Paper Citation Record · LEDGER

DenseMLLM: Standard Multimodal LLMs for Dense Prediction

As of 6 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 1 inbound Pith citation observation for arXiv:2602.14134.

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

pith.paper-citation-record.v1
2602.14134 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:23:35.957580Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-08T01:54:30.649092Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T02:04:26.424891Z

Reference resolution

23 of 23 outbound references displayed

verified exact0
verified fuzzy0
unresolved23
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 96f62d90-8e2e-41b6-ad2d-0f6fed872828 · outbound

This paper cites RLE string.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction RLE string

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:35.463345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 658d868e-8250-4af4-8bc0-9ce006f3c349 · outbound

This paper cites an unresolved cited work.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Unresolved cited work

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:35.718786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f46f50ed-9152-4b56-91ae-a312b9e0d20d · outbound

This paper cites S., and Lin, M.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction S., and Lin, M

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:34.302345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a15d26ea-df99-4243-8734-283e6f38b8eb · outbound

This paper cites Swinmtl: A shared architecture for simultaneous depth estimation and se- mantic segmentation from monocular camera images.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Swinmtl: A shared architecture for simultaneous depth estimation and se- mantic segmentation from monocular camera images

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:34.473897Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 75207e2f-7548-48ec-9a5b-1503e99d3947 · outbound

This paper cites Ufo: A unified approach to fine-grained visual perception via open-ended language interface.arXiv preprint arXiv:2503.01342, 2025a.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Ufo: A unified approach to fine-grained visual perception via open-ended language interface.arXiv preprint arXiv:2503.01342, 2025a

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:34.644056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52b6dc11-bfab-4cda-ac4c-669226af52ec · outbound

This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:34.805229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd6dfdfe-4afe-437f-a1a5-f4490fc688d6 · outbound

This paper cites VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:34.980496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6645d106-7b66-4803-9bb6-a7c6d0e446d4 · outbound

This paper cites InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:35.129957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e52d6eb0-fe4a-4304-ad84-425e73b3fbdd · outbound

This paper cites Qwen2.5 Technical Report.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Qwen2.5 Technical Report

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:35.241079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94644f63-9640-493d-983b-78c3f719e063 · outbound

This paper cites Visual representation alignment for multimodal large language models.arXiv preprint arXiv:2509.07979,.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Visual representation alignment for multimodal large language models.arXiv preprint arXiv:2509.07979,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:35.288627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af58203f-071f-47fd-b286-8d4ed74fdd03 · outbound

This paper cites Semantic Segmentation for the Open World.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Semantic Segmentation for the Open World

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:35.634650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7980be9-7a39-448f-b585-91aa30436ebd · outbound

This paper cites RLE string.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction RLE string

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:35.775714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 721c078c-2fcd-468f-83c6-d0306fc8ebe2 · outbound

This paper cites During testing, the predicted values need to be de-quantized to obtain the real depth; otherwise, only relative depth is obtained.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction During testing, the predicted values need to be de-quantized to obtain the real depth; otherwise, only relative depth is obtained

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:35.957580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e295596-64b2-4160-a1f5-c77d0116f190 · outbound

This paper cites During testing, we dequantize to the actual depths and exclude invalid depths.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction During testing, we dequantize to the actual depths and exclude invalid depths

Reference 1000

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:35.913684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e449bbf3-80e5-470f-b876-fd81be049334 · outbound

This paper cites Token activation map to visually explain multimodal llms.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Token activation map to visually explain multimodal llms

Reference 2011

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:33.922033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1451865a-7c9a-4791-9a06-15a32fff1dfe · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction DINOv2: Learning Robust Visual Features without Supervision

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:34.118285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0872b2d1-4d96-4fd7-a576-8b93f4c585a0 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:35.367262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4008008e-1e56-4c2a-9d80-8aef88889994 · outbound

This paper cites an unresolved cited work.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Unresolved cited work

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:33.985256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac3b1f72-e304-4413-aa12-aa9b707e7c18 · outbound

This paper cites Depthlm: Metric depth from vision language models.arXiv preprint arXiv:2509.25413,.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Depthlm: Metric depth from vision language models.arXiv preprint arXiv:2509.25413,

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:33.622893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83e0c2c3-6ba3-4fb7-8596-b705792efcad · outbound

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

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:33.484278Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e66a50c-6327-46c8-b119-652a6d6c6a69 · outbound

This paper cites UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction UniDepthV2: Universal Monocular Metric Depth Estimation Made Simpler

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:34.181055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 081f0df1-d124-4cc9-abe0-b3032db15574 · outbound

This paper cites SAM 3: Segment Anything with Concepts.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction SAM 3: Segment Anything with Concepts

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:33.793070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c736002b-5762-44f3-92ec-012ce0ce4a4b · outbound

This paper cites Lu, P., Bansal, H., Xia, T., Liu, J., Li, C., Hajishirzi, H., Cheng, H., Chang, K., Galley, M., and Gao, J.

DenseMLLM: Standard Multimodal LLMs for Dense Prediction Lu, P., Bansal, H., Xia, T., Liu, J., Li, C., Hajishirzi, H., Cheng, H., Chang, K., Galley, M., and Gao, J

Reference 2026

Resolution: unresolved; no resolver link, observed 2026-08-02T23:23:34.046942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation e2fbf0c8-a908-4dbb-a474-6a0934b4ef71 · inbound

Vision as Unified Multimodal Generation cites this paper.

Vision as Unified Multimodal Generation DenseMLLM: Standard Multimodal LLMs for Dense Prediction

Reference 104

Resolution: verified exact; local_arxiv, observed 2026-07-08T02:04:26.426147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.