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Paper Citation Record · LEDGER

Thinking with Anchors: Grounded and Efficient Document Reasoning

As of 8 August 2026, this Paper Citation Record lists 100 of 192 outbound references and 0 inbound Pith citation observations for arXiv:2608.04424.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.04424 v1

Coverage vector

measured 100 of 192 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:24:54.575516Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

100 of 192 outbound references displayed

  • verified exact9
  • verified fuzzy0
  • unresolved91
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 079bbeaa-c242-4e64-a758-45ab268f868c · outbound

This paper cites Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models.

Thinking with Anchors: Grounded and Efficient Document Reasoning Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models

Reference 1

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source=pdf_text observed=2026-08-07T00:24:48.228681Z digest=sha256:7b8753577b83ec2682fbf75499dc8e89f1467f0f4a4bb00c9affa897fb23f9cd

Observation b87716f9-dcfd-40a0-af94-57f6162a546d · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Thinking with Anchors: Grounded and Efficient Document Reasoning Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2

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source=pdf_text observed=2026-08-07T00:24:48.289120Z digest=sha256:a69e5f765a89cf35e7a840d82a4606f7eeb2d34578fd15c1f1da335bae4b2d5c

Observation 939ed157-f89f-4cd0-a570-61b9b2513a3d · outbound

This paper cites Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads.

Thinking with Anchors: Grounded and Efficient Document Reasoning Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Reference 3

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source=pdf_text observed=2026-08-07T00:24:48.396919Z digest=sha256:8b29a712bc198a12c99547a694853382bfe34f1a47e10dae18ec2555fb3502f6

Observation 79d40e6c-d860-48e4-b6e4-e7da9681bfde · outbound

This paper cites End-to-end object detection with transformers.

Thinking with Anchors: Grounded and Efficient Document Reasoning End-to-end object detection with transformers

Reference 4

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source=pdf_text observed=2026-08-07T00:24:48.482296Z digest=sha256:f262fb55142fed38171c69501b1e06c60723ee6f556004cd4cb70ff14ad07c1a

Observation 6930afa3-d89e-458e-9e14-2c151e7cf105 · outbound

This paper cites SAM 3: Segment Anything with Concepts.

Thinking with Anchors: Grounded and Efficient Document Reasoning SAM 3: Segment Anything with Concepts

Reference 5

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source=pdf_text observed=2026-08-07T00:24:48.560859Z digest=sha256:2172571b024805bc1093cda6896b2b648e2a5832851f3b3f137dcc1899c7f51d

Observation 89998913-626c-4f99-961b-318e76ce9386 · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 6

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source=pdf_text observed=2026-08-07T00:24:48.668507Z digest=sha256:3a86e42144da4c774f6503f13e58a1a68f626d4e0b3733b6d9fb0fd199d7d0ef

Observation 0320ae71-272c-496b-a799-9bf9b37f32e5 · outbound

This paper cites Chaudhuri (ed.).Digital Document Processing: Major Directions and Recent Advances.

Thinking with Anchors: Grounded and Efficient Document Reasoning Chaudhuri (ed.).Digital Document Processing: Major Directions and Recent Advances

Reference 7

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T00:24:48.786909Z digest=sha256:ac136c9537083e4f621b17bcbe2e40a81643c0d4dea4f511bc6a3cf60f89ce94

Observation e98c58e3-c3ae-46d7-a90a-f9730d9cc96c · outbound

This paper cites Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic.

Thinking with Anchors: Grounded and Efficient Document Reasoning Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic

Reference 8

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source=pdf_text observed=2026-08-07T00:24:48.866113Z digest=sha256:a7125303e5107987652e7c09653c7ec4631837bbd5006a933c34fe37df76e6be

Observation 4c6f4780-02ba-4b86-a7b7-c98724fa0f1b · outbound

This paper cites Fleet, and Geoffrey Hinton.

Thinking with Anchors: Grounded and Efficient Document Reasoning Fleet, and Geoffrey Hinton

Reference 9

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source=pdf_text observed=2026-08-07T00:24:48.955959Z digest=sha256:5c9db0ba1c2d3257c3998f8d9d66c24514aaecb9dc3e5b466b4d8fe43d6ffcde

Observation 551169d8-3bc3-46a9-a6e6-38a9398158c3 · outbound

This paper cites Graph-based document structure analysis.

Thinking with Anchors: Grounded and Efficient Document Reasoning Graph-based document structure analysis

Reference 10

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source=pdf_text observed=2026-08-07T00:24:49.064174Z digest=sha256:29dcf6ed3c55b351906a3b29699d05f0bbf4abc71404ed09a96f0ee84161f438

Observation 5fae058d-1240-417b-8472-f9b57fc96786 · outbound

This paper cites M6doc: A large-scale multi-format, multi-type, multi-layout, multi-language, multi-annotation category dataset for modern document layout analysis.

Thinking with Anchors: Grounded and Efficient Document Reasoning M6doc: A large-scale multi-format, multi-type, multi-layout, multi-language, multi-annotation category dataset for modern document layout analysis

Reference 11

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source=pdf_text observed=2026-08-07T00:24:49.180375Z digest=sha256:9ae049715d83bf855dfad3f3f28c570e4d39f765309095b4b8f3fc0f12bb141c

Observation 533c0f0d-e1e9-40c4-a446-fb04145dc1f4 · outbound

This paper cites M 6Doc: A large-scale multi-format, multi-type, multi-layout, multi-language, multi-annotation category dataset for modern document layout analysis.

Thinking with Anchors: Grounded and Efficient Document Reasoning M 6Doc: A large-scale multi-format, multi-type, multi-layout, multi-language, multi-annotation category dataset for modern document layout analysis

Reference 12

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source=pdf_text observed=2026-08-07T00:24:49.262984Z digest=sha256:4868fbfa528856291c739d647611d0a963cf0a3498caad1b2600ee713f4ca96e

Observation 0a506b45-5748-43c7-b9b4-33eb887f46a4 · outbound

This paper cites SDAR: A synergistic diffusion-autoregression paradigm for scalable sequence generation.arXiv preprint arXiv:2510.06303, 2025.

Thinking with Anchors: Grounded and Efficient Document Reasoning SDAR: A synergistic diffusion-autoregression paradigm for scalable sequence generation.arXiv preprint arXiv:2510.06303, 2025

Reference 13

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source=pdf_text observed=2026-08-07T00:24:49.348761Z digest=sha256:4150c8db5b64348f07e204c8f3fced3d62a72126cb84434354ff0780928f7950

Observation 5dca52eb-1408-4797-bab4-6b0762f268f3 · outbound

This paper cites Diachronic Document Dataset for Semantic Layout Analysis.

Thinking with Anchors: Grounded and Efficient Document Reasoning Diachronic Document Dataset for Semantic Layout Analysis

Reference 14

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source=pdf_text observed=2026-08-07T00:24:49.478969Z digest=sha256:7ebe4559f8a1a8e2b36d082182df5de343c585e09a9e910f5daae277e3f75c40

Observation ee3bbd3d-77a1-44c4-bc5b-5248a3b56d0c · outbound

This paper cites Molmo and pixmo: Open weights and open data for state-of- the-art vision-language models.

Thinking with Anchors: Grounded and Efficient Document Reasoning Molmo and pixmo: Open weights and open data for state-of- the-art vision-language models

Reference 15

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source=pdf_text observed=2026-08-07T00:24:49.678461Z digest=sha256:dd43066be07788f81399820b886c12a7fa5cf182e31d6f66b235313e6d634a0d

Observation 1fc0bc2d-daf6-4fe0-acbe-d41226c90871 · outbound

This paper cites HoloCount: A Holistic Visual Counting Benchmark for MLLMs.

Thinking with Anchors: Grounded and Efficient Document Reasoning HoloCount: A Holistic Visual Counting Benchmark for MLLMs

Reference 17

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source=pdf_text observed=2026-08-07T00:24:49.859133Z digest=sha256:ef4affcbcae95f61f465977f31a480d955c17ed5a6baa885c6f3319417670608

Observation 2fdd163c-3a6d-4f70-830e-8d288f4cb57d · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 18

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source=pdf_text observed=2026-08-07T00:24:49.934247Z digest=sha256:3103873a25b2438df88a7f81e7a74a9fa707137b97b128af2680732b15ef8727

Observation 9d869abe-5c80-455a-aa68-321478e61d8b · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

Thinking with Anchors: Grounded and Efficient Document Reasoning YOLOX: Exceeding YOLO Series in 2021

Reference 19

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source=pdf_text observed=2026-08-07T00:24:50.023097Z digest=sha256:cc9b6c84045d4bd457f43a2f8805256fececa5bd66910b41416abf38901dce1a

Observation 6f503460-1747-43d4-b41f-fc41ecfe8519 · outbound

This paper cites Better & faster large language models via multi-token prediction.

Thinking with Anchors: Grounded and Efficient Document Reasoning Better & faster large language models via multi-token prediction

Reference 20

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source=pdf_text observed=2026-08-07T00:24:50.131818Z digest=sha256:f37004b93ea37b9f99996c6a625b9ae4a9dbaf080a55edb689f46622ea2bef09

Observation d863bb68-d4ae-4d07-ae0b-474357c11d1f · outbound

This paper cites Morariu, Handong Zhao, Rajiv Jain, Nikolaos Barmpalios, Ani Nenkova, and Tong Sun.

Thinking with Anchors: Grounded and Efficient Document Reasoning Morariu, Handong Zhao, Rajiv Jain, Nikolaos Barmpalios, Ani Nenkova, and Tong Sun

Reference 21

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source=pdf_text observed=2026-08-07T00:24:50.211249Z digest=sha256:2b7141a06744370bcddacdae82560a637a004048dded5c3e09d7ca9773602a56

Observation 7bf1e27a-3c7c-41db-a7b8-3332fbfef14c · outbound

This paper cites ADoPD: A large-scale document page decomposition dataset.

Thinking with Anchors: Grounded and Efficient Document Reasoning ADoPD: A large-scale document page decomposition dataset

Reference 22

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source=pdf_text observed=2026-08-07T00:24:50.284619Z digest=sha256:5a954bd51b6a77850b0f750c7cf26d512e0724e78a2b42c461853fc0cfbfbde5

Observation 5f9b4020-4b7a-4051-b975-a4c2e83b929a · outbound

This paper cites Visual programming: Compositional visual reasoning without training.

Thinking with Anchors: Grounded and Efficient Document Reasoning Visual programming: Compositional visual reasoning without training

Reference 23

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source=pdf_text observed=2026-08-07T00:24:50.339968Z digest=sha256:46a77a6e845ce6523620ee5615798230830bbffd2576e3b1bc56c2b17479d841

Observation 411e90da-7263-4a79-b97e-a8d49deb4b08 · outbound

This paper cites DocAtlas: Multilingual Document Understanding Across 80+ Languages.

Thinking with Anchors: Grounded and Efficient Document Reasoning DocAtlas: Multilingual Document Understanding Across 80+ Languages

Reference 24

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:24:50.491568Z digest=sha256:ceb76d10bba593fe69706d4ebd4ec0d18d98f85db1da74d35a79e87734806b01

Observation de501bda-bfc5-4cd5-92a2-e5fdad6cf85e · outbound

This paper cites Drone-based object counting by spatially regularized regional proposal network.

Thinking with Anchors: Grounded and Efficient Document Reasoning Drone-based object counting by spatially regularized regional proposal network

Reference 25

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source=pdf_text observed=2026-08-07T00:24:50.590490Z digest=sha256:d888f1285e590bd3c0014edb954f3ad475d2d6dde6b730ea0851dad8efed17b9

Observation c32ed399-ba1a-4a3b-a62c-6f3c45762d92 · outbound

This paper cites Layoutlmv3: Pre-training for document ai with unified text and image masking.

