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Paper Citation Record · LEDGER

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval

As of 19 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2411.15766.

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

pith.paper-citation-record.v1
2411.15766 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:02:28.793051Z

measured 62 of 62 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 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

62 of 62 outbound references displayed

  • verified exact0
  • verified fuzzy3
  • unresolved59
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 92c97ab0-fbc0-4626-b909-20e01907f88e · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.613911Z

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.

source=pdf_text observed=2026-08-12T14:02:28.539666Z digest=sha256:19254456b9260c4237396996dff03a43a2d7421d1ef756208181ca9997789239

Observation 7f0432e0-a510-443f-8071-a958303f037c · outbound

This paper cites LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.546032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.546032Z digest=sha256:22c48a895f2dfe3a64a64b804e04299072f483e6649183f3f4e232cbead1255a

Observation ed7311f9-fb42-424d-8513-7a3fcc0ebb22 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.601587Z

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.

source=pdf_text observed=2026-08-12T14:02:28.552483Z digest=sha256:e295aac7c902bdf4750ee70d763980b700dbb74e65e24d2b215ba26d3fb51dc3

Observation 3cbd8b23-e9ac-430c-a1e9-f613290efbcd · outbound

This paper cites Quick Dense Retrievers Consume KALE: Post Training Kullback Leibler Alignment of Embeddings for Asymmetrical dual encoders.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Quick Dense Retrievers Consume KALE: Post Training Kullback Leibler Alignment of Embeddings for Asymmetrical dual encoders

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.557986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.557986Z digest=sha256:ba5ac7ecc1fe40b4da218760525ccb904aebbc99ae3b7cbc4f10fe8a9ad88c89

Observation 687ffc99-6243-4e87-b325-f2ae39f1dd62 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 5

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.589992Z

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.

source=pdf_text observed=2026-08-12T14:02:28.563190Z digest=sha256:eeba4af5fd8c96466637b2957e1671c0ef16931cdccfc2974398a84ad853e88b

Observation 34b0177b-35df-4622-8456-7e99f82ae8c3 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.578064Z

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.

source=pdf_text observed=2026-08-12T14:02:28.568635Z digest=sha256:feffd732140c621106744122e1c95a79dee309243abffd15071a7f9f9be9e8a1

Observation 8e9861ac-4f27-49c6-b034-8fcb6cbcb46d · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.573430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.573430Z digest=sha256:31e473ee2b20e0f86a7668bc99e27f16840712917bae79cd8dfc8aa9c8b5dd0e

Observation efbd5e5a-d9ce-43b3-8a6f-9c818b0491db · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.566076Z

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.

source=pdf_text observed=2026-08-12T14:02:28.579352Z digest=sha256:7667784f09f7ad130c12439602ce47b96e092d9710e4e0993a359ef91e0fc72a

Observation 25f6f087-f799-4b9f-9ec1-b8b4a6b61016 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Distilling the Knowledge in a Neural Network

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.584073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.584073Z digest=sha256:14f0402878b43211015dcb0dac0294ed20c8b335e251479b3f9be9384538436d

Observation 8c7834c2-a852-4828-a302-247466fd4475 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 10

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.553176Z

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.

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Observation 34333926-d7d5-46de-82b7-845768bcfa96 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.541187Z

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.

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Observation 7d490627-e618-4764-8d9f-90b122118322 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.528794Z

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.

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Observation 4e26a82b-76d2-4868-b5a7-e9eb79814eeb · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.516747Z

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.

source=pdf_text observed=2026-08-12T14:02:28.603028Z digest=sha256:542403785c72ea645fe81b56d5588e30a4023356fb6b1ff39d99dd6ffe97d78b

Observation 82bf4eed-5da7-41f3-9f38-4eebb389e9d3 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.504769Z

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.

source=pdf_text observed=2026-08-12T14:02:28.606463Z digest=sha256:7174a561d930ab05b5992fd85a6d6110bf25117f8bee4cb23aac140d27cb86f4

Observation 98e5d9f5-e04a-4d7d-97af-e96b336e07d1 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.610256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.610256Z digest=sha256:580ec59710c62ce2967d12056de0208daa5df6d8c3a6301a4be41b7960c326d8

Observation 45e136b7-addd-4f36-b6d8-7f096f606def · outbound

This paper cites Scaling Laws for Neural Language Models.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Scaling Laws for Neural Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.618666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.618666Z digest=sha256:d15f7d33356536d6bd932b7839cbecc65b19b67a2441aafceda7689cd2ab1b8f

Observation 9a12021e-2eef-4b37-b6fd-decb6d74bb20 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.485539Z

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.

source=pdf_text observed=2026-08-12T14:02:28.622153Z digest=sha256:0e47d894b4075e22ce53cb22c74bf93b354ebe0f5254a1289f7b5b7e4366655d

Observation dabca04a-bcc3-4f22-8c9f-dba2c4c2ca1f · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.473645Z

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.

source=pdf_text observed=2026-08-12T14:02:28.626117Z digest=sha256:ee6130a084fe688e4bdbe137da415984ee15aaf39a2b0efee954e0b7273d8d04

Observation 8e6c282f-fbd8-4473-9881-7a8b12306372 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.461642Z

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.

