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Paper Citation Record · LEDGER

Thinking with Anchors: Grounded and Efficient Document Reasoning

As of 9 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 2026-08-09T06:31:02.800959+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:fb52d44eb4d2ed0ed54e497921699881714eb563204c08a890f756645acacd1a

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=sha256:369eb25e288c7ab33c4a2c12ee32ba66a226bfd4074ee28858e591bf6a9df0b5

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=sha256:55ca351f46bdb3457329155fa45e70c3516cccd5f9af7cc357b1cf49f8a995cb

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=sha256:3ab89a36d739546e96523eeb094c9dd39a968bbaef4066673764ebe15ed428f5

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:db9cff6a4377861812d59c33ac9f7f0e694b739eecc361f549a356e3c459e57e

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=sha256:7cf4057fcb65bd38c5f15d39028b647164cf033f9a9755373990c83fd4b54d86

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

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:24:48.786909Z digest=sha256:ffd93a072f9da210b3df98534ce95c82f517ac6caaf84479194c8f87a5184709

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:b6fc3347cfe544407d105685bb3a074fa3ebbc623e48a9d4923ce9fa178e49be

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=sha256:2f4a3f94b98c10133c168cd4da36731779df0aa93d685295b1747dc73c447e25

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=sha256:2c5a4693aef7027fcc6dc746cc4b2b1cfc3ae0d035c57d7a2d48a68d6c026ed9

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=sha256:39ede851ff0a45081207ad13479f1670c5fc3ea5a6f134c4e03ba889d7f6b4ec

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=sha256:57a77350e987c1654fd9cfdaa662cbd9c6b029d9cfc4af21dfafd97d1ffcc6c2

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:a881b051eb840f6689009ce6cd6efa516a8c4807dbaa7b5df060c493d93942af

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:ba5b6db3fc086354538ddd8e47b957b22ef706a8c36b3ca040f41dd56b3b3a84

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=sha256:00d3177f8eb07b3d91ddb979fbbd1c0f58b649f720c4e323d8bb17e77854b770

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=sha256:3336d65be8dee9cd8fa971fb551983be6fdf79a46766304cf25a8c30d6888358

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=sha256:43e5352316402370f9d070fb4950077105834e1412b1f5ad500fb420944ff690

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=sha256:2b6314992874aeb75ff947c99a7070cc97ebc4e2db358aedbc9638934bcf0377

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:dbb31978ea4d9c8ffb2d08fc7f4f0c055353319f3817e17669c8baac47de39d8

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=sha256:266df26841f43eec04df809f7a1dac4f21ff923e289eaef4e1d13a344e57bec1

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=sha256:381676c368a9246c55dbc843eaf4bd8da4c016bceaf4710cfb9a948630ad2951

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:eea0469ae7abc81eaf12be1d01a90e58ecaf5ff7e10dca3bf7320eec467f8b52

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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local_arxiv, observed 2026-08-07T00:24:55.065353Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:24:50.491568Z digest=sha256:60c9b160a412d245c4fffaa27c39ea665cb4b9f423bc0566a0b185cefc22f71c

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=sha256:74a6fbbb3ffd8d00dede1eff52c76c51107d899bd86f54291af80a621701bc5d

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=sha256:4c5d6bd121bbffc16a50fe0e25864cbfc55f65e124037b541e72201abc50b9f1

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=sha256:969513c4d68d25899ef736e9495982c30d744963d8c76e7823c4583ea6dcfc26

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:b264e60573a3a881659dd7ea441a3c53ebe15dcfd88eb9653c18d270a5589e41

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:fc60c3620d1b8cc1e74cacc47e56bf4046389bf4376144d36b41a791eb143a6f

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=sha256:0601490fa4d6b2af8d17af77938c53bbe0860a4e1172c47b87cc553142c0fa47

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:c99717afa030de87219222ae515e0859e4adffb9029aa19a7f287e658987c8ed

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:f1d230a535ae36083f75efbe3558b5abd42b6d6549145b207dd3e65defa33fbc

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:24:52.027097Z digest=sha256:0a9c6152de7277e59afadb905e74407920140e30150d0034f445a22c7d22a959

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=sha256:5c0b9bfc4019013368b2a0f6abdbe2a7813ed9a500ba8507354a73602ebe678b

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=sha256:91e744f1db335fbaa688e015f5286fe8be44193b7003d64a74bb3e1270856deb