Thinking with Anchors: Grounded and Efficient Document Reasoning Layoutlmv3: Pre-training for document ai with unified text and image masking

Reference 26

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source=pdf_text observed=2026-08-07T00:24:50.674143Z digest=sha256:f383e2d37677d0f2c9a7c0c771d2f30d0304dec02578e649fb0ebf1322df6caf

Observation 45afe1ac-cda1-4449-b81d-fe0632a77905 · outbound

This paper cites Composition loss for counting, density map estimation and localization in dense crowds.

Thinking with Anchors: Grounded and Efficient Document Reasoning Composition loss for counting, density map estimation and localization in dense crowds

Reference 27

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source=pdf_text observed=2026-08-07T00:24:50.779625Z digest=sha256:e70bdc355dfbfbb319fc18b374a9f6f59bfeb85d3b2a6ddacdd62badd62e51f2

Observation d65af17d-37ba-4d74-a156-8e4f031bbbdd · outbound

This paper cites OCR-free document understanding transformer.

Thinking with Anchors: Grounded and Efficient Document Reasoning OCR-free document understanding transformer

Reference 28

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source=pdf_text observed=2026-08-07T00:24:50.928068Z digest=sha256:9939b5a0d5a7cf93aaf1104c847c7175a93fcd80a2894e6a0bde62db81d2f459

Observation 896c4cc0-aa0e-4673-972f-6b9426b418c6 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick.

Thinking with Anchors: Grounded and Efficient Document Reasoning Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick

Reference 29

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source=pdf_text observed=2026-08-07T00:24:51.487779Z digest=sha256:83090880e89dee68b95c1367f3bd5c685cacd8fa82c2ef73ba1105d14396bf85

Observation 88d80684-a1b8-4f5b-96b4-a410ad80ced4 · outbound

This paper cites Page segmentation using a convolutional neural network with trainable co-occurrence features.

Thinking with Anchors: Grounded and Efficient Document Reasoning Page segmentation using a convolutional neural network with trainable co-occurrence features

Reference 30

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source=pdf_text observed=2026-08-07T00:24:51.598760Z digest=sha256:8ce4d39e5ab0e45f2f53b8305d6fdfe421780b9ec5e862a1aa29a5dec7169a06

Observation 9f90620e-7413-4ee8-9718-02312095bd77 · outbound

This paper cites DocBank: A benchmark dataset for document layout analysis.

Thinking with Anchors: Grounded and Efficient Document Reasoning DocBank: A benchmark dataset for document layout analysis

Reference 32

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source=pdf_text observed=2026-08-07T00:24:51.860465Z digest=sha256:6cb9fc3a8ad9f1b06571b03ff62ce06cd77e3c916d7bd4c2deefe99c567a721c

Observation 21620cec-624c-4959-9099-2cf26a4621dc · outbound

This paper cites Morariu, Handong Zhao, Rajiv Jain, Varun Manjunatha, and Hongfu Liu.

Thinking with Anchors: Grounded and Efficient Document Reasoning Morariu, Handong Zhao, Rajiv Jain, Varun Manjunatha, and Hongfu Liu

Reference 33

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source=pdf_text observed=2026-08-07T00:24:51.949260Z digest=sha256:15c3298d766343d900283dd20b1b184bb901f63eebd32e5b318becc602544fa4

Observation 820acda7-e2b4-4fa0-8336-abeae281e46f · outbound

This paper cites MonkeyOCR: Document parsing with a structure-recognition-relation triplet paradigm.arXiv preprint arXiv:2506.05218, 2025.

Thinking with Anchors: Grounded and Efficient Document Reasoning MonkeyOCR: Document parsing with a structure-recognition-relation triplet paradigm.arXiv preprint arXiv:2506.05218, 2025

Reference 34

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doi, observed 2026-08-07T00:24:55.043880Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:24:52.027097Z digest=sha256:c763656132e47b0f7306e5cd4ccaa04f549db9ba8b18769093c730f6f7779115

Observation 77cd14d2-05c4-4874-b781-bdd45a5cdeed · outbound

This paper cites Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C.

Thinking with Anchors: Grounded and Efficient Document Reasoning Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C

Reference 35

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source=pdf_text observed=2026-08-07T00:24:52.105752Z digest=sha256:dd8474aefc3b3b61f6995b06c0ddc489f9cb9c0f9774caf8fc380b4a2d383496

Observation f4163009-e78c-427a-bae8-31c41caa1fc4 · outbound

This paper cites Visual instruction tuning.

Thinking with Anchors: Grounded and Efficient Document Reasoning Visual instruction tuning

Reference 36

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source=pdf_text observed=2026-08-07T00:24:52.183456Z digest=sha256:0f2d1a95f33d5cb7d463b78ead2442a4c60fc3299fe1d76ce445b86bac5ca7bd

Observation 43378107-26ca-4fa4-a554-6d8ab5ef90cc · outbound

This paper cites Grounding DINO: Marrying DINO with grounded pre-training for open-set object detection.

Thinking with Anchors: Grounded and Efficient Document Reasoning Grounding DINO: Marrying DINO with grounded pre-training for open-set object detection

Reference 37

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source=pdf_text observed=2026-08-07T00:24:52.290243Z digest=sha256:6031a5195ba2316c0ddadf3bd176c9bee2b352362adb259f3524bb4ce5db7ad9

Observation be5c1e1f-4a3a-4ab7-a795-8458df0ef21a · outbound

This paper cites Unified-IO 2: Scaling autoregressive multimodal models with vision, language, audio, and action.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unified-IO 2: Scaling autoregressive multimodal models with vision, language, audio, and action

Reference 38

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source=pdf_text observed=2026-08-07T00:24:52.374404Z digest=sha256:87eb6891fe203c0781d9dbf552dc47e90150818f957761998b17c318a6ac6f12

Observation 394f9ca7-b8f4-4e03-81a5-0a8b81ea2f44 · outbound

This paper cites Thinking with visual primitives.

