Paper Citation Record · LEDGER

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

As of 16 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 20 inbound Pith citation observations for arXiv:2412.14475.

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

pith.paper-citation-record.v1
2412.14475 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:15:56.192559Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:15:20.804212Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T23:57:53.176747Z

Reference resolution

12 of 12 outbound references displayed

verified exact0
verified fuzzy4
unresolved7
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation af091d17-c7da-4e6a-87d5-029565f0d090 · outbound

This paper cites Look for the same interaction but devoid of any heart symbol.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval Look for the same interaction but devoid of any heart symbol

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:15:56.339085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fd9f4ef7-d8b4-44b8-baa1-1a584198968a · outbound

This paper cites In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 19305–19314.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 19305–19314

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:15:56.419902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation acb89feb-0e48-4c88-8844-0a3e463b56a5 · outbound

This paper cites UniRAG: Universal Retrieval Augmentation for Large Vision Language Models.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval UniRAG: Universal Retrieval Augmentation for Large Vision Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T12:15:56.175111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d52db14-40e9-4c6b-acb0-57b31f01295e · outbound

This paper cites Finetuned Language Models Are Zero-Shot Learners.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval Finetuned Language Models Are Zero-Shot Learners

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T12:15:56.177838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3adc849-1f4d-4f9e-95e0-06843621c933 · outbound

This paper cites In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining , pages 4493–4501.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining , pages 4493–4501

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:15:56.411619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation eb581a6f-cfc7-4dda-a690-8d01eecacfbe · outbound

This paper cites In Forty-first Interna- tional Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval In Forty-first Interna- tional Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T12:15:56.185785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee9fb6dd-3468-4b03-90b6-16a9cffc43a0 · outbound

This paper cites Since only the CLIP-based checkpoint is available for MagicLens, we select the CLIP-L backbone for both methods.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval Since only the CLIP-based checkpoint is available for MagicLens, we select the CLIP-L backbone for both methods

Reference 12

Resolution: malformed identifier; raw_fallback, observed 2026-08-11T12:15:56.329625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 40e6231a-fe4b-4975-9fcf-654cff7cb8ca · outbound

This paper cites Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-11T12:15:56.180625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52b7cacc-e658-4bfb-a743-741745f6f167 · outbound

This paper cites Advances in neural in- formation processing systems, 35:27730–27744.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval Advances in neural in- formation processing systems, 35:27730–27744

Reference 2022

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T12:15:56.428137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e75326b6-96dd-4b38-b24f-87a9008f5cc5 · outbound

This paper cites BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-11T12:15:56.162136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d0be5d2-07fd-4662-8820-2fee6a1032e9 · outbound

This paper cites The Llama 3 Herd of Models.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval The Llama 3 Herd of Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T12:15:56.158303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cea26d7a-e0d9-4ef0-85df-1532a9fab0b2 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval Representation Learning with Contrastive Predictive Coding

Reference 8589

Resolution: unresolved; no resolver link, observed 2026-08-11T12:15:56.165259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 5f12a605-9e82-4beb-9de6-413412e083c2 · inbound

mmE5: Improving Multimodal Multilingual Embeddings via High-quality Synthetic Data cites this paper.

mmE5: Improving Multimodal Multilingual Embeddings via High-quality Synthetic Data MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-08T05:02:36.595221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cdd8dc1-59d3-454e-ac30-51e83ef4162a · inbound

Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation cites this paper.

Ask in Any Modality: A Comprehensive Survey on Multimodal Retrieval-Augmented Generation MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T23:35:56.668315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e21cafdd-a429-4a5e-bbeb-6698966204e0 · inbound

Modality Curation: Building Universal Embeddings for Advanced Multimodal Information Retrieval cites this paper.

Modality Curation: Building Universal Embeddings for Advanced Multimodal Information Retrieval MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 114

Resolution: unresolved; no resolver link, observed 2026-08-07T14:14:47.316531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f300874-302d-4a8f-8132-99a04d30d97a · inbound

mRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation cites this paper.

mRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T12:42:28.039506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 817a48cc-2a7b-4f0d-a292-666c9c209a86 · inbound

Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification cites this paper.

Video-XL-2: Towards Very Long-Video Understanding Through Task-Aware KV Sparsification MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T23:13:10.664784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea48ff13-bf4e-40f4-a2a4-63577caebc06 · inbound

MoCa: Modality-aware Continual Pre-training Makes Better Bidirectional Multimodal Embeddings cites this paper.