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=sha256:0d4178e807227d1572dc15089ca196d114bb7472227fce47cfb4f7f2a482d121

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:e2d112e444091a2ee2c64ed1ee7f3026fa829090b453249235c02bcc715a19b8

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=sha256:503399e2e510d4ce7c95433b8752cf37aa383b6abd77b25485a0f58130bec0cb

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:d268e2da20d44ed332041fff79db10bb0a8c9d6c7e571036ffa28151433fe23e

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:f9a842bb4bcbf7588735f37afbe6c95ee1b641b0c5d40bf1615943118a0d5742

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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source=pdf_text observed=2026-08-07T00:24:52.750695Z digest=sha256:2d7ce236308bfc6727f303e36ef84ff9afedb63a2fb54f730b5c26126ff3af0a

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:b1e13810196c75e465ce371019b770d74ad6cde190a0f2bbce92306341e37354

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:ed8548de31fc333198ea7b57b53cef3347b353d226b25938774174e39d2b151e

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:e1bd16b1e4c90c13c3c0db663cba3c933b78c44f69893d41a0fb747e0edec5e8

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:b3d44ed15bb79c2f2f477f9f024f9ad82cc3044930a3c589e28e371e5f1e035b

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=sha256:11315286d6ea2522036eb6dad612c41685f5eee0ead400cecc2ba2a9ac5bf71d

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=sha256:3946db7391d1261fde14e6f2823a3792f7348783e6c7c7ec99c0cdc934326b29

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=sha256:4a106bcb0b7864fb63669bcd27373832e3ad65a4aae4ede28a8f624c63f56a0d

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=sha256:9d31978ac8d19766b7494f82092c09a032576227edcb6565a79e25d251a9491d

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:deda0b920abacffacb152678a023d5911310669bf246d026d60ae81232d2043d

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:e49426887457dc631de919939762c76a12099daaa15d13a7e921a2fa877df71f

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:fc3d376754bb019b7f026226448afa71c2d5ae1e6bbb4b06cbf7a94d4a842c08

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=sha256:8e9cb8599435d618d6fcb5eb43448b621a4d544769d5548d1ca10d56c005a2bf

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=sha256:68b2515059b13e2be31a37220c7b22575423f9ff302b27f06d39be9530ea2932

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=sha256:2172cf0473c02a8df6c956a6e287fe17b42230ae82491db72d0385a34ec07e0a

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=sha256:35f16a68fe965f38cd7af4cdaf4699e246f8d583ae0c1f58391805c5b06a96fb

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=sha256:0ea8f523bef2578a057660d6c7f79dc904c010f1625f4e309e37c7f6f6a7f8a8

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

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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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:24:54.448925Z digest=sha256:09906b377537cc0036a0c9ed63005588adc2f47edd2a393a9843791292f38bf2

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=sha256:12de1f998e1eb41ab13348b7474602fc69d6e3de2f90ceb9eeb9cfb1b181e54e

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=sha256:48372fa72a43c011e9d2dc8d3edd4e80eb4b9f91a7c56acbc10dd59741e490fd

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:d9ec3c0b65aaef809db2f912ada7997749287e7194ca962ee9bd2cffd73409a9

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

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source=pdf_text observed=2026-08-07T00:24:54.459129Z digest=sha256:bc0b7c4f586898526a221ebfe63b8c63899b37bcca44960e1293857df919b613

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:e3da6856a2f81f48833bc35ad6269c9368294c0ff506fc215c3886fe4b58a024

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

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source=pdf_text observed=2026-08-07T00:24:54.463953Z digest=sha256:1c3c610a0532fa05ef4b315b8b111ca88110c4693e5f55e8da578665f81efa6d

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

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source=pdf_text observed=2026-08-07T00:24:54.466365Z digest=sha256:0f96021eabd8f23049dc696db45ab1223ace1a90b34a93d27d40f15921400c64

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

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source=pdf_text observed=2026-08-07T00:24:54.469000Z digest=sha256:1acb1af5c56d6cf1f12cf8717ee4cd2fde9a7bf2e1a3446c52ff7b6a875e9942

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=sha256:58486e0d1b1f85954471e40f87c7179226a00667c232bcf6ac54a02407dbba7f

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=sha256:256cc585265389d0f708b15d7449f617c81d4de760c8c69cb90b9e86de2ede09

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=sha256:3cd8bdea8687beb315374ecc6f46fa6fcd9bf75073de48b070978f4fbdefe926

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=sha256:4153a957053fc918f1e1f373e149c640efcfb6f79dabd3eb64f5561814c381c4

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:e88d98e46c7c0307b555d09cb099fa99e5732fe735699c4f7bda3390c3c565aa

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

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source=pdf_text observed=2026-08-07T00:24:54.484326Z digest=sha256:43db2266a19c1db16783c75012d2baa5d75b163d2335e4ebaf4fb06129708bce

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=sha256:2149a3660a39d3a4e00d06188c4674e9ff537a5f4f3c9f7d6972d86534b2eb4d

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

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source=pdf_text observed=2026-08-07T00:24:54.495171Z digest=sha256:f3c65f25f3ce73df8886eca160d7998618f74a194ba1fd7737cdf06a9889dcbd

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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source=pdf_text observed=2026-08-07T00:24:54.489763Z digest=sha256:acbc5ee8182c1e080172b824eb22f352646a8f374044699c1af7f4e20f31c84c

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T00:24:54.497190Z digest=sha256:782e01bb01e5ab9b2f4aff610112df33ee8a025c055a880265fa655e3c233a9a

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

Resolution
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:d4310d00893401a2b843a54a57786701621e892d22ef3bf0a92373a22a5ea3f5

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=sha256:66d223e05f3bff062d776a354829ba0fec3b407e2fe2f2616d9fbd95ffe5f084

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:f4b979aa3de9b42ac7798bc5c9e93fafcb9b6c1a1dbb62e1d1677ceadaf2862c

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=sha256:2842a50cbbdd705f174249d022db305d56d53146653d8dbdb9a83e2beaf8cbe1

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:b1cd9ce6c013e29978cb1eb7eb4c88578973ecb27af002af428b1d907fcc2157

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=sha256:05e279c58cbf5243efdda8cb26fb93b819feaffba8489dc5870e37e7be480aec

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:eff6fb0f738760fe60eb86bbfc7839901c6e08dfe598b9f971c1ec008bb41157

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=sha256:6df86d26fff4474104a1f7ab483194acc4505bc6796b5ad0e541de6d1900448f

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=sha256:260d9c0204292b6dd1f491a8bc6c359c3848f24c4dafb8ffb8e0a4436dabf903

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=sha256:4bce7c1d3179eb2ddaaa9bf7c47ddd89868eb38015b35c0f567aeff642506875

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=sha256:5909c142344a01ad97b6178f49608ef9568b554ad59fe35660c40fd1fe606853

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=sha256:5efb8eb63204a56bdb566b6c4e8f823c6b1e75030a979e7b33266d2461b06c23

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=sha256:95e76382c87a009f3ec69de5e1e78f3f29eb6823feb32fd339a92781d819a24d

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=sha256:5be6e68b7692562bd62f7700222c8a71a0874fbd23c33b38029af88676ebe8f2

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=sha256:1e34f305891040b6ffd0534d949290f361fcc9ef17900a07930b6f12b2a51049

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=sha256:87043da3ffb889568a694254013698ed351b82e9deec2c35d41dc11e05a7eaad

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:d8c46d45ec52115f177cb910fab4ac453b11de038dc4b7ee2be1386c0e40a393

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:f3ba8200e80b1f4566c5f8a6dd9d1c1eca63d238eeb0ad528eccc46f937b7c00

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=sha256:224cda9b9613bb808f230f005637d004f6b5d2d8d60a09c421f203480fae66ab

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:a19edf3d48ba7f3d47399d73441322f4704b0278ea746e9110ae60b54873dab1

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=sha256:44711a1448bd1911dcd1e9ba0a55d37702c41561863a040b8f7bd4460c311bf2

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=sha256:9fc37e8343772459f5074fb4724b59ff6634e17b16001d01aba6adea2d6752d1

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=sha256:1b77e9414cacf550d7bec4aa1a967ecae9a10afa2ac802eb475b893134f50588

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:d91f5e7622958bb90e64b1a7e03a58b65521763f2f6ec3346769e55c2d5ce579

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:e87735a6d5af0305371f01790c6e4847edfc813460db6b22e439ece1c65ea59d

Pith citing papers

No inbound Pith citation observations are available.