Thinking with Anchors: Grounded and Efficient Document Reasoning Thinking with visual primitives

Reference 39

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source=pdf_text observed=2026-08-07T00:24:52.470880Z digest=sha256:c49719424195a6ac8f743ff20a8b76ac4aa94bcaac04ce9dfffde4a6b636f854

Observation fac83a38-d9a9-40b1-bf01-69180567a452 · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 40

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source=pdf_text observed=2026-08-07T00:24:52.561322Z digest=sha256:6e2a8b6671ccc5c50e2c595b2b618abb78653affae9619063bdb8bd7543adad0

Observation b61bccc2-bb04-4df5-9e9e-1886828ffa9a · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 41

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source=pdf_text observed=2026-08-07T00:24:52.639233Z digest=sha256:7da378180f8370c94690076698bb67466346faaeca170bceae66cf585a8c0cdd

Observation 61f184af-d016-4a8e-b440-6610a124707a · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 42

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:24:52.750695Z digest=sha256:ec893c26da1e3d6b86ac5411109559dbe44aeae848c649fb373c05f43f1e14de

Observation a9b12337-80b2-4e52-a59f-e6f44547cc9e · outbound

This paper cites Iiit-ar-13k: a new dataset for graphical object detection in documents.

Thinking with Anchors: Grounded and Efficient Document Reasoning Iiit-ar-13k: a new dataset for graphical object detection in documents

Reference 43

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source=pdf_text observed=2026-08-07T00:24:52.824268Z digest=sha256:b27114534b172b50472c93ed919f9e9170c8415647c92a364299106db641e9fd

Observation b6ae49ec-c851-4144-9fb7-a10bfc31b88a · outbound

This paper cites IndicDLP: A foundational dataset for multi-lingual and multi-domain document layout parsing.

Thinking with Anchors: Grounded and Efficient Document Reasoning IndicDLP: A foundational dataset for multi-lingual and multi-domain document layout parsing

Reference 44

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source=pdf_text observed=2026-08-07T00:24:52.923043Z digest=sha256:9bc554f753d21b91b78339cd6ae3e06f07eb5068b939f511c1ce8c8484d8db87

Observation 41a110d7-a2a8-43ae-aac8-b3c346f3a1cf · outbound

This paper cites Large Language Diffusion Models.

Thinking with Anchors: Grounded and Efficient Document Reasoning Large Language Diffusion Models

Reference 45

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source=pdf_text observed=2026-08-07T00:24:53.065685Z digest=sha256:256e53c81846976092914e34d42113a4e2905972d0329f89f62d364075dcbbf8

Observation d7201835-c1b5-4f7e-b8d9-8f9a55eefb83 · outbound

This paper cites A general approach for multi-oriented text line extraction of handwritten documents.IJDAR, 2012.

Thinking with Anchors: Grounded and Efficient Document Reasoning A general approach for multi-oriented text line extraction of handwritten documents.IJDAR, 2012

Reference 46

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source=pdf_text observed=2026-08-07T00:24:53.158010Z digest=sha256:822946694f4afeb6ebdef74a2ff6c9ce5e7eb1c518a03a31cbf3c1cd30f69ba6

Observation 808f3734-c002-475a-a11d-5faf1cca39c0 · outbound

This paper cites Teaching clip to count to ten.

Thinking with Anchors: Grounded and Efficient Document Reasoning Teaching clip to count to ten

Reference 47

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source=pdf_text observed=2026-08-07T00:24:53.219257Z digest=sha256:b6ab3fd6df6face58edffea6046f74879d208fa974ee5ac46a2e6000611a7c90

Observation 58608b4b-dc55-4974-b221-e0d013a8ec6f · outbound

This paper cites Continuous document layout analysis: Human-in-the-loop AI-based data curation, database, and evaluation in the domain of public affairs.Information Fusion, 108:102398, 2024.

Thinking with Anchors: Grounded and Efficient Document Reasoning Continuous document layout analysis: Human-in-the-loop AI-based data curation, database, and evaluation in the domain of public affairs.Information Fusion, 108:102398, 2024

Reference 48

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source=pdf_text observed=2026-08-07T00:24:53.369671Z digest=sha256:02dfae875d9ccd7a2cf9c87783c601a2fc63a4b6bfe710d647ce80083e3148e5

Observation 3dc67f54-36c3-4482-8fda-d13e60af90e2 · outbound

This paper cites Kosmos-2: Grounding Multimodal Large Language Models to the World.

Thinking with Anchors: Grounded and Efficient Document Reasoning Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 49

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source=pdf_text observed=2026-08-07T00:24:53.495972Z digest=sha256:12486d17b1e75559ca52346521684577fa7785f57f232cd090c0b6eb5b1a0683

Observation 7faada0d-29b7-45e0-b275-7ae08b53f293 · outbound

This paper cites Nassar, and Peter W.

Thinking with Anchors: Grounded and Efficient Document Reasoning Nassar, and Peter W

Reference 51

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source=pdf_text observed=2026-08-07T00:24:53.740933Z digest=sha256:181e548d7cf24bae2af6eab9c33ee150167d2b2fdec58f60c90b0bbb99615e8f

Observation 276ccffa-1798-4196-9fd5-131ebe9d0330 · outbound

This paper cites Learning to count everything.