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Observation 6b11f066-63c6-4a74-83d7-c24d0a097cc8 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.446064Z

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.

source=pdf_text observed=2026-08-12T14:02:28.633074Z digest=sha256:30f047c667bb771da40601b0295ff6eb25c69a85a923c9bb9641fd85cd86588f

Observation a5f6bea7-db59-48bd-af59-139fdf759338 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.433489Z

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.

source=pdf_text observed=2026-08-12T14:02:28.637621Z digest=sha256:f9bb8c1615ce67df01774fe75248650187ae2b0c7ad595cb880c31cca5ec461a

Observation c9fe8151-82a8-4de4-bb9f-4a210fd9b16c · outbound

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

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.640871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.640871Z digest=sha256:9515e99a6ff5f92a16199da60bb08787eea86f44526cd40d03ff339cc145c2a1

Observation 3e41300a-26f2-4217-a2ed-2b3177e2f26c · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.422084Z

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.

source=pdf_text observed=2026-08-12T14:02:28.644631Z digest=sha256:390ed3e2bc10fa3d4346a6b11bd86c70a93b85fa93bc95b3e882769a13f36b84

Observation 9ad82de6-25be-4626-bb91-d4e7555f7939 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.409556Z

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.

source=pdf_text observed=2026-08-12T14:02:28.648295Z digest=sha256:39f226fafba840c06835dddf0102352028405f293cdfb98c1cfe8c96d91b0f08

Observation 446c058b-d4f6-4e45-9851-7d8427474b1a · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.398536Z

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.

source=pdf_text observed=2026-08-12T14:02:28.652176Z digest=sha256:85bb4f3138cf4aea6779db6d722a9101ffcc57e341823810274a910fedd04d51

Observation 7ce0b88f-7331-4492-b9d3-fbd944336d0e · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.656608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.656608Z digest=sha256:9bef015eb20718f52971215d13d4057af1251a87a7998d56e5c094b1d67908ee

Observation 4f0cb4cc-f3a2-441f-bbe1-ae54f7f6ed64 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 27

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.378874Z

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.

source=pdf_text observed=2026-08-12T14:02:28.660387Z digest=sha256:3f2f9d4adfd91950058d689fd1b7a4444a31f41c5f918bfb7b6e4919dc4f533d

Observation 750b3fe8-0546-4111-89f9-b3698378ac42 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 28

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.366999Z

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.

source=pdf_text observed=2026-08-12T14:02:28.665207Z digest=sha256:88d8fd8954979ea13a26b6a9e46bed645a87800fafc901336b47803160cd0e50

Observation bf81440d-ef5a-4589-bcfd-2bb6f2e08c6e · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 29

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.356379Z

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.

source=pdf_text observed=2026-08-12T14:02:28.669283Z digest=sha256:7eff3a222cb0dfa082d31e81e08034e486845cd10e63845b752ff6e3b8df323c

Observation 35be1375-7a25-4389-8915-e50638129905 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.345420Z

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.

source=pdf_text observed=2026-08-12T14:02:28.672898Z digest=sha256:c1cf9426a66fc867d0d8139d660f78d16935697953cabf6a17d30726b80c4a8b

Observation 157c20dd-5df1-402f-b382-b01adc3a063c · outbound

This paper cites CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval CRUD-RAG: A Comprehensive Chinese Benchmark for Retrieval-Augmented Generation of Large Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.676669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.676669Z digest=sha256:7fe80fdc1f3cd06ee645be35de54a6b51d6d42e48732495f5a7c5b1aeff27802

Observation 5d832deb-f0d6-4d50-bbcc-b4e13ad74a97 · outbound

This paper cites Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.680734Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.680734Z digest=sha256:6715a7aafe257a4a4910789b7d3b7576ae2631d2428e83b1fdd9a7f938a8a618

Observation 435682e5-2e2c-459c-92ff-def60a5abcd3 · outbound

This paper cites Task-level Distributionally Robust Optimization for Large Language Model-based Dense Retrieval.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Task-level Distributionally Robust Optimization for Large Language Model-based Dense Retrieval

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.684763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.684763Z digest=sha256:6a580f17192be2092bd5e8f090529826ff3ed46de418787c8aed08767c619830

