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Paper Citation Record · LEDGER

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

As of 15 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 11 inbound Pith citation observations for arXiv:2507.05513.

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

pith.paper-citation-record.v1
2507.05513 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:30:17.456943Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:17:07.896230Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:26:45.662409Z

Reference resolution

33 of 33 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a19bd9a3-99f5-4e52-9965-cc30d66829aa · outbound

This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 1

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Observation d0078f67-5d0e-4c8b-b65b-9ceda893262f · outbound

This paper cites NV-Retriever: Improving text embedding models with effective hard-negative mining.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model NV-Retriever: Improving text embedding models with effective hard-negative mining

Reference 2

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Observation e4cc2e0d-72d5-4f4d-876d-a54ddbd8c0e9 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 3

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Observation b46d6ff3-48bd-4bfe-98f2-a4b28ee47c6b · outbound

This paper cites Improving Text Embeddings with Large Language Models.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Improving Text Embeddings with Large Language Models

Reference 4

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source=pdf_text observed=2026-08-06T19:30:14.121856Z digest=sha256:4ce9efed60df32435f4104fddc2bf37068558b43c96314ea5eecd0240a0d1757

Observation f8929367-915c-490d-a7d9-8b936e685c2c · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model MTEB: Massive Text Embedding Benchmark

Reference 5

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Observation 12dd8bdc-8af7-4542-8dc9-ddce17c36247 · outbound

This paper cites Maintaining MTEB: Towards Long Term Usability and Reproducibility of Embedding Benchmarks.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Maintaining MTEB: Towards Long Term Usability and Reproducibility of Embedding Benchmarks

Reference 6

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Observation b6ea4e9e-39c1-4865-aee7-b94237261c65 · outbound

This paper cites Colpali: Efficient document retrieval with vision language models, 2024.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Colpali: Efficient document retrieval with vision language models, 2024

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6a7a5e06-6293-4852-87d3-6a94e896a44d · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 8

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Observation 31b93e16-d9d9-4226-928a-0be167144748 · outbound

This paper cites Llama-nemotron: Efficient reasoning models.arXiv preprint arXiv:2505.00949, 2025.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Llama-nemotron: Efficient reasoning models.arXiv preprint arXiv:2505.00949, 2025

Reference 9

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source=pdf_text observed=2026-08-06T19:30:14.904219Z digest=sha256:7aa2d66c7f7cc30db9e9564f20d07aa3af5469f0ef4b737008b00cf49244065b

Observation efc8c371-3195-4ec9-8a13-0156566cf750 · outbound

This paper cites Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models

Reference 10

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source=pdf_text observed=2026-08-06T19:30:14.990336Z digest=sha256:0e027c523d639d264760cc6192f9fbd666fb1c77768679270084258984564275

Observation e4100d6c-9eff-4187-817e-e7a6ac4ded21 · outbound

This paper cites Eagle 2.5: Boosting long-context post-training for frontier vision-language models.arXiv preprint arXiv:2504.15271, 2025.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Eagle 2.5: Boosting long-context post-training for frontier vision-language models.arXiv preprint arXiv:2504.15271, 2025

Reference 11

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Observation 56c58fc6-bd31-4405-a763-f42ad0bf928a · outbound

This paper cites Learning transferable visual models from natural language supervision.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Learning transferable visual models from natural language supervision

Reference 12

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Observation b0df4747-e17c-400a-8a12-e75a29bad489 · outbound

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

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Reference 13

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Observation 8c69ad93-c839-48e0-8bb3-3696c272c0d3 · outbound

This paper cites Am-radio: Agglomera- tive vision foundation model reduce all domains into one.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Am-radio: Agglomera- tive vision foundation model reduce all domains into one

Reference 14

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Source-reported events for the cited work

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Observation 89728c12-f3ff-45b7-bba5-a93f1e99fbe9 · outbound

This paper cites Vidore benchmark v2: Raising the bar for visual retrieval.arXiv preprint arXiv:2505.17166, 2025.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Vidore benchmark v2: Raising the bar for visual retrieval.arXiv preprint arXiv:2505.17166, 2025

Reference 15

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Observation 55e902fc-2d4d-470a-acfa-003d15ec0f3c · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 16

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Unavailable: canonical work link unavailable.

