Paper Citation Record · LEDGER

MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:2407.21439.

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

pith.paper-citation-record.v1
2407.21439 v2

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:26:48.640460Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T03:26:29.522095Z

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Outbound references

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Pith citing papers

Observation db7cf982-5136-4bdd-8a21-7b8c849cdcf1 · inbound

[CLS] Token Tells Everything Needed for Training-free Efficient MLLMs cites this paper.

[CLS] Token Tells Everything Needed for Training-free Efficient MLLMs MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T20:23:18.494894Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f30c1ff8-c5da-4edd-9365-30995fd5f807 · inbound

Re-ranking the Context for Multimodal Retrieval Augmented Generation cites this paper.

Re-ranking the Context for Multimodal Retrieval Augmented Generation MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T21:31:36.457256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3880363-f873-48c8-98a8-aff26caa6c42 · inbound

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding cites this paper.

Advancing General Multimodal Capability of Vision-language Models with Pyramid-descent Visual Position Encoding MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T18:53:21.146912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bb00841-177b-4903-9002-8156b2501165 · inbound

Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection? cites this paper.

Can Multimodal Large Language Models be Guided to Improve Industrial Anomaly Detection? MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T14:03:31.085402Z

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Unavailable: canonical work link unavailable.

Observation 6f0c58a8-71ae-4346-ad77-9d614b4367d1 · inbound

MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document Retrieval cites this paper.

MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document Retrieval MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T00:57:01.524134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0eb58194-925d-49d8-983b-041ace8443a5 · inbound

MMSearch-R1: Incentivizing LMMs to Search cites this paper.

MMSearch-R1: Incentivizing LMMs to Search MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-16T15:27:04.434875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 218b0545-9730-4ecd-87a5-7850e7bc3386 · inbound

Structured Attention Matters to Multimodal LLMs in Document Understanding cites this paper.

Structured Attention Matters to Multimodal LLMs in Document Understanding MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:47:37.157188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 455e2a99-45a1-4abe-8724-6e181a5c3fde · inbound

Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation cites this paper.

Filter-And-Refine: A MLLM Based Cascade System for Industrial-Scale Video Content Moderation MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T14:58:42.431248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ba350e6-d4d5-446e-a5ac-b2fe3690b2d8 · inbound

Progressive Multimodal Search and Reasoning for Knowledge-Intensive Visual Question Answering cites this paper.

Progressive Multimodal Search and Reasoning for Knowledge-Intensive Visual Question Answering MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-18T20:06:49.993824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation afeab4e9-ee85-4b06-8a3e-527685adbb07 · 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 MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T12:06:03.171729Z

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Unavailable: canonical work link unavailable.

Observation 44b61f8a-b3f0-4ece-805d-1ca1e97a2b09 · inbound

MoLoRAG: Bootstrapping Document Understanding via Multi-modal Logic-aware Retrieval cites this paper.

MoLoRAG: Bootstrapping Document Understanding via Multi-modal Logic-aware Retrieval MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T16:26:48.640460Z

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Unavailable: canonical work link unavailable.

Observation 64ba41ca-8f99-419e-8568-a0a436a3f7e7 · inbound

UniRank: End-to-End Domain-Specific Reranking of Hybrid Text-Image Candidates cites this paper.

UniRank: End-to-End Domain-Specific Reranking of Hybrid Text-Image Candidates MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T03:30:18.800075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4177daae-e04e-4b28-b35a-f1a75d543151 · inbound

POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management cites this paper.

POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T13:10:26.411295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b7a8d606-9765-47ef-be30-f437c1d9e6bd · inbound

POINTS-Seeker: An Open Recipe for Multimodal Search Agents with Visual Memory Management cites this paper.

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T16:18:19.791830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 743e5878-ff36-4ce1-8c12-cc3460eefd45 · inbound

DR-MMSearchAgent: Deepening Reasoning in Multimodal Search Agents cites this paper.

DR-MMSearchAgent: Deepening Reasoning in Multimodal Search Agents MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 61

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T12:31:07.955385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e6d67562-0b42-45ab-970b-d4bf2cd3a09c · inbound

MEG-RAG: Quantifying Multi-modal Evidence Grounding for Evidence Selection in RAG cites this paper.

MEG-RAG: Quantifying Multi-modal Evidence Grounding for Evidence Selection in RAG MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:56:12.167030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fd1e0177-7bc5-4082-8290-f3ffabefabf9 · inbound

Very Efficient Listwise Multimodal Reranking for Long Documents cites this paper.

Very Efficient Listwise Multimodal Reranking for Long Documents MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T05:27:19.513310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c8eeca18-ff73-4727-9182-75531912103d · inbound

Utility-Oriented Visual Evidence Selection for Multimodal Retrieval-Augmented Generation cites this paper.

Utility-Oriented Visual Evidence Selection for Multimodal Retrieval-Augmented Generation MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T19:09:22.931216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 62dcfd88-1786-4d73-824a-3ed816b35fe5 · inbound

ImageAuditor: Membership Inference Attack against Image-based Retrieval-Augmented Generation cites this paper.

ImageAuditor: Membership Inference Attack against Image-based Retrieval-Augmented Generation MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:29.523662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 01479933-8141-4996-a352-b434b846aa2e · inbound

Mitigating Modality and Language-Style Gaps for Zero-Shot Video Moment Retrieval cites this paper.

Mitigating Modality and Language-Style Gaps for Zero-Shot Video Moment Retrieval MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T15:36:43.543626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbd19029-5fd5-48d1-8ab2-a416f8b429ca · inbound

Reason Before You Retrieve: Agentic Planning for Multi-modal RAG cites this paper.

Reason Before You Retrieve: Agentic Planning for Multi-modal RAG MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 155

Resolution: unresolved; no resolver link, observed 2026-08-02T10:20:56.267613Z

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Unavailable: canonical work link unavailable.

Observation 312351ca-9292-4bd0-8cfb-724d94152819 · inbound

DualG-MRAG: Decoupling Macro-Reasoning and Micro-Matching for Multimodal Retrieval-Augmented Generation cites this paper.

DualG-MRAG: Decoupling Macro-Reasoning and Micro-Matching for Multimodal Retrieval-Augmented Generation MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-31T03:11:53.134556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.