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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 2026-08-08T06:32:00.761636+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=sha256:2d81f094e5ba21fba798b4c17318cec99ea1f6213daaaa185b8988c5535ce515

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=sha256:417907c30d212bdad776bccf587eb03762e6b5e47313202b011fb9c9e1abea41

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=sha256:2241fec08b33b43d54152df250fc02b3010f1fff7585ca26c23f4e0dd0dd5cd6

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:e2bdc9f8e663167a88d8082fb6874858fa8d16387a28a6a8b0b781bc5431d50e

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=sha256:93c7537345d98fc1235eb4980c7df862b5bc2e105435401a2da49b17dd3b4eb1

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=sha256:9e49f1e00f21d2b9f5ce4d9cc35363848bed5d59ed0e68c671d690c63384270a

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:b8e237b581f161e7387babd334c0c866116949832b06b19e26a096785fb1aa14

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=sha256:5827a5df40b214ef201e5975686ef51cb198bf091dadf6f6c2c3c4246959fd70

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:af96665257091acd28153dd7f19481965776cb50e0cfc9c446c0f628e48ba042

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=sha256:8b7566aad7e9d641f7e18c45ca11507a16df21c291079b38ed5d13b2b9ea113d

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:be8741ef9d324aae1f96d5686c47c3e21c6d8cdb37060fe61b49752797161f8f

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:a33ef7a4855789ce9ca5e1d9dddfe9c3e06d1c2ddc54af51e27529b0208bea46

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:be96c503a2743ce3665c886a5c4bc34e724b908edd2ab9c5b51126f02f6ff402

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=sha256:81ed69175a015e28dae1ad861c9b60a47afb598204a574cb322fb9120f438cbc

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=sha256:31bea43e26979371f778c8c100ca675b89804965cc7aefce2a6efe7f48af2655

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=sha256:7de04060bfdbb1d6290c179dfa04e31977a3b19d8b2067f778d2d62391db1d31

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:c5b5ff5b572afe8ac1a8764753e25b41cb7ac4555f20968c627f366b45cbf3a1

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=sha256:8400e7fb6d415fc6fe855b2c7faa8b65a61c6919a41ea7f72f6de65a333bf680

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:c0b76ad9b6a3d2c671d8f98f2448eb3080cdd8b9d3783410822da6e76c692b85

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:c72e9079cf062cdf15d2fd00b84e2411685c7f406d3331a614a5c40785666c64

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=sha256:5aff8a453fa229826aa9353f5cab3db51b54f26424470c114a15a97fe9551dbf

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:e805165aebc4a63c5f1fc8d2bbf9c8b4c5b6ee28eb5bb9859bcafbee2f070cbb

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:24:50.491568Z digest=sha256:3d6beee5384d7cc8bc43746f4f0db58b10789c3e3dddbc58ee782c2a1938ac13

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:a88fa320aa612252a1341bdd54938860a101e2723debf4c192548fe5ba579485

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=sha256:5ceb20c3ca32ace1f74101506e867d50c351b98c8999c97cbe0346cb985c9a51

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:a561d3a130c307a09bc1a58dc9e3081091bba1a5b907a0a70f3c0a188899cf5d

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=sha256:1f997f13825bf7eca15638da8e756dde4f9f29bc30b31aaec723c9c924127fb9

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=sha256:9370ed0fb4c9c9d4af02dfcb8093addb59c3ebf4de696c2f1977f051e4d1eaca

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:b084f8b355d9c9086fa0e27549b601ae0037ff5a7df8c4425aadf7f59ee4ad9d

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=sha256:6367d9fd847588ff0787a35228c55e78ee7f04357985e987ff727ca8056e7588

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=sha256:925328e9d84e05a971c958a01592d33b55c48d491dc1ecea62796eeeb4d546e3

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:24:52.027097Z digest=sha256:558a54e28deb086b812a3f9c53e5dd2a22ec43e03d8b01d71ab2f16dd00be16c

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=sha256:3fb3540e973f83b8b48e024a82417d9ea2f7947a9891e25d7c1d2ebe22b45b97