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Observation dc91540f-a6d3-45ab-98e9-245c2010e7b3 · outbound

This paper cites Colbert: Efficient and effective passage search via con- textualized late interaction over bert.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Colbert: Efficient and effective passage search via con- textualized late interaction over bert

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 1aa4abb2-8692-4107-8f47-19f0172c2454 · outbound

This paper cites A simple frame- work for contrastive learning of visual representations.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model A simple frame- work for contrastive learning of visual representations

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 18f9aa0c-bbc7-4273-a115-09267a35e8d6 · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 19

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Observation 09ea16db-ff8d-4c11-acb8-a56763042a02 · outbound

This paper cites Miracl: A mul- tilingual retrieval dataset covering 18 diverse languages.Transactions of the Association for Computational Linguistics, 11:1114–1131, 2023.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Miracl: A mul- tilingual retrieval dataset covering 18 diverse languages.Transactions of the Association for Computational Linguistics, 11:1114–1131, 2023

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation d31d5bb3-60a2-47b4-b2aa-5ee5f95b94de · outbound

This paper cites Natural questions: a benchmark for question answering research.Transactions of the Association for Computational Linguistics, 7:453–466, 2019.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Natural questions: a benchmark for question answering research.Transactions of the Association for Computational Linguistics, 7:453–466, 2019

Reference 21

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Observation 48dd99ce-cd7c-48a9-8f2d-e6f086bf55ef · outbound

This paper cites Stack Exchange Community Data Dump, 2023.https://archive.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Stack Exchange Community Data Dump, 2023.https://archive

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b8f29932-ad0f-44b1-ad30-7d1a25884192 · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 23

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Observation 88e33850-ae5d-49c5-9ee5-6314aab896bf · outbound

This paper cites Mammoth2: Scaling instructions from the web.Advances in Neural Information Processing Systems, 2024.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Mammoth2: Scaling instructions from the web.Advances in Neural Information Processing Systems, 2024

Reference 24

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raw_fallback, observed 2026-08-06T19:30:18.667317Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 6cfec9d6-82ce-4196-b19d-2236621dcdab · outbound

This paper cites Xueguang Ma.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Xueguang Ma

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 82c44e7f-d6b2-4b51-b68e-0ffd5524c382 · outbound

This paper cites Tevatron 2.0: Unified Document Retrieval Toolkit across Scale, Language, and Modality.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Tevatron 2.0: Unified Document Retrieval Toolkit across Scale, Language, and Modality

Reference 26

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Observation e6f067d6-b26c-4c68-aba5-2e3f9d913474 · outbound

This paper cites llamaindex/vdr-multilingual-train, 2025.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model llamaindex/vdr-multilingual-train, 2025

Reference 27

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raw_fallback, observed 2026-08-06T19:30:18.460475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 899b14df-0cd5-4ba3-8cbe-7bddf2309539 · outbound

This paper cites Visrag: Vision-based retrieval-augmented generation on multi-modality documents, 2024.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Visrag: Vision-based retrieval-augmented generation on multi-modality documents, 2024

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ef193f98-922c-4c93-9e98-1405c16b9bdb · outbound

This paper cites Building and better understanding vision-language models: insights and future directions., 2024.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Building and better understanding vision-language models: insights and future directions., 2024

Reference 29

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raw_fallback, observed 2026-08-06T19:30:18.244951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 5bdb5fe4-7cb7-43ea-9522-c6de41db5230 · outbound

This paper cites MIRACL-VISION: A Large, multilingual, visual document retrieval benchmark.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model MIRACL-VISION: A Large, multilingual, visual document retrieval benchmark

Reference 30

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Source-reported events for the cited work

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Observation 3e96084d-fce8-4651-a21f-be0eab99cc8f · outbound

This paper cites Enhancing q&a text retrieval with ranking models: Benchmarking, fine- tuning and deploying rerankers for rag.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model Enhancing q&a text retrieval with ranking models: Benchmarking, fine- tuning and deploying rerankers for rag

Reference 31

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raw_fallback, observed 2026-08-06T19:30:18.141073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation a8fa457f-0902-4db2-9e18-dde56e62facc · outbound

This paper cites A little pooling goes a long way for multi-vector representations, 2024.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model A little pooling goes a long way for multi-vector representations, 2024

Reference 32

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raw_fallback, observed 2026-08-06T19:30:17.991738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation b534590b-dfc1-41b0-ac5c-ecdd715b5876 · outbound

This paper cites MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings.

Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings

Reference 33

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source=pdf_text observed=2026-08-06T19:30:17.456943Z digest=sha256:638b7bf7ec14326493d587b0da5393d17d71b49d27537e77a76194a51f639590

Pith citing papers

Observation 9b4bef9b-7d07-4a31-8a68-06a18fbf9cdd · 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 Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 66

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T14:11:27.431911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-18T14:09:22.942238Z digest=sha256:26ac413c03f5a3f59563fc746fb92204d60d682906355081be1f3ed560183cca

Observation 35ad1636-c51b-4b63-94af-2b5203797508 · inbound

Guided Query Refinement: Multimodal Hybrid Retrieval with Test-Time Optimization cites this paper.

