Paper Citation Record · LEDGER

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings

As of 20 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:2505.24782.

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

pith.paper-citation-record.v1
2505.24782 v2

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:35:41.561351Z

measured 57 of 57 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-19T06:31:37.201344Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T06:32:07.564911Z

Reference resolution

55 of 55 outbound references displayed

verified exact2
verified fuzzy1
unresolved52
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6e0125e6-fdfa-4e68-b16f-94020effc594 · outbound

This paper cites online" 'onlinestring :=.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings online" 'onlinestring :=

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:35.090979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45e6eb54-bdbf-46a3-8095-8e1544bf0f8e · outbound

This paper cites write newline.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings write newline

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:35.259050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b539695-fa96-4546-a766-f6a4b6143483 · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:35:43.794170Z

Source-reported events for the cited work

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Observation 933443f1-96d4-40e7-a535-bfe8a36284f3 · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:35:43.587233Z

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 48ad719a-41ae-4183-940b-6b06b6bcec88 · outbound

This paper cites Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:35.831907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cbe95c5-4a0d-4823-83be-f70f04488fa1 · outbound

This paper cites EuroBERT: Scaling Multilingual Encoders for European Languages.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings EuroBERT: Scaling Multilingual Encoders for European Languages

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:35.991876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 878a4fa3-cb1e-4189-b9e1-2f6b4b5f1779 · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:35:43.432768Z

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 6d7922ce-524f-4a90-a3c6-8ba7177cbdd1 · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:35:43.244482Z

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 6dd4677b-02d6-49cf-b549-1bb599c4948f · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3787ed86-7be8-4500-af1c-48f381d8dcd4 · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:36.557147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd97c605-210b-4735-9b55-f094265c0ea1 · outbound

This paper cites M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:36.636972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db539bec-880a-4ff5-811e-cb9fb0e5de00 · outbound

This paper cites From Local to Global: A Graph RAG Approach to Query-Focused Summarization.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings From Local to Global: A Graph RAG Approach to Query-Focused Summarization

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:36.737456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46cbeff5-fb80-4fa5-a926-92b0e5707d0a · outbound

This paper cites ColPali: Efficient Document Retrieval with Vision Language Models.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings ColPali: Efficient Document Retrieval with Vision Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:36.862401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9162ed4e-03f1-444f-b11e-7b1123c872ba · outbound

This paper cites Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:36.956843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9546f77-4c23-418a-aa52-c3c0309dff17 · outbound

This paper cites Towards Trustworthy Reranking: A Simple yet Effective Abstention Mechanism.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Towards Trustworthy Reranking: A Simple yet Effective Abstention Mechanism

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:35:42.551776Z

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 5bae5789-f7e9-4879-ad2f-7be9bb0ecaac · outbound

This paper cites Late Chunking: Contextual Chunk Embeddings Using Long-Context Embedding Models.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Late Chunking: Contextual Chunk Embeddings Using Long-Context Embedding Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.173417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4c5345e-9fa8-48de-8852-286ae79d6512 · outbound

This paper cites Unsupervised Dense Information Retrieval with Contrastive Learning.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unsupervised Dense Information Retrieval with Contrastive Learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.236285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e640e5d4-b9fe-4f74-896e-2ea002dd0792 · outbound

This paper cites LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.310372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aae5b47c-7a72-46e4-ae37-84362ffaadb7 · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Dense Passage Retrieval for Open-Domain Question Answering

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.411316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9132ddf-7f39-4c42-94ef-7e412db3e276 · outbound

This paper cites ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.501961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abb1e945-06d6-40d0-b7b6-8fbaaaab7dda · outbound

This paper cites The NarrativeQA Reading Comprehension Challenge.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings The NarrativeQA Reading Comprehension Challenge

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.597515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35fd1d5d-8c7d-402f-a043-d20bd569ade8 · outbound

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

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.669424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f04928c-6650-4bdb-a612-03e25b100a1f · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.755459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3497bda0-3d56-4b3f-841f-71ba4561057c · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.872311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a327fc0d-c424-43b4-b994-3fddf6dc932b · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.974636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9498298-07a1-4917-9acb-0a3c6fc677da · outbound

This paper cites Unifying Multimodal Retrieval via Document Screenshot Embedding.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unifying Multimodal Retrieval via Document Screenshot Embedding

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.087216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8074480a-de70-4633-bfbc-9ab64e538542 · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.172619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 251184c4-8b22-49dc-81d7-3194339f32c3 · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-07T12:35:43.031925Z

Source-reported events for the cited work

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Observation 461054fd-392b-4fb1-bdd9-7285558d2165 · outbound

This paper cites Contextual Document Embeddings.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Contextual Document Embeddings

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.362337Z

Source-reported events for the cited work

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Observation c9830f65-2d6f-47ca-a927-afd4ab2bf914 · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings MTEB: Massive Text Embedding Benchmark

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.435116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41a7b8d1-f28e-4264-8630-29a8c5495534 · outbound

This paper cites Large Dual Encoders Are Generalizable Retrievers.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Large Dual Encoders Are Generalizable Retrievers