MoCa: Modality-aware Continual Pre-training Makes Better Bidirectional Multimodal Embeddings MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 51

Resolution: malformed identifier; no resolver link, observed 2026-08-06T21:52:26.368534Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9d88d211-7d25-4bd4-9218-0753f25b0e33 · inbound

M2IO-R1: An Efficient RL-Enhanced Reasoning Framework for Multimodal Retrieval Augmented Multimodal Generation cites this paper.

M2IO-R1: An Efficient RL-Enhanced Reasoning Framework for Multimodal Retrieval Augmented Multimodal Generation MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-05T22:52:01.500298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20634687-b0c9-4b4d-888a-96e2ce2993a2 · inbound

UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion cites this paper.

UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T17:15:20.804212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b256bed-4b4d-4b16-805a-3a0502ddb7fc · inbound

VaccineRAG: Boosting Multimodal Large Language Models' Immunity to Harmful RAG Samples cites this paper.

VaccineRAG: Boosting Multimodal Large Language Models' Immunity to Harmful RAG Samples MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-05T12:06:04.699156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 879d1c88-9ecd-43f1-9784-17f4e8b03650 · inbound

MetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction cites this paper.

MetaEmbed: Scaling Multimodal Retrieval at Test-Time with Flexible Late Interaction MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:11:27.427700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f1bba11f-22f1-4721-a4e3-89d5458a3eeb · inbound

FreeRet: MLLMs as Training-Free Retrievers cites this paper.

FreeRet: MLLMs as Training-Free Retrievers MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:01:23.440156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation bbf44705-8aec-4727-975c-e52fb73c1668 · inbound

FreeRet: MLLMs as Training-Free Retrievers cites this paper.

FreeRet: MLLMs as Training-Free Retrievers MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T13:51:47.927031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2590b86f-d365-48bd-8cb7-0945ba9214fc · inbound

MOON2.0: Dynamic Modality-balanced Multimodal Representation Learning for E-commerce Product Understanding cites this paper.

MOON2.0: Dynamic Modality-balanced Multimodal Representation Learning for E-commerce Product Understanding MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-03T22:05:18.174178Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b2daacc-64ab-4298-8848-2183d22a76d8 · inbound

PLUME: Latent Reasoning Based Universal Multimodal Embedding cites this paper.

PLUME: Latent Reasoning Based Universal Multimodal Embedding MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 56

Resolution: verified exact; arxiv_id, observed 2026-05-13T21:53:20.023927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e17543a1-e00b-413a-bce1-83c8107dae5a · inbound

HIVE: Query, Hypothesize, Verify An LLM Framework for Multimodal Reasoning-Intensive Retrieval cites this paper.

HIVE: Query, Hypothesize, Verify An LLM Framework for Multimodal Reasoning-Intensive Retrieval MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:56:02.495210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d71df57b-d05c-474c-9974-bc13298991b2 · inbound

Combating Visual Neglect and Semantic Drift in Large Multimodal Models for Enhanced Cross-Modal Retrieval cites this paper.

Combating Visual Neglect and Semantic Drift in Large Multimodal Models for Enhanced Cross-Modal Retrieval MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:31:13.650436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8ed8847a-afc6-4771-af20-3dc07e31baba · inbound

TIGER-FG: Text-Guided Implicit Fine-Grained Grounding for E-commerce Retrieval cites this paper.

TIGER-FG: Text-Guided Implicit Fine-Grained Grounding for E-commerce Retrieval MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-19T23:57:53.181609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e53ef929-4874-470e-85a3-9a1a25468bc8 · inbound

VIG-RL: Learning to Search and Insert for Verified Image Grounding cites this paper.

VIG-RL: Learning to Search and Insert for Verified Image Grounding MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 78

Resolution: unresolved; no resolver link, observed 2026-07-31T19:17:00.310323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d361da6-ed3b-4036-95a7-cc220fbcaec2 · inbound

Douyin Multimodal Embedding Model Technical Report cites this paper.

Douyin Multimodal Embedding Model Technical Report MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-04T13:45:31.800765Z

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Unavailable: canonical work link unavailable.

Observation a7f1fb02-e0e9-475e-aa65-791472167c6d · inbound

Learning from Failures: Retrieval-Centric CoT via Hard Negatives for Unified Multimodal Retrieval cites this paper.

Learning from Failures: Retrieval-Centric CoT via Hard Negatives for Unified Multimodal Retrieval MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T18:30:14.608010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.