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=sha256:75802dd1ed8554715dbbd80b234bc808d9e20c06a8f684c4c15d420a0c6ca8ca

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=sha256:5f15c23c3a51d5a6f37769c7c95f2bc87cd90fb1bc826cac105dacaa64ba4aaa

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=sha256:2d7c4b98ea12131023d6e5406706eeca03c033b34a4ccbfe2c7896cdfee73ddb

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:ff5992b819654573a4922ca1b1e812618908e1b08a65891f93d125803cea97c7

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:c03cccbf01ffa2a6848c0af7f16a8b6d3d8a872987684ed8258adbf9fc40a558

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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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:24:52.639233Z digest=sha256:67d18a32e73ac9042e161dc03389fbd2911e85cc5e79a976bf07f32f530d7edc

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:24:52.750695Z digest=sha256:99b29d2a3c362b65fa2da7d977a6a1d646b6b2559fa5e2187dc800d5cf2b0f1c

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:b85cdea09f9613fd3c62db188d5f2678682c92e15d0ad5550cd4530fd7b70be4

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=sha256:1de55047d113960ecbbe9057c4d094269ba81f4ccb444c158048611455dfdf36

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:e72cfac2827dd612cef7497b9a92a018286701adeff992656af674525347f7e8

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=sha256:7907413ccfc7cbf63854d5e5865340af40f9e99b200c9ac85f289ca650f28168

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:bff3a7d8bee9205889e2c323b06d38baf91e3f82904722b3fd357be2968277c5

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:cbb7276885e2760077d3c84077cb92ec140861e7fbdb94f860c093f2aec1f24e

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=sha256:17d66bdeaf7af2072b5bb49d9c7263523a873a3098034a3aebd3b1c77072fb51

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:c418bc8e5de384331969af5eab9e583f503f14ae1e5c3c50825ad7046d26521d

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:e83816b34e2f9eaa783da3b5c5d1a7932e665ed322f0d118b84f0e2f5eac4415

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=sha256:3181777de256908ffe849d81c9c959b5db4fb600e0b4cca3628b6f2794764b2f

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:cc8034871cbca0055aed27ea7940831f0bf2d82cd3c56ed40f227a4ea031beb3

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:df78717a5f2776b2770ef076d9b4188d562440b5bc28dc28e15ba9847edca5cc

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:f0834b3a7ad773a3eaff87ffb6f348a51364dea07decd0cb35d3911af3801bd7

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=sha256:699c6d20d14de28ac7caf27cdd3e69c4ad6bbf0c3e44f33b244033f66e369906

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=sha256:4369e3f482615bac2969e37895007e8c5257cdc5d841061efbc1e230796ee942

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=sha256:3f8785f3b8d0d76343a1bd128715a9d75c6d98f652dda54ae4aa76f13f51acd7

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:24:54.448925Z digest=sha256:4f2537b5bbe3bf4df800424045b7fe0d77d6d842eddca5006527a3a607fa0be8

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=sha256:7e77886f61a75d1525190b915777d25d21bab205f4f20d7493fea355f2f4de4a

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=sha256:3b64f0d81a5245cdeb4a5e95f78debea90e6ce27c2c99ff6ab679e6aa1fc8ef5

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:ff7d1ca56833ddc11ec8cf4abf508bccf31544bdb79e630da1f1eb576a0751d2

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=sha256:957021c365d7bfa9e4cd778ad6104c15b8fccb120316f74b7be1d1c27be01314

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=sha256:0589a1e025af01ba6c9557543e98b05a736627462577ae90e94ab0864c5ee057

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:c4a7ab1bc0e3f723f6255e18164cc4e1c80b54e82917a490cc813131e8f9333a

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:b859c9f16edc0deec24c83b4c037e94db3466d0f97027d2b3a403aaf9dfc51d1

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=sha256:34bb3c781b506a69d3bc1e9d42352f65ec6d1bf43dd1bd326570c10c1d355cbc

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:e7a9d1b112af9521b7c7a6f4c9d7aaf253b69e0e1f40bcad04759368e2813a0b

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=sha256:898d6d5a4dbb9afe6180110722edf91da6580fdb1e1e97c52ec381aa3810ba6f

