Paper Citation Record · LEDGER

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning

As of 19 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2504.21263.

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

pith.paper-citation-record.v1
2504.21263 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:12:43.318792Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

40 of 40 outbound references displayed

verified exact0
verified fuzzy16
unresolved24
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 09c9d36b-7a06-4edd-9847-e4968303d1fa · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Flamingo: a visual language model for few-shot learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.086277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 037a2a1b-4b9d-48f6-adc9-5cfb2db92f59 · outbound

This paper cites Visual prompting via image inpaint- ing.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Visual prompting via image inpaint- ing

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:44.106739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f0c1fdde-05fc-4384-b87d-e3264fe354f5 · outbound

This paper cites Language models are few-shot learners.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Language models are few-shot learners

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:44.086176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8a165846-d522-443d-8e57-f385bcbcccf1 · outbound

This paper cites Why can gpt learn in-context? language models secretly perform gradient descent as meta- optimizers.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Why can gpt learn in-context? language models secretly perform gradient descent as meta- optimizers

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:44.068751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ee7af2de-b636-4e3d-a1a8-213360c1ea32 · outbound

This paper cites Why can GPT learn in-context? language models secretly perform gradient descent as meta- optimizers.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Why can GPT learn in-context? language models secretly perform gradient descent as meta- optimizers

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:44.048735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8110bb54-5fc6-4a6e-b27c-4a90ae71af7e · outbound

This paper cites A survey on in-context learning.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning A survey on in-context learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:44.015916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 477e48e7-21e7-40c8-8956-df521c4e8653 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Taming transformers for high-resolution image synthesis

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.998457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 52500beb-ebeb-41f5-b255-43188ed5dc50 · outbound

This paper cites The pascal visual object classes challenge: A retrospective.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning The pascal visual object classes challenge: A retrospective

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.129236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f80b276-862d-4c1f-b189-2eee41fcd80c · outbound

This paper cites Explore in-context learning for 3d point cloud understanding.Advances in Neural Information Processing Systems, 36, 2024.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Explore in-context learning for 3d point cloud understanding.Advances in Neural Information Processing Systems, 36, 2024

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.970145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4fa4bc87-e4c6-4d60-b08a-54696e648e4a · outbound

This paper cites Masked autoencoders are scalable vision learners.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Masked autoencoders are scalable vision learners

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.138499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5bd6351-6cd7-44f2-9342-6b5f1aaf18db · outbound

This paper cites In-Context Learning Creates Task Vectors.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning In-Context Learning Creates Task Vectors

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.144547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a240d9dc-96c3-4767-8fa7-1fd9a1971ba9 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning LoRA: Low-Rank Adaptation of Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.150291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b6f8670-5679-42a1-b0e9-d5aace0a00b3 · outbound

This paper cites MIMIC-IT: Multi-Modal In-Context Instruction Tuning.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning MIMIC-IT: Multi-Modal In-Context Instruction Tuning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.156342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb0bd2cc-8ff5-4802-a194-8777bbfe6981 · outbound

This paper cites Visual in-context prompting.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Visual in-context prompting

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.942955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e79820b0-0e6e-4210-8104-a1020581fad9 · outbound

This paper cites Microsoft coco: Common objects in context.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Microsoft coco: Common objects in context

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.167715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6dcea9f-04c7-4633-b420-5a363085b3e0 · outbound

This paper cites P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.174370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5c4336e-44f8-4954-998a-4b11b8720e87 · outbound

This paper cites Context diffusion: In-context aware image generation.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Context diffusion: In-context aware image generation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.180678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a91a195e-a492-415d-9146-2f10d5128eef · outbound

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

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Kosmos-2: Grounding Multimodal Large Language Models to the World

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.187196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ec7e0bc-cb32-41fa-846f-44ae1d3ac1b8 · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Measuring and Narrowing the Compositionality Gap in Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.193441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b83a6800-b869-454e-bab3-0b19b78f126b · outbound

This paper cites Imagenet large scale visual recognition challenge.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Imagenet large scale visual recognition challenge

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.199317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 862cc234-0f4e-4028-b925-bbb85c40cb3e · outbound