Thinking with Anchors: Grounded and Efficient Document Reasoning Learning to count everything

Reference 52

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source=pdf_text observed=2026-08-07T00:24:53.802744Z digest=sha256:eaf05a661bc1a71019f42ea185b7c4fbbe1082ea01e50eef48673808117e9c0c

Observation ec3cda0e-375b-44a3-b16c-aa0c366f0ed1 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Thinking with Anchors: Grounded and Efficient Document Reasoning SAM 2: Segment Anything in Images and Videos

Reference 53

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source=pdf_text observed=2026-08-07T00:24:53.950122Z digest=sha256:cf22f83b7ca64302267a026d8fcd45defe1eea1929ebe179bb164b3ef437874e

Observation 01ed7edc-18a5-474a-8a50-c52288b54ea3 · outbound

This paper cites RF-DETR: Neural architecture search for real-time detection transformers.

Thinking with Anchors: Grounded and Efficient Document Reasoning RF-DETR: Neural architecture search for real-time detection transformers

Reference 54

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source=pdf_text observed=2026-08-07T00:24:54.060348Z digest=sha256:a3864a47099d9d5f595ccb008ea96f1c82d530e21655af7f14a084f87b143a14

Observation 034e7500-57ea-46a7-a51d-dff8000ef3ad · outbound

This paper cites Jhu-crowd++: Large-scale crowd counting dataset and a benchmark method.IEEE transactions on pattern analysis and machine intelligence, 44(5):2594–2609, 2020.

Thinking with Anchors: Grounded and Efficient Document Reasoning Jhu-crowd++: Large-scale crowd counting dataset and a benchmark method.IEEE transactions on pattern analysis and machine intelligence, 44(5):2594–2609, 2020

Reference 55

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source=pdf_text observed=2026-08-07T00:24:54.342985Z digest=sha256:dfb68157b79892fe233e2de5d5520ae05668b378348ba3ab2a9ef55be9804db1

Observation 193b4e5c-ae56-4c2f-8b9a-1134a1f869f3 · outbound

This paper cites An overview of the tesseract OCR engine.

Thinking with Anchors: Grounded and Efficient Document Reasoning An overview of the tesseract OCR engine

Reference 56

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source=pdf_text observed=2026-08-07T00:24:54.438755Z digest=sha256:5a121e3021dc7264f67eebd73f0d392d68d2b623457222f48337d2493020d4cf

Observation f80cc12e-ffea-4cfc-a0ac-e5ff2cf213ab · outbound

This paper cites ViperGPT: Visual inference via python execution for reasoning.

Thinking with Anchors: Grounded and Efficient Document Reasoning ViperGPT: Visual inference via python execution for reasoning

Reference 57

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source=pdf_text observed=2026-08-07T00:24:54.441343Z digest=sha256:56363232fb2fa32535ee5e4c5598af06d2d3661527c03965bb4c9e282a763fdd

Observation 82d90caa-d664-49e6-8f4a-30ba8a1e5e0a · outbound

This paper cites CountQA: How Well Do MLLMs Count in the Wild?.

Thinking with Anchors: Grounded and Efficient Document Reasoning CountQA: How Well Do MLLMs Count in the Wild?

Reference 58

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source=pdf_text observed=2026-08-07T00:24:54.443710Z digest=sha256:8f726c6f70b87d30b5e3021ea418e49a8be183e64aef4e6043d6cb1fa8ffe7f8

Observation 5576bf1c-6c8e-4710-9832-12241c09914a · outbound

This paper cites Unifying vision, text, and layout for universal document processing.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unifying vision, text, and layout for universal document processing

Reference 59

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source=pdf_text observed=2026-08-07T00:24:54.446460Z digest=sha256:2d22c1e017075126b673b24bd18d53c65c8a3ee1daec072d0a047214f4b35d47

Observation 30ce183f-53e3-4d55-b75e-a072d5c21aeb · outbound

This paper cites Kwai Keye-VL-2.0 Technical Report.

Thinking with Anchors: Grounded and Efficient Document Reasoning Kwai Keye-VL-2.0 Technical Report

Reference 60

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local_arxiv, observed 2026-08-07T00:24:55.321032Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:24:54.448925Z digest=sha256:f0d471d9773fb5ebae92c7018bf4f8699c660ff76c25d7f1e541e83c1ad70291

Observation 819bd54a-be10-4975-be9c-c34d5d50c113 · outbound

This paper cites YOLOv12: Attention-Centric Real-Time Object Detectors.

Thinking with Anchors: Grounded and Efficient Document Reasoning YOLOv12: Attention-Centric Real-Time Object Detectors

Reference 61

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source=pdf_text observed=2026-08-07T00:24:54.451586Z digest=sha256:f779881b032f97ec93bc08184700c8490cd53bc72e91bf26c0558756fb3ccdbf

Observation bfe4410f-5234-4672-8b85-2a1f5e692804 · outbound

This paper cites Tjong Kim Sang and Fien De Meulder.

Thinking with Anchors: Grounded and Efficient Document Reasoning Tjong Kim Sang and Fien De Meulder

Reference 62

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source=pdf_text observed=2026-08-07T00:24:54.454053Z digest=sha256:c79dc934aa78051a1ae0e4ea0b66749aaa4ab2a404168188149478998e47616c

Observation cb24a83c-1134-40de-b4b8-8d44b04c9ae9 · outbound

This paper cites SCAN: Semantic document layout analysis for textual and visual retrieval-augmented generation.

Thinking with Anchors: Grounded and Efficient Document Reasoning SCAN: Semantic document layout analysis for textual and visual retrieval-augmented generation

Reference 63

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source=pdf_text observed=2026-08-07T00:24:54.456515Z digest=sha256:60779f94974f7a02c4c128759f9a752e6ecbe6dc048e4a80660c4981fb3752f8

Observation 9698d5c8-eaaa-4402-9ca6-0ebb4acd8e55 · outbound

This paper cites Nwpu-crowd: A large-scale benchmark for crowd counting and localization.IEEE transactions on pattern analysis and machine intelligence, 43(6):2141–2149, 2020.