Observation 90d4418f-67b3-4adb-999a-8ff02d67f5cc · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 34

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.333701Z

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.

source=pdf_text observed=2026-08-12T14:02:28.689107Z digest=sha256:bd429c5d8ff2747efb43f550488a178844eccbf4f6565603884c7d3d26554a9b

Observation 096ca914-8bb7-4958-bfa7-530cf7879f7d · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.695310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.695310Z digest=sha256:bbb1740bfe886ec373c52271be16b6d4575eda0112fb34c1a1232102a5f29338

Observation 009d27fd-a130-4f9b-8e6b-5d91ec600a5d · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.317027Z

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.

source=pdf_text observed=2026-08-12T14:02:28.701718Z digest=sha256:1d9b3398c8cbea30aa4c8161f730f7fd4e4764a0d88b52e838d659257ea209a3

Observation d9405e35-ab0a-4971-a69b-b4163ba6381d · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.305953Z

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.

source=pdf_text observed=2026-08-12T14:02:28.705649Z digest=sha256:c9e4c03017a96fc081be5c813c38c1374dde17762f3842db5f42c1863a54ca4b

Observation 814eeaf2-daea-4690-847d-48fac6ebf28a · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.294182Z

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.

source=pdf_text observed=2026-08-12T14:02:28.709820Z digest=sha256:39705b091e8679a79c47b11978e89f0c2662b774c2cb3eee3541614b8bf6d73f

Observation f1e54c6f-fb5d-49fe-afc2-123ebc06d8ba · outbound

This paper cites Let's Think Dot by Dot: Hidden Computation in Transformer Language Models.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Let's Think Dot by Dot: Hidden Computation in Transformer Language Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.713467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.713467Z digest=sha256:496f2804f51ef2d3aafb1c0bce204351446aaeebed6ca4072836494b587df0be

Observation dc8d1e02-381c-4093-a024-112c5f53a1e8 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.282760Z

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.

source=pdf_text observed=2026-08-12T14:02:28.717090Z digest=sha256:265dcf5f23b689a362de673e33be9ee5a18002dbd7c601debc85851379340c01

Observation 77c4f608-ae16-4cfb-ae71-a66132c0c964 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.271447Z

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.

source=pdf_text observed=2026-08-12T14:02:28.720995Z digest=sha256:f83abcce06143e89b8226be02215cd08a0a2dc1dfe21bd43468c6e000d7e02af

Observation cc51e5cb-474d-4361-b8f3-24eae28d8b48 · outbound

This paper cites 2021.{Zero-offload}: Democratizing{billion-scale} model training.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval 2021.{Zero-offload}: Democratizing{billion-scale} model training

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:02:29.259358Z

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.

source=pdf_text observed=2026-08-12T14:02:28.724750Z digest=sha256:f04b061d7a1b89d47d284329e04744d0d74c0aba816aca5bf1bc42bc3ecdf973

Observation 0f0c27b3-e90e-443a-9cd7-268334b0641c · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.243701Z

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.

source=pdf_text observed=2026-08-12T14:02:28.728458Z digest=sha256:d08e6f4fe3db5766396dca1c0a7ea90c435e1d9481bea99764bc6776d69e4422

Observation 98b4982a-cf99-4ebd-9138-2a1434ecd94e · outbound

This paper cites Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.731958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.731958Z digest=sha256:9814a6e40fe111c39832694b3305c8dd11d3a1beecdf0530e9b717c6cf2c6a00

Observation 4f4dd475-ff55-452a-89ec-bf2c8c69d831 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.735315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.735315Z digest=sha256:3ab21b4fb28df261c048d46a45464ed21af7aa6c8b502b63fad3e1bcd153f696

Observation 0591a7fc-2ef5-4d8e-b70d-7c8da918474c · outbound

This paper cites Improving Text Embeddings with Large Language Models.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Improving Text Embeddings with Large Language Models

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.738233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.738233Z digest=sha256:95b7dbe3e3728e8f65517f00ae9f6451c77a49936a3cb8611958f429c54bf09e

Observation 0be34ca7-502b-4768-991c-1a5ca835820d · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.223911Z

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.

source=pdf_text observed=2026-08-12T14:02:28.741603Z digest=sha256:36ab4feb383c9969a2856670af5b7c951060184c0ceb173943081bab810a7a35

Observation a0d701b6-1535-40aa-a6bb-5421def0640e · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.212818Z

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.

source=pdf_text observed=2026-08-12T14:02:28.744897Z digest=sha256:b7f4b7eea7148bb5c2c6d2338e0fef039ea04f5ca9ddf8a669d0563da2b1dbbf