This paper cites One-Shot Learning for Semantic Segmentation.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning One-Shot Learning for Semantic Segmentation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.204365Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc7c940c-1782-4590-8bc6-84a4d0375615 · outbound

This paper cites On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.209568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87120e2a-fd86-493a-9c8f-6c511490109c · outbound

This paper cites Generative multimodal models are in- context learners.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Generative multimodal models are in- context learners

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.888875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 63a787fe-1176-4d10-b137-7ac012a125d1 · outbound

This paper cites Exploring effective factors for improving visual in-context learning.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Exploring effective factors for improving visual in-context learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.220638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19353e04-9c22-4668-8a02-4a1a9cacb89f · outbound

This paper cites Rethinking and improving visual prompt selection for in-context learning segmentation.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Rethinking and improving visual prompt selection for in-context learning segmentation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.225660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6ecead2-b0ec-4fd2-a608-d7c4e2261312 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Gemini: A Family of Highly Capable Multimodal Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.231123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a125e601-c513-4f29-a908-bb71e0aeb5d2 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning LLaMA: Open and Efficient Foundation Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.236675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91e845be-518d-41d0-9834-05ff6c6e48cb · outbound

This paper cites Transformers learn in-context by gradient descent.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Transformers learn in-context by gradient descent

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.856938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f1220948-9b87-4f6f-8a40-412645341f4b · outbound

This paper cites Images speak in images: A generalist painter for in-context visual learning.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Images speak in images: A generalist painter for in-context visual learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.838881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cf2b64a0-14da-4a1d-9eba-fbfda98d8d62 · outbound

This paper cites SegGPT: Segmenting Everything In Context.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning SegGPT: Segmenting Everything In Context

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.258254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8752d6ed-c736-4a48-a5f8-fd36dbf522e8 · outbound

This paper cites In- context learning unlocked for diffusion models.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning In- context learning unlocked for diffusion models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.819218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f271e597-d663-4a02-95d6-5f80d84d3957 · outbound

This paper cites Larger language models do in-context learning differently.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Larger language models do in-context learning differently

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.275668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3460d02-5db6-4e38-936a-981bc3965cc1 · outbound

This paper cites Towards global optimal visual in-context learning prompt selection.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Towards global optimal visual in-context learning prompt selection

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.800337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f69c66cb-3ae8-41d2-a53a-b104a14b9798 · outbound

This paper cites Ground-Truth Labels Matter: A Deeper Look into Input-Label Demonstrations.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Ground-Truth Labels Matter: A Deeper Look into Input-Label Demonstrations

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.288678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce09b2f6-c75d-42c6-a7aa-103013e43c24 · outbound

This paper cites Instruct me more! random prompt- ing for visual in-context learning.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Instruct me more! random prompt- ing for visual in-context learning

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.781826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cb80cf3a-0cd3-4d5d-9d89-473592dc8aaf · outbound

This paper cites What makes good examples for visual in-context learning? Advances in Neural Information Processing Systems, 36, 2023.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning What makes good examples for visual in-context learning? Advances in Neural Information Processing Systems, 36, 2023

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.762937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1c3bd1a0-311c-4876-a000-c1d69f88bf05 · outbound

This paper cites Mmicl: Empowering vision-language model with multi-modal in-context learning.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Mmicl: Empowering vision-language model with multi-modal in-context learning

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:12:43.740550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 67fe4a03-0411-4932-8902-486515969664 · outbound

This paper cites Can We Edit Factual Knowledge by In-Context Learning?.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Can We Edit Factual Knowledge by In-Context Learning?

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.312726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ea49a14-a23f-4a3d-95f1-6bb3fd59179d · outbound

This paper cites Visual In-Context Learning for Large Vision-Language Models.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Visual In-Context Learning for Large Vision-Language Models

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.318792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7aff7bd1-7e60-4758-807d-b6a26cb7406c · outbound

This paper cites an unresolved cited work.

Embracing Collaboration Over Competition: Condensing Multiple Prompts for Visual In-Context Learning Unresolved cited work

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-16T05:12:43.114116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.