Thinking with Anchors: Grounded and Efficient Document Reasoning Nwpu-crowd: A large-scale benchmark for crowd counting and localization.IEEE transactions on pattern analysis and machine intelligence, 43(6):2141–2149, 2020

Reference 64

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source=pdf_text observed=2026-08-07T00:24:54.459129Z digest=sha256:7c1e561fe9c3412ee8099bb11f340cedf26435614da302030203113b7b3833b2

Observation 4259258c-d8c4-42b8-ae2a-de5784bd6c20 · outbound

This paper cites LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decoding.

Thinking with Anchors: Grounded and Efficient Document Reasoning LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decoding

Reference 65

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source=pdf_text observed=2026-08-07T00:24:54.461437Z digest=sha256:62ae0d449ea38ea2d9e4bd31f788db653fc5e39c0075e3f3766944364a63794b

Observation a690aa5d-53aa-4c4e-8ebe-a2afa9f8a5b6 · outbound

This paper cites Fast-dLLM v2: Efficient block-diffusion LLM.arXiv preprint arXiv:2509.26328, 2025.

Thinking with Anchors: Grounded and Efficient Document Reasoning Fast-dLLM v2: Efficient block-diffusion LLM.arXiv preprint arXiv:2509.26328, 2025

Reference 66

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source=pdf_text observed=2026-08-07T00:24:54.463953Z digest=sha256:f349a925387f0042cba49e13cb72902ee840e634c8047df2040a66a6644d166c

Observation d8fe4277-dccc-47ee-9532-5d1ffebcd9a8 · outbound

This paper cites DocGenome: An open large-scale scientific document benchmark for training and testing multi-modal large language models.arXiv preprint arXiv:2406.11633, 2024.

Thinking with Anchors: Grounded and Efficient Document Reasoning DocGenome: An open large-scale scientific document benchmark for training and testing multi-modal large language models.arXiv preprint arXiv:2406.11633, 2024

Reference 67

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source=pdf_text observed=2026-08-07T00:24:54.466365Z digest=sha256:d9314b7f967e6a5186b3195c0e0532d18059e28c293cd0e8af1950a39ed4155a

Observation 4cbf61c2-a4cd-4e7c-8e59-d77d14e2081e · outbound

This paper cites Florence-2: Advancing a unified representation for a variety of vision tasks.

Thinking with Anchors: Grounded and Efficient Document Reasoning Florence-2: Advancing a unified representation for a variety of vision tasks

Reference 68

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source=pdf_text observed=2026-08-07T00:24:54.469000Z digest=sha256:50ce71cad9a323597a8a814ff8d257a66e4eec1eb4db474ab06e8a7d11825585

Observation 585d1668-23e4-4831-8573-b8abb2c1dced · outbound

This paper cites Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V.

Thinking with Anchors: Grounded and Efficient Document Reasoning Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V

Reference 69

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source=pdf_text observed=2026-08-07T00:24:54.471478Z digest=sha256:f2416568da1dc12a9ca8f3b65aac5656dcce8aacdd290d9f4796b067b17e3cc2

Observation fec97968-127e-4f4a-9bcb-371692c94886 · outbound

This paper cites MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action.

Thinking with Anchors: Grounded and Efficient Document Reasoning MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

Reference 70

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source=pdf_text observed=2026-08-07T00:24:54.474041Z digest=sha256:8066bcf89e0817eca03e49e4dda1d0b8c6163b1bc313e50bc494d1535133cb03

Observation 712c21a6-6553-49b6-b733-ed53f314de63 · outbound

This paper cites Dream 7B: Diffusion Large Language Models.

Thinking with Anchors: Grounded and Efficient Document Reasoning Dream 7B: Diffusion Large Language Models

Reference 71

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source=pdf_text observed=2026-08-07T00:24:54.476459Z digest=sha256:6297835fc8547cbcf7b7c1dfba22fb4c920cf93f3bbacb26b84bddc4c1b2d2cd

Observation 8554b5dd-8a74-4452-806c-39494a6757ed · outbound

This paper cites Ferret: Refer and ground anything anywhere at any granularity.

Thinking with Anchors: Grounded and Efficient Document Reasoning Ferret: Refer and ground anything anywhere at any granularity

Reference 72

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source=pdf_text observed=2026-08-07T00:24:54.479375Z digest=sha256:ebaab8e6a0efdd7cde3e5474a4e8040a61d295792c9cb4563425ada28bb24415

Observation 32fc71cf-f639-4ea2-b614-8097c6899d45 · outbound

This paper cites Single-image crowd counting via multi- column convolutional neural network.

Thinking with Anchors: Grounded and Efficient Document Reasoning Single-image crowd counting via multi- column convolutional neural network

Reference 73

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source=pdf_text observed=2026-08-07T00:24:54.481841Z digest=sha256:aaffde35d12420d4f111c757e8b09f41bbf69a7b64796b360e490c8fad399996

Observation 9ddfc482-a3c7-4627-a6b0-b25ba5d6ace0 · outbound

This paper cites Multimodal Chain-of-Thought Reasoning in Language Models.

Thinking with Anchors: Grounded and Efficient Document Reasoning Multimodal Chain-of-Thought Reasoning in Language Models

Reference 74

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source=pdf_text observed=2026-08-07T00:24:54.484326Z digest=sha256:873bd628e33a588b1231d29ccb1964e657cd472982a4f4b65c245f651ea7ea4b

Observation 76f1fca5-d39d-40bf-9c35-fe62fe81cd9c · outbound

This paper cites DocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive Perception.

Thinking with Anchors: Grounded and Efficient Document Reasoning DocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive Perception

Reference 75

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source=pdf_text observed=2026-08-07T00:24:54.487012Z digest=sha256:a1c507a2c37814bb00170326356c35d9e14c488c5b174d3617adf09c80ff4f6f

Observation 747ef930-a335-48d1-9ef0-b22531f0f2e4 · outbound

This paper cites PubLayNet: Largest dataset ever for document layout analysis.

