-979c-4de8-8738-41e0dc52ca0a · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Findings of the Association for Computational Linguistics: EMNLP 2023 , pages =
Reference 15
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Observation 9d757787-0fac-4949-865e-d84af149f26f · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Findings of the Association for Computational Linguistics: EMNLP 2024 , pages =
Reference 16
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Observation 1057ed13-8c63-4fe5-bc3e-5a8c6f9bc3f3 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages =
Reference 17
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Observation b6c0bb62-f2d4-4b3f-9b37-ce1c836ab4cb · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the AAAI Conference on Artificial Intelligence , volume =
Reference 18
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Observation a0c06f8c-e487-4dc6-a8de-b898dad33249 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Qwen3-VL Technical Report
Reference 19
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Observation 7b19cb67-6e49-4047-b027-beb260698c80 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
Reference 20
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Observation 2b9d2b5a-5ac7-45c6-a90f-6207f9b2b115 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages =
Reference 21
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Observation 4285a41b-b788-473e-afb3-6cb721ca6610 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Computer Vision -- ECCV 2024 , pages =
Reference 22
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Observation 3ced6690-2b55-486a-885a-e14346f1154e · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs PyramidDrop: Accelerating Your Large Vision-Language Models via Pyramid Visual Redundancy Reduction
Reference 23
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Observation 91162634-3a3d-4b23-b02a-9c759a58f3bf · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs and Okuno, Tomoyuki and Nakata, Yohei and Keutzer, Kurt and Zhang, Shanghang , title =
Reference 24
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Observation f7debecc-3b70-4cb7-a942-d6317034d828 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs The Fourteenth International Conference on Learning Representations , year =
Reference 25
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Observation e1349d50-b950-4aea-b4fa-c036eb7f4d40 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs arXiv preprint arXiv:2509.24837 , year =
Reference 26
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Observation ed74f993-a7ac-4ecf-b0fa-3ade1ecc9fce · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs The Thirty-Ninth Annual Conference on Neural Information Processing Systems , year =
Reference 27
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Observation a1e8daec-0ad8-42fc-91ed-42ffb196d330 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the IEEE/CVF International Conference on Computer Vision , pages =
Reference 28
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Observation 63f807ed-abae-4d20-bf38-3bea1f3aeaef · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the Computer Vision and Pattern Recognition Conference , pages =
Reference 29
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Observation 56ac6f38-9978-46a6-aff6-7293d6157dac · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Multi-Stage Vision Token Dropping: Towards Efficient Multimodal Large Language Model
Reference 30
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Observation f0aad939-9553-427f-ba33-a8fd57dc7134 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages =
Reference 31
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Observation daba2d85-d58d-46fb-a2a7-a524b9a00b16 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the AAAI Conference on Artificial Intelligence , volume =
Reference 32
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Observation d5e0c4ff-4087-41e2-a3a7-3d7d5f21d778 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the AAAI Conference on Artificial Intelligence , volume =
Reference 33
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Observation e9991464-cee1-44fd-af42-393f698b63f7 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the Computer Vision and Pattern Recognition Conference , pages =
Reference 34
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Observation 924ecc97-c796-401d-83cf-d8baec19dfba · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs FocusLLaVA: A Coarse-to-Fine Approach for Efficient and Effective Visual Token Compression
Reference 35
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Observation d8689bff-a83a-4786-8b6c-a56d3bf64478 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs The Fourteenth International Conference on Learning Representations , year =
Reference 36
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Observation 5bfb6a66-56d3-4d8a-a9be-46a4c9ea2904 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs arXiv preprint arXiv:2507.20630 , year =
Reference 37
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Observation 42e4f99b-8179-413f-96f8-ca3031ac7aab · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs and Piergiovanni, A
Reference 38
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Observation 31b74e81-d549-48df-82dc-2bcc068b7f2f · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs The Eleventh International Conference on Learning Representations , year =
Reference 39
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Observation 545396b8-e7c3-40e4-8bfa-7fdc8d6a834d · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages =
Reference 40
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Observation 60ac6df1-7e3a-44f3-9d55-e4376775bb35 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Adaptive Computation Time for Recurrent Neural Networks
Reference 41
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Observation b719c8b9-dc49-4e0d-9ad7-f2b85b8abc67 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs and Grauman, Kristen and Feris, Rogerio , title =
Reference 42
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Observation a88c8932-9a4f-47ed-8f12-9fbe2c9227a8 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs , title =
Reference 43
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Observation 680e4685-233e-498f-9200-c744d39e8287 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Advances in Neural Information Processing Systems , volume =
Reference 44
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Observation 3ec376e1-657d-4e7d-b78a-271032e5e60d · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Advances in Neural Information Processing Systems , volume =
Reference 45
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Observation 116a78d3-95b8-4046-b8d6-70280056484c · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages =
Reference 46
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Observation 13f46ad9-817f-476f-9ff8-8c2ddc5b1170 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages =
Reference 47
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Observation 754eb6c5-b16d-4d12-9e8d-e0bf403b5466 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs and Tay, Yi and Metzler, Donald , title =
Reference 48
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Observation f36d8354-964a-448f-a822-848958918f06 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Reference 49
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Observation b2336bbc-b73c-4319-a773-c473372379d0 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , pages =
Reference 50
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Observation a1e4b0bf-e2ca-4828-9e18-74412de29071 · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs RoboVQA: Multimodal Long-Horizon Reasoning for Robotics
Reference 51
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Observation b4063264-a7af-40be-af5e-44770881646b · outbound
ET-Prune: Evidence-Aware Dynamic Budgeting for Visual Token Pruning in Text-Rich MLLMs MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
Reference 52
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No inbound Pith citation observations are available.