Paper Citation Record · LEDGER

AIDE: Agentically Improve Visual Language Model with Domain Experts

As of 8 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 1 inbound Pith citation observation for arXiv:2502.09051.

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

pith.paper-citation-record.v1
2502.09051 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T22:51:02.176089Z

measured 28 of 28 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:33:56.525727Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T00:34:04.453845Z

Reference resolution

27 of 27 outbound references displayed

verified exact1
verified fuzzy1
unresolved25
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9fd34b14-1a2d-4600-be48-0b6c5d838139 · outbound

This paper cites https://github.com/PaddlePaddle/PaddleOCR.

AIDE: Agentically Improve Visual Language Model with Domain Experts https://github.com/PaddlePaddle/PaddleOCR

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T22:51:02.599280Z

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.

Observation e3a99080-5ac5-41f9-a351-04e6bdf735ed · outbound

This paper cites Flamingo: a Visual Language Model for Few-Shot Learning.

AIDE: Agentically Improve Visual Language Model with Domain Experts Flamingo: a Visual Language Model for Few-Shot Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.035005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 477853ad-ab42-431a-8877-4c30b5d58839 · outbound

This paper cites ShareGPT4V: Improving Large Multi-Modal Models with Better Captions.

AIDE: Agentically Improve Visual Language Model with Domain Experts ShareGPT4V: Improving Large Multi-Modal Models with Better Captions

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.040957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae84e11c-25a2-49fc-8504-0c76cd8e3e6b · outbound

This paper cites ColorSense: A Study on Color Vision in Machine Visual Recognition.

AIDE: Agentically Improve Visual Language Model with Domain Experts ColorSense: A Study on Color Vision in Machine Visual Recognition

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-07T22:51:02.454498Z

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.

Observation 288263e2-4415-4cd8-973d-2d77755e6549 · outbound

This paper cites MegaCOIN: Enhancing Medium-Grained Color Perception for Vision-Language Models.

AIDE: Agentically Improve Visual Language Model with Domain Experts MegaCOIN: Enhancing Medium-Grained Color Perception for Vision-Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.054133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 707eaddc-99b1-4369-a018-e021d1ce2148 · outbound

This paper cites VILA$^2$: VILA Augmented VILA.

AIDE: Agentically Improve Visual Language Model with Domain Experts VILA$^2$: VILA Augmented VILA

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.060115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17b99959-2ea4-4a07-b09e-aacff4629978 · outbound

This paper cites an unresolved cited work.

AIDE: Agentically Improve Visual Language Model with Domain Experts Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:51:02.582399Z

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.

Observation 86d13882-21a5-4091-8838-69c0b071b24b · outbound

This paper cites MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models.

AIDE: Agentically Improve Visual Language Model with Domain Experts MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.077942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 539149fd-9897-41cf-b11c-8f42aeac7118 · outbound

This paper cites Language Is Not All You Need: Aligning Perception with Language Models.

AIDE: Agentically Improve Visual Language Model with Domain Experts Language Is Not All You Need: Aligning Perception with Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.083431Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54530509-9881-4191-8e03-df9c6846c256 · outbound

This paper cites Evaluating Object Hallucination in Large Vision-Language Models.

AIDE: Agentically Improve Visual Language Model with Domain Experts Evaluating Object Hallucination in Large Vision-Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.089154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bf98f31-0817-465a-842c-6028598edeba · outbound

This paper cites Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning.

AIDE: Agentically Improve Visual Language Model with Domain Experts Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.094840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d1c5df0-0697-4f7b-bf31-2729069bfb5f · outbound

This paper cites MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning.

AIDE: Agentically Improve Visual Language Model with Domain Experts MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.100050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32e65011-305e-4243-94c0-f70778bc5d39 · outbound

This paper cites Visual Instruction Tuning.

AIDE: Agentically Improve Visual Language Model with Domain Experts Visual Instruction Tuning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.105296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 801101c5-25ef-4aa6-bb36-b682c8af1162 · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

AIDE: Agentically Improve Visual Language Model with Domain Experts Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.110594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a95793cf-c7a3-48be-930d-3fc39b394dab · outbound

This paper cites MMBench: Is Your Multi-modal Model an All-around Player?.

AIDE: Agentically Improve Visual Language Model with Domain Experts MMBench: Is Your Multi-modal Model an All-around Player?

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.115887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35d0c92a-b5ab-48f1-bf2e-0f1d10152ea7 · outbound

This paper cites an unresolved cited work.

AIDE: Agentically Improve Visual Language Model with Domain Experts Unresolved cited work

Reference 17

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:51:02.566521Z

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.

Observation a3334bfa-f0a5-46b5-89b3-b804ec73ca3b · outbound

This paper cites ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning.

AIDE: Agentically Improve Visual Language Model with Domain Experts ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.125610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b7deb53-b14d-415b-885b-03ae6c5fcc8f · outbound

This paper cites Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks.

AIDE: Agentically Improve Visual Language Model with Domain Experts Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.130476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c07c2caa-faa4-46f9-ae1d-b4c4accee154 · outbound

This paper cites an unresolved cited work.

AIDE: Agentically Improve Visual Language Model with Domain Experts Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:51:02.551802Z

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.

Observation 9e50171f-9fac-4c3c-a3d1-e69360510242 · outbound

This paper cites Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders.

AIDE: Agentically Improve Visual Language Model with Domain Experts Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.140407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29b874c9-f940-4a09-b68b-1e0d9b484a78 · outbound

This paper cites Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs.

AIDE: Agentically Improve Visual Language Model with Domain Experts Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.145279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9288146e-b192-4e30-99dc-fb5f06424d32 · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

AIDE: Agentically Improve Visual Language Model with Domain Experts Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.150470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 425c3e3c-6699-4e6a-b98f-4afc0b156f14 · outbound

This paper cites an unresolved cited work.

AIDE: Agentically Improve Visual Language Model with Domain Experts Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:51:02.536797Z

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.

Observation b37e27cd-d0da-491f-9f3c-1e4c4349c0ff · outbound

This paper cites an unresolved cited work.

AIDE: Agentically Improve Visual Language Model with Domain Experts Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-07T22:51:02.521494Z

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.

Observation c062180a-2661-4a6b-a21e-c281cf7ac7ec · outbound

This paper cites Florence: A New Foundation Model for Computer Vision.

AIDE: Agentically Improve Visual Language Model with Domain Experts Florence: A New Foundation Model for Computer Vision

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.164934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c9d1c0e-3121-461b-83d5-51f24c97b64d · outbound

This paper cites online" 'onlinestring :=.

AIDE: Agentically Improve Visual Language Model with Domain Experts online" 'onlinestring :=

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.170241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76938200-1074-44f6-b82a-50bf4817e6ed · outbound

This paper cites write newline.

AIDE: Agentically Improve Visual Language Model with Domain Experts write newline

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T22:51:02.176089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 7d51a540-97a0-41d0-9202-02ef0d0b3ea4 · inbound

VL-GenRM: Enhancing Vision-Language Verification via Vision Experts and Iterative Training cites this paper.

VL-GenRM: Enhancing Vision-Language Verification via Vision Experts and Iterative Training AIDE: Agentically Improve Visual Language Model with Domain Experts

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-08-07T00:34:04.544547Z

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.