Guided Query Refinement: Multimodal Hybrid Retrieval with Test-Time Optimization Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-18T09:42:30.776704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-18T09:41:38.974413Z digest=sha256:e00e953a916346c6e6930d9f55aae5325f3932e2c68af3693ed3c6410d33a727

Observation 56ca07bc-fef5-479d-85e0-1e77ad8c1ddc · inbound

Attention Grounded Enhancement for Visual Document Retrieval cites this paper.

Attention Grounded Enhancement for Visual Document Retrieval Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 57

Resolution
verified exact
arxiv_id, observed 2026-05-17T20:55:15.279385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-17T20:53:15.920563Z digest=sha256:80c9bc3b162df425dfe13ed81887e18caa9cd82295f4d60467a687e11eae726d

Observation c852765e-9000-4228-88ff-3c7ed7d26398 · inbound

Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking cites this paper.

Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 24

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T09:36:21.258887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-12T09:36:21.184692Z digest=sha256:fccd7fbe72c062c382ec865c88363e3dcdfdd7a9fa74bcfef6af0a4c96dd5c6d

Observation a10a664d-0a7a-4a59-848d-6f4605e6e7c2 · inbound

CausalEmbed: Auto-Regressive Multi-Vector Generation in Latent Space for Visual Document Embedding cites this paper.

CausalEmbed: Auto-Regressive Multi-Vector Generation in Latent Space for Visual Document Embedding Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 31

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T10:17:44.631336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-16T10:14:15.589472Z digest=sha256:3ed80291d1b9dbc065248e8c8d73e22988c09b82300e24e75548190b6d1a1546

Observation 801f85c4-dcc3-4023-9151-5a1ce50e1c1b · inbound

LEMUR: Learned Multi-Vector Retrieval cites this paper.

LEMUR: Learned Multi-Vector Retrieval Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-22T12:01:30.237549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-22T11:56:41.934325Z digest=sha256:4749240edc38414b654942bc6df9b951bc5fc591a1f119eefc605b1b6df786dc

Observation eb29bfa4-1cda-4f4c-9651-a6da50627910 · inbound

Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval cites this paper.

Col-Bandit: Query-Time Top-$K$ Estimation for Late-Interaction Retrieval Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-03T05:21:48.770461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T05:21:48.770461Z digest=sha256:03635d3fe762ba403f58af488e77454ca12aeb6431a28edaff602c4dc6edef06

Observation d4222c15-8339-4705-b42e-0ff28de935cd · inbound

Beyond Bag-of-Patches: Learning Global Layout via Textual Supervision for Late-Interaction Visual Document Retrieval cites this paper.

Beyond Bag-of-Patches: Learning Global Layout via Textual Supervision for Late-Interaction Visual Document Retrieval Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T08:06:36.201875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-12T01:16:05.097254Z digest=sha256:67156d181c149895388f6bdba0b42ffdfcc3134a1ebdc9722604898357ae0d71

Observation 2d1638e3-3189-4122-8230-148640cc2182 · inbound

MM-Matryoshka: Towards Budget-Elastic Visual Document Retrieval via a 2D Multimodal Matryoshka Training Framework cites this paper.

MM-Matryoshka: Towards Budget-Elastic Visual Document Retrieval via a 2D Multimodal Matryoshka Training Framework Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 91

Resolution
verified exact
arxiv_id, observed 2026-07-02T07:26:45.664327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-06-28T06:59:06.801340Z digest=sha256:4feaf6afcd5bfa5c04b6eeedbf1e67bc5fd4fdd85ba577b7d0b7521e02bd09e7

Observation 14eaa617-84b0-4772-91e9-d905fb2c6733 · inbound

ColGraphRAG: Late-Interaction Evidence Retrieval for Multimodal GraphRAG cites this paper.

ColGraphRAG: Late-Interaction Evidence Retrieval for Multimodal GraphRAG Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-02T14:33:51.465955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:33:51.465955Z digest=sha256:89c27efd8b80b6b8991a9f4fd308953a7c058807e8f054348d444ab1cd3969c1

Observation f6e03987-e6d4-4935-9ac6-fe5ecce24f3b · inbound

KoVRE: Training an Efficient Embedding Model for Korean Visual Document Retrieval cites this paper.

KoVRE: Training an Efficient Embedding Model for Korean Visual Document Retrieval Llama Nemoretriever Colembed: Top-Performing Text-Image Retrieval Model

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T00:17:07.896230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:17:07.896230Z digest=sha256:bd229f0a40b08d85aa3ea51d81c7096eb250743f04cd1d692d682f7b24fdb044