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:a54c984f9952bbccb11c4792bbf1fe17a8f4c049fa0f050b1a9d5899b56bb9bc

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=sha256:23545bbb6e7477556e1ea2e0def16553e99b5c4d86e2cb54f0b595fe77d69ce9

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=sha256:7289d1ea8c92d6e35f4b1bdeece427146b8652e3f854306a8330b30ba204878b

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=sha256:2c6301fd3e67b17a9fa7a7b233581ae8a65403b13ae8297fb130d13176801e6b

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=sha256:03363f27768fa6eba8d663db096baf9c4f6cd62e0c648a7f303c179eab19f7ca

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=sha256:143df04411f850151e72e3aac5ab64c2ecc0340ae3fbb0ea7464539593bdc538

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=sha256:066164d38a69e48aa40c69ab71aaf8e8e3c55c14fac509e9126232671ebccf03

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T00:24:54.497190Z digest=sha256:629fef1d4ea591dde9f3ffd23dd53066e1d36b44c4862526e9310dca5ad1ff04

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=sha256:64f32ece43bfc3b648aa98e33f8440fcfd33accd4d702b807257c9d37ab9a0b0

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

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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=sha256:6aa56089e40a401ec116cd848081ba06a527df2ec5cc655cee9ce9106622b7f2

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=sha256:179c688f1523adbf82684c2dcb533855b694f13b5fb1f1aab4998c65380e00de

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:e4978f4748c4a6384dd3b32ad21f9ab928c17f87616a70eb00c1b2f2ecfb2907

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=sha256:1a232a48444f7752620088889f6f383a54098270e8d30f5b91f0b0d794652532

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=sha256:5dfe69b126e13e952fb93e6316d0d68c09ef8234d1751747cb66ed297ad7c82a

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:a454ba9abd7365f12bcc547785dd09cf2121518762237f6cfcd51a21c6ba228c

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:c435fc59896b6d158c8dba9e2f84f61bed855ed6ca09977d3ac64f1a84b8b17e

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:e51875768a062c5733439e2783a06df73ca91df967dd266b86296498cf7f976a

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=sha256:955f6b1884e3ae2aaa8ac1cc8cca5225bf47ac650436a6ae000367cec8bce232

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=sha256:1cc1e1a521927c978648b55e8b3d46d6afe9ce23362872c812865350ef29e064

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=sha256:25abef02af59b62c7c0992d01fea1b1fdce3638bbdecde843cce4427b103f84b

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=sha256:83871ebf671b1fbcfaa6c49983f0efa3f1215f78c8559cf2991f57a5e0ce539f

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:b15b24890b468ac63a6b51e3476dd55bdfd16459e257a4ce2db9fe29622983e8

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:fba7f3717767c0b37f58045c3053142228731858fb4a1aaac4e940b725f865ae

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=sha256:6568236a244ff5f6eab8f76598c65af60b215cb00319b8767293a8cb52546582

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:cf4a7885824ccdc9cf285fd3b2192131b5f66fdf13eb25f790e29de39178a11c

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=sha256:08a8a18d4691ac5b8311c94543f99bce88dc0564a0352bb0865a3f380d09d739

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:c7d30d9284c3cad1569aebb369d2ff40b470058d9f871386c3a8f1463ba1fe71

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:f9755c103687f5a878742d375a522ad3cc19539bca35ca7651db9bd03001753e

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=sha256:87bf0ae98c3e6c9bc001abb32941aecbe4c37ea47f63ae63c6250049848fe3d7

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=sha256:439206abd6f089148d1a59f866d7db5faf1f1cfaf9f7bc214fa0ae79cf62b74a

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:e6de18b6e1e9336ebf80d1404c34ffeabbdea627a6bc80bc6fafb8208930eb05

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=sha256:60efc19582c8cbdf5b505b83890423604864946d7dc3a33d737f50dbfaab59e3

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:d87a0eb789abf3f265a75c6fce12fc62b11646f2048bb7e21fe08deb06d29954

Pith citing papers

No inbound Pith citation observations are available.