Thinking with Anchors: Grounded and Efficient Document Reasoning PubLayNet: Largest dataset ever for document layout analysis

Reference 77

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source=pdf_text observed=2026-08-07T00:24:54.495171Z digest=sha256:d6183024a9d1416d873250a0e7f0bfb757494403207883b26573ac220e668989

Observation 21be752e-a656-41b4-a9a0-f5dcd312670d · outbound

This paper cites DocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive Perception.

Thinking with Anchors: Grounded and Efficient Document Reasoning DocLayout-YOLO: Enhancing Document Layout Analysis through Diverse Synthetic Data and Global-to-Local Adaptive Perception

Reference 78

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.489763Z digest=sha256:20267c61522938c0e87a44c2132fabd8bde371476a61d975194003d785c58733

Observation c82c4cec-adf2-442f-9f4c-917c7ff3c3f9 · outbound

This paper cites FLARE: Diffusion for Hybrid Language Model.

Thinking with Anchors: Grounded and Efficient Document Reasoning FLARE: Diffusion for Hybrid Language Model

Reference 81

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verified exact
local_arxiv, observed 2026-08-07T00:24:55.094129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T00:24:54.497190Z digest=sha256:9d15f76dcc8ab2ae8754b77e74dfb5019b9bf9340e0cd00949c1b752e2e0901f

Observation f7059b72-769a-400f-b7a3-777ceee1a682 · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 82

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unresolved
no resolver link, observed 2026-08-07T00:24:54.500735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.500735Z digest=sha256:22f9d5154a24bfe6e56982f6f8d75814e738b78ca2bf78774eb860f0343487f2

Observation 8ee60e37-69df-4e82-8e5a-05747ca7b8c8 · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.502944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.502944Z digest=sha256:05f6b8cc3ecb5a91e7c13620cc26b03ba1a1b7ccba26e220654c4b4d17752e2a

Observation b9f39d7c-2bdb-4680-a610-450e85432332 · outbound

This paper cites icon.A single large, visually striking standalone graphic =prominent pattern.

Thinking with Anchors: Grounded and Efficient Document Reasoning icon.A single large, visually striking standalone graphic =prominent pattern

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.505710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.505710Z digest=sha256:2a350609d95115e6363c217ea3f6cb699a92a7ac874b5114ee73ce74482d8749

Observation 17df3003-ab72-472a-a9db-0c63384e8bf6 · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.508595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.508595Z digest=sha256:8019d1a6ee3aa252a78345ceabcc55f88264b1c57e7222d4bbeb7db53970bef1

Observation 503edb93-da53-495b-a3d4-2d42f43aeaad · outbound

This paper cites Image labels beside photos =image caption.

Thinking with Anchors: Grounded and Efficient Document Reasoning Image labels beside photos =image caption

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.511061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.511061Z digest=sha256:8c3e1812b3d20ae3410014b62963918d8fa1479ae6cf3903ea438f820bfd7012

Observation 82e2858e-b7ac-4263-9c57-333f08db9b7e · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.513793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.513793Z digest=sha256:24853ecbeaf50bee3391e73b898daaccd08ec997b9fe7e570abf5326ba06ae6a

Observation ca508761-afb6-4de2-bb94-4878bf0ee620 · outbound

This paper cites Plain colored region without border =color block (borderless).

Thinking with Anchors: Grounded and Efficient Document Reasoning Plain colored region without border =color block (borderless)

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.516548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.516548Z digest=sha256:981ccc9ba80fd31c722d476a45b6a71a40326a7fce5b29659e7213f7bf29f02d

Observation 38ebcd4d-8e19-4d28-b7cb-4fc0cb202e2a · outbound

This paper cites Do not split the tag across modes.

Thinking with Anchors: Grounded and Efficient Document Reasoning Do not split the tag across modes

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.519071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.519071Z digest=sha256:f762ba9ae7ddf53cf26405f9e00dc328da7eaac2f5b7211844e0fd8bd9568dc0

Observation 5bc58f7d-9a72-4852-bf8d-5cc4757c8de8 · outbound

This paper cites A single-item list must still be separated.

Thinking with Anchors: Grounded and Efficient Document Reasoning A single-item list must still be separated

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.521947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.521947Z digest=sha256:a16c99636f8ee7026333cc91be125bc8bbafe28c7b242df26a8922d2807432d9

Observation 8b985886-c44d-4bda-bac1-a6238c1db247 · outbound

This paper cites background pattern vs.

Thinking with Anchors: Grounded and Efficient Document Reasoning background pattern vs

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.524518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.524518Z digest=sha256:9387e9d1b6f10121704f8a6e76463c473f4577ef1112716f073023808517ad27

Observation 535cc545-2d32-426c-8d08-a2589687bb4d · outbound

This paper cites In newspaper layouts, side-column text adjacent to the main article =note; text at the very bottom =footer.

Thinking with Anchors: Grounded and Efficient Document Reasoning In newspaper layouts, side-column text adjacent to the main article =note; text at the very bottom =footer

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.527533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.527533Z digest=sha256:c42e181a95004f20374f202a4442f763f8c4bcda944b5d9bcbf450d2009f9c83

Observation 930a991c-7147-4889-b10d-a2062b957a0c · outbound

This paper cites Hyperlinks or emphasis embedded in a large body-text block without their own pre-annotation belong to the body-text box.

Thinking with Anchors: Grounded and Efficient Document Reasoning Hyperlinks or emphasis embedded in a large body-text block without their own pre-annotation belong to the body-text box

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.530207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.530207Z digest=sha256:dc3bcf465f9e0714a603285d2765d9d877ee4385500105ffbd23c2edac9d3e11

Observation 071559b1-af95-4ebc-8c21-30641c358209 · outbound

This paper cites image caption; table title.Contextual explanatory text at the top-left or bottom of an image block =note.