Observation 64632378-6f47-4799-83ac-743100861104 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.202402Z

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.

source=pdf_text observed=2026-08-12T14:02:28.747985Z digest=sha256:8130c68915389cbe88e17288dcd5ab6689d97d3d31b49c7e288d3a101ef31704

Observation 1bb61577-7438-4fa4-8b9c-c29c5e67a70a · outbound

This paper cites Large Language Models for Generative Information Extraction: A Survey.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Large Language Models for Generative Information Extraction: A Survey

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.751424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.751424Z digest=sha256:bef968cfe093693ac01db72c3c40f0fe2616edd6d5c9bc6ac0f88a85ae597ad6

Observation 9f4c000d-0c9b-42db-9bd5-f2ac36b66a74 · outbound

This paper cites Negative Sampling for Contrastive Representation Learning: A Review.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Negative Sampling for Contrastive Representation Learning: A Review

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.755234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.755234Z digest=sha256:a20796dc8a718eb43d36c699bb847315c9bc9d9434a7ca472059205cb036afb3

Observation c05e6a1d-388c-48a0-b870-b4a164621c34 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.758880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.758880Z digest=sha256:8dc0a591aafd95c4be7f534ad59986cb0e7db76e6882c0090f3c695afca3fbe3

Observation 0de37c3f-4503-4220-8ae2-bccb3bb68e01 · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.171894Z

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.

source=pdf_text observed=2026-08-12T14:02:28.766173Z digest=sha256:959b959786849dd4dcab4645e0d216b9a191d7b63446b49ff6eeb3dfb37181bf

Observation e044395d-a13b-49b8-9592-f290fa7900cb · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.160998Z

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.

source=pdf_text observed=2026-08-12T14:02:28.769680Z digest=sha256:02572971affad4137ee642022c2f724e4da24ff4324fd806fd4a0c932e48e7d7

Observation a06ba546-136f-4fd7-a5e4-ed8074395b15 · outbound

This paper cites NoteLLM-2: Multimodal Large Representation Models for Recommendation.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval NoteLLM-2: Multimodal Large Representation Models for Recommendation

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.773332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.773332Z digest=sha256:c9b57e11227a1f430347acd3dd0bcfcd362c8a07b0e7db2ac7f2b7a32be1fb32

Observation c230ede2-77b7-43e2-9b3a-0ff17c3cc0fc · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.149893Z

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.

source=pdf_text observed=2026-08-12T14:02:28.777058Z digest=sha256:26e593c805c138a4c589b3b8572518489ae1b2a6b09c737a2bd5e9c9d9e6a653

Observation e081dd71-63a2-44fa-b5b9-dd61f244882c · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-12T14:02:29.139813Z

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.

source=pdf_text observed=2026-08-12T14:02:28.781331Z digest=sha256:ac08a3d667044968d69277cb7edef3069a781924822214b0bd5e812e9c97f7b7

Observation 0ea010ee-d85d-41e4-ae35-ab52a21e1962 · outbound

This paper cites A Survey of Large Language Models.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval A Survey of Large Language Models

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.784940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.784940Z digest=sha256:61ecdfe61785a58e5785f8ffff58bb98256f350deb6f50988420461cb4aa6341

Observation 3434de40-ba35-4528-a3ea-9206b98790fc · outbound

This paper cites an unresolved cited work.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Unresolved cited work

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.789063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.789063Z digest=sha256:6e269c7aba71d7ff2ce6f648cfc879dbc1c4fafabc717d710bada8f7e770a67e

Observation 81d03f2b-e7a6-4b7b-a3f5-7dfac89deb82 · outbound

This paper cites Peony" despite the.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Peony" despite the

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:02:29.128625Z

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.

source=pdf_text observed=2026-08-12T14:02:28.793051Z digest=sha256:1cb7069a7423935d9ea084a868cd46ab9eac1181fbf4f7e41f87cbe962de7175

Observation a5577292-e3fa-4dcf-9454-ee8e5a2e61f2 · outbound

This paper cites In SIGIR.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval In SIGIR

Reference 2021

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:02:29.183761Z

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.

source=pdf_text observed=2026-08-12T14:02:28.762502Z digest=sha256:b84e6edc41f770be3748138adf5b8e2576f9d578a79d856bb7444560e1f3ad70

Observation 2aa64f62-e7db-492e-8a6c-465e2155249b · outbound

This paper cites Scaling Sentence Embeddings with Large Language Models.

ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval Scaling Sentence Embeddings with Large Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-12T14:02:28.614023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:02:28.614023Z digest=sha256:977d0d5a66dab2a10cb8012fd1cff7bb0f4b23e2c2bd2799253c1cb246e58313

Pith citing papers

No inbound Pith citation observations are available.