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.568382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d46216c-ebb0-4f07-93c5-735c10480da5 · outbound

This paper cites Nomic Embed: Training a Reproducible Long Context Text Embedder.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Nomic Embed: Training a Reproducible Long Context Text Embedder

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.750679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa2ddcac-9a64-47b2-ba25-0f590c1ae8a1 · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Representation Learning with Contrastive Predictive Coding

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.841556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bf29cc9-9e31-4c8d-b8e3-03d7d764118c · outbound

This paper cites Multi-Meta-RAG: Improving RAG for Multi-Hop Queries using Database Filtering with LLM-Extracted Metadata.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Multi-Meta-RAG: Improving RAG for Multi-Hop Queries using Database Filtering with LLM-Extracted Metadata

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:38.942407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39466cfe-09cb-4a20-8f41-284d15d037c5 · outbound

This paper cites Grounding Language Model with Chunking-Free In-Context Retrieval.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Grounding Language Model with Chunking-Free In-Context Retrieval

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.013312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0cee9502-6127-4fee-9aa4-03847cf047de · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.087282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2f9eafcf-3e5c-4184-9450-e413823bfbcc · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.164467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13ff1823-3cde-41f9-b8c2-eec5a672f14b · outbound

This paper cites Robertson, Steve Walker, Susan Jones, Micheline Hancock-Beaulieu, and Mike Gatford.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Robertson, Steve Walker, Susan Jones, Micheline Hancock-Beaulieu, and Mike Gatford

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:35:42.846289Z

Source-reported events for the cited work

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Observation 3727f3be-0115-482f-9cd9-63c33c6ee6dd · outbound

This paper cites Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.320076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b97503f3-22e2-4991-8ed5-0b6d835db39c · outbound

This paper cites RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.417189Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2dda3bf5-eaf2-46a5-a068-21c73f56e54f · outbound

This paper cites FaceNet: A Unified Embedding for Face Recognition and Clustering.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings FaceNet: A Unified Embedding for Face Recognition and Clustering

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.494432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74b58663-305c-4305-aedd-d3b157c767df · outbound

This paper cites FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-07T12:35:42.087570Z

Source-reported events for the cited work

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Observation 12980dec-912f-4cbe-acbf-579bf6250d4b · outbound

This paper cites BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.686979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 477dcfb1-2139-4930-bc2a-eba929bb92e6 · outbound

This paper cites Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.783146Z

Source-reported events for the cited work

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Observation a6944cb1-85df-4405-82ff-c4ca880da7eb · outbound

This paper cites LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.879972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a341dee-c84b-4134-8fba-e5d267a6da4e · outbound

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

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:39.947606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation daede230-474e-4411-82d4-9d29a8a01e4a · outbound

This paper cites Improving Text Embeddings with Large Language Models.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Improving Text Embeddings with Large Language Models

Reference 48

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Source-reported events for the cited work

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Observation 0e69deab-fb11-46b0-b876-c18007b5be83 · outbound

This paper cites Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:40.425906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c5235dc-39e0-490d-b718-4d3546f5f625 · outbound

This paper cites Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:40.557193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32ecdd65-33a8-4424-9927-2ceaa5cd21da · outbound

This paper cites Retrieval meets Long Context Large Language Models.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Retrieval meets Long Context Large Language Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:40.744965Z

Source-reported events for the cited work

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Observation eb2866fd-216e-4769-af7b-4f543dece219 · outbound

This paper cites Qwen2.5-1M Technical Report.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Qwen2.5-1M Technical Report

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:40.930281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74b5e41b-3903-4c2d-8ff0-63795698cfc3 · outbound

This paper cites an unresolved cited work.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Unresolved cited work

Reference 54

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ba27247-7633-4a42-b260-9fe30bf18a82 · outbound

This paper cites Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:41.298206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfdbaa7f-bb57-45e9-a4bb-78d238f20d31 · outbound

This paper cites GSM-Infinite: How Do Your LLMs Behave over Infinitely Increasing Context Length and Reasoning Complexity?.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings GSM-Infinite: How Do Your LLMs Behave over Infinitely Increasing Context Length and Reasoning Complexity?

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:41.438347Z

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Observation 2d576f3c-b7f1-45f7-9736-6a5458b8a13a · outbound

This paper cites LongEmbed: Extending Embedding Models for Long Context Retrieval.

Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings LongEmbed: Extending Embedding Models for Long Context Retrieval

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:41.561351Z

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Pith citing papers

Observation 6bd3fa9f-96a3-4298-b9ad-2218d14e9d8d · inbound

Should We Still Pretrain Encoders with Masked Language Modeling? cites this paper.

Should We Still Pretrain Encoders with Masked Language Modeling? Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-19T06:32:07.568043Z

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Observation 951eee55-96e3-4a73-9b98-e9c3615384da · inbound

Visual Late Chunking: An Empirical Study of Contextual Chunking for Efficient Visual Document Retrieval cites this paper.

Visual Late Chunking: An Empirical Study of Contextual Chunking for Efficient Visual Document Retrieval Context is Gold to find the Gold Passage: Evaluating and Training Contextual Document Embeddings

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T10:31:04.450710Z

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.