Thinking with Anchors: Grounded and Efficient Document Reasoning image caption; table title.Contextual explanatory text at the top-left or bottom of an image block =note

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.533010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.533010Z digest=sha256:252d1008c7feae3abe3938c0c47a5f991cb99c25188b4c13dd0482111f5dc12d

Observation 9e6aefdc-f807-48f2-aeca-48b92022a575 · outbound

This paper cites note.A label directly beside or below a photo =image caption.

Thinking with Anchors: Grounded and Efficient Document Reasoning note.A label directly beside or below a photo =image caption

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.535664Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.535664Z digest=sha256:2c177dfb2c51af8d09529b7da82cb593f769e17c76245212156c02d6dfe965d0

Observation 7007ce9d-855c-441b-a333-faaba021672f · outbound

This paper cites All elements above =foreground.

Thinking with Anchors: Grounded and Efficient Document Reasoning All elements above =foreground

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.538174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.538174Z digest=sha256:0c715abf7c87611197610ca8d31d9ca234afaeb7f3f3c653c5c9a291400300fa

Observation 3c12e59c-14f2-4ab7-9c3a-81f16d34e805 · outbound

This paper cites prominent pattern; legend vs.

Thinking with Anchors: Grounded and Efficient Document Reasoning prominent pattern; legend vs

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.541019Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.541019Z digest=sha256:ff02af5642b37d45760f3b543b01daf448790760bf6929a9d531c95340da5f7a

Observation 1317472c-6ea6-4b84-ae68-ffce08e77bcc · outbound

This paper cites legend.Text directly below a photo pointing to it =image caption.

Thinking with Anchors: Grounded and Efficient Document Reasoning legend.Text directly below a photo pointing to it =image caption

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.543430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.543430Z digest=sha256:eaaf3b6c42d859c6abb872fb48f781dbcf8ba9ca8b59ef33c2bede796a2be9d9

Observation adde57ab-746f-41cf-8661-9033fa4c138c · outbound

This paper cites icon (cartoons).Cartoon resembling a recognizable icon-style symbol =icon.

Thinking with Anchors: Grounded and Efficient Document Reasoning icon (cartoons).Cartoon resembling a recognizable icon-style symbol =icon

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.546004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.546004Z digest=sha256:70725165b4921987a93ee21f30688b8344838484238896fa102f40bbe697854b

Observation 7ddeea5b-46e3-415f-ac43-68fe1e9ee029 · outbound

This paper cites background pattern (full-bleed non-solid).If the bottommost layer is a non-solid graphic spanning the full width or height, label itbackground image, notbackground pattern.

Thinking with Anchors: Grounded and Efficient Document Reasoning background pattern (full-bleed non-solid).If the bottommost layer is a non-solid graphic spanning the full width or height, label itbackground image, notbackground pattern

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.550266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.550266Z digest=sha256:75a5e2c9dbfa65d79d23e96e6dcf597f50237827b4e871e18e04ae085f6f585f

Observation 3db1aa9a-c987-4752-a436-e52149246554 · outbound

This paper cites There areNnumbered boxes (0..N−1). Group them.

Thinking with Anchors: Grounded and Efficient Document Reasoning There areNnumbered boxes (0..N−1). Group them

Reference 101

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.553670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.553670Z digest=sha256:53271c713786caf2fbbfc76a0b9fe6f1b7ba9d9906ec67e563d9065cf327ea1f

Observation c8876943-0b61-419d-a001-4362a52b0c31 · outbound

This paper cites Below them on the right,[[6]] marks the First in Malaysia badge.

Thinking with Anchors: Grounded and Efficient Document Reasoning Below them on the right,[[6]] marks the First in Malaysia badge

Reference 103

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.559316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.559316Z digest=sha256:271b1b95fab6dd843a93d08b70ab364738031dda87e3af1288e53321daa9a8b1

Observation 207ec647-6593-4c59-b01b-4cb8071ff591 · outbound

This paper cites 37 Fine-grained Counting [Trigger_Placeholder] How many regions on this page should be counted as Photograph? Original Image Image with Visual Anchors Anchor Thinking Reasoning.

Thinking with Anchors: Grounded and Efficient Document Reasoning 37 Fine-grained Counting [Trigger_Placeholder] How many regions on this page should be counted as Photograph? Original Image Image with Visual Anchors Anchor Thinking Reasoning

Reference 104

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.562342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.562342Z digest=sha256:299940fc43562b53ca08888b195e9a96dbfb50b2e6dc5685c27a606a455a6160

Observation a823d827-ad93-4d7a-acc8-a393b4288557 · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 106

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.567489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.567489Z digest=sha256:698a74d49739f4b909e93dd20656ecc5f10074009c284ac55a5ba33f862fcecf

Observation 431c2b81-32ef-45ca-b5ec-52ebf4941ca4 · outbound

This paper cites 38 Fine-grained Counting [Trigger_Placeholder] Count the Table regions visible on this page.

Thinking with Anchors: Grounded and Efficient Document Reasoning 38 Fine-grained Counting [Trigger_Placeholder] Count the Table regions visible on this page

Reference 107

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.570262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.570262Z digest=sha256:2aa7235a75e10b8feb1a7e1e3cbdcb8baa84b5255e6e51c59f9a22a9d6c9da94

Observation ddc25a1f-2411-43ac-be70-2b6d5cb20636 · outbound

This paper cites an unresolved cited work.

Thinking with Anchors: Grounded and Efficient Document Reasoning Unresolved cited work

Reference 109

Resolution
unresolved
no resolver link, observed 2026-08-07T00:24:54.575516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:24:54.575516Z digest=sha256:2c03437b6e903cca2afdf47cf779dca3652f8b0a6358160ee35b13221c0fd703

Pith citing papers

No inbound Pith citation observations are available.