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Paper Citation Record · LEDGER

Unsupervised dense retrieval with conterfactual contrastive learning

As of 12 August 2026, this Paper Citation Record lists 72 of 72 outbound references and 0 inbound Pith citation observations for arXiv:2412.20756.

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

pith.paper-citation-record.v1
2412.20756 v1

Coverage vector

measured 72 of 72 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:18:14.606104Z

measured 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

72 of 72 outbound references displayed

  • verified exact8
  • verified fuzzy5
  • unresolved57
  • parse uncertain0
  • malformed identifier2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2ff6869c-eb8a-4935-871b-f12af0f0c595 · outbound

This paper cites GPT-4 Technical Report.

Unsupervised dense retrieval with conterfactual contrastive learning GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

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Observation 91ea54d8-26ca-43b1-bc2e-60214025f88e · outbound

This paper cites 2008.Models in cooperative game theory.

Unsupervised dense retrieval with conterfactual contrastive learning 2008.Models in cooperative game theory

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 731a03e6-8d50-4279-8365-cab07c046e72 · outbound

This paper cites Towards Imperceptible Document Manipulations against Neural Ranking Models.

Unsupervised dense retrieval with conterfactual contrastive learning Towards Imperceptible Document Manipulations against Neural Ranking Models

Reference 3

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Observation 421d5295-0cf3-4f71-b4f3-d41116f86b9a · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 4

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Source-reported events for the cited work

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Observation 1219b84a-dd34-48fd-9313-da42250a73fc · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation b90d965a-fd64-42b8-a381-eda05bee887a · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0a3c582b-65db-455d-a233-cd29f47d21e0 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 7

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Observation 822adfea-0dda-4b3b-9759-37e2562f3397 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 8

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Observation 332ea8b0-f641-4506-9266-96f35d341c44 · outbound

This paper cites Complementing Lexical Retrieval with Semantic Residual Embedding.

Unsupervised dense retrieval with conterfactual contrastive learning Complementing Lexical Retrieval with Semantic Residual Embedding

Reference 9

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Observation 395f4375-c367-403f-913b-6b14b143caf6 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Unsupervised dense retrieval with conterfactual contrastive learning Explaining and Harnessing Adversarial Examples

Reference 10

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Observation 4021e04b-747b-4282-b4cb-3b7c00000168 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 11

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Observation b5686fd7-0488-432b-a417-154df46382df · outbound

This paper cites Bruce Croft.

Unsupervised dense retrieval with conterfactual contrastive learning Bruce Croft

Reference 12

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Observation d7ac3cb5-9960-4a34-9206-19658facd7a8 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 13

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Observation 73b55f04-fef6-451e-a60c-ed7007ad4eba · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation cc8bad2a-cb6d-4688-bebc-880a7f061000 · outbound

This paper cites Certified Robustness to Adversarial Word Substitutions.

Unsupervised dense retrieval with conterfactual contrastive learning Certified Robustness to Adversarial Word Substitutions

Reference 15

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Observation 2d42c020-c0cd-4b58-90eb-0d21246061b5 · outbound

This paper cites Johansson, Uri Shalit, and David A.

Unsupervised dense retrieval with conterfactual contrastive learning Johansson, Uri Shalit, and David A

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation b0f03748-b45a-43b1-bdc2-b3e87dd432f5 · outbound

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

Unsupervised dense retrieval with conterfactual contrastive learning Dense Passage Retrieval for Open-Domain Question Answering

Reference 17

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Observation 62e25d29-c536-4ef7-9a42-e16af438a9a7 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation eb9bb206-b87c-4aaa-9281-54672a8251dd · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 19

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Observation 8f8eb289-b863-4cb6-9830-a33e0d17bc01 · outbound

This paper cites Kusner, Joshua R.

Unsupervised dense retrieval with conterfactual contrastive learning Kusner, Joshua R

Reference 20

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 27948dd0-ad23-4ce2-b249-11758bfb75f9 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 21

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Observation 697f1ee6-3300-498f-8e10-c2064c83f018 · outbound

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Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 22

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Observation 15c5851d-cac4-4745-96ef-af072afe94ca · outbound

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Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 23

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Observation a14aa693-9dee-4700-8cda-6537982e3cba · outbound

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Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 24

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Observation 4c26b027-1a95-46cf-b6a8-1d225a863b0a · outbound

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Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 25

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Observation f40a4db3-be22-49ca-aa9c-6eb3beeee68c · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 26

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Source-reported events for the cited work

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Observation 6328e2f9-b91f-4376-b78c-ceff8be0a206 · outbound

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Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 27

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Observation bf937234-47bf-4655-a13a-d866076a1f27 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Unsupervised dense retrieval with conterfactual contrastive learning RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 28

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Observation ec194b43-6213-4ac5-9130-16cc91144018 · outbound

This paper cites On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective.

Unsupervised dense retrieval with conterfactual contrastive learning On the Robustness of Generative Retrieval Models: An Out-of-Distribution Perspective

Reference 29

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Observation 61a55db0-4370-491e-b886-29778dca075d · outbound

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Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 30

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Observation 726a70da-9cdc-4c7c-b7b0-b7dc0e1d8503 · outbound

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Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 31

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Source-reported events for the cited work

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Observation c71e9755-bd07-479e-861f-9c0a0d0b57fc · outbound

This paper cites Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models.

Unsupervised dense retrieval with conterfactual contrastive learning Topic-oriented Adversarial Attacks against Black-box Neural Ranking Models

Reference 32

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Observation 0ea2c938-ce17-4361-bd12-4fc1d0cc99c0 · outbound

This paper cites Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off.

Unsupervised dense retrieval with conterfactual contrastive learning Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off

Reference 33

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 5650fe0f-1a77-4764-b350-6b6d762bd3fa · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 34

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Observation 03de2611-3c75-48ea-a50a-123b9d19a65f · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 2868e35f-d51c-442c-8baf-815ccd90ae42 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 36

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Observation 500e0429-f314-45d2-99e0-8e829f358d14 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 37

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Observation 2406030f-8440-4d00-a0b6-1630416b3334 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Unsupervised dense retrieval with conterfactual contrastive learning Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 38

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Observation efe95b86-4202-4ee3-a563-ee626a15df50 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 39

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malformed identifier
raw_fallback, observed 2026-08-10T23:18:16.177418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.467578Z digest=sha256:a6f64bda1fcf9ca53c04c6dd7751cc3738f1dcec29a106b1a3dc768096b01dde

Observation ddb5da94-b5d7-41f1-a8d7-4c7ec19cdaac · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.471577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.471577Z digest=sha256:bf21c7ab5c9843d70a38ba177a0243ff0d6847f837e83c092b55601e4747cebb

Observation 43070cce-7cf5-45d3-8db0-78a3320e67a9 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.475373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.475373Z digest=sha256:625b20bea2249e0adfef188e8fb13caa01475cedc5751f519a4750ba333f7457

Observation 41869c75-53ed-410e-98ce-6658fa152e9d · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-10T23:18:16.150570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.479412Z digest=sha256:b153dca3a902e47ba861879aa0775c5c6445664a2d4d32d4280ba9387e0b11a6

Observation e48e33ca-2ee9-41ad-87b1-d0d07059632c · outbound

This paper cites Passage Re-ranking with BERT.

Unsupervised dense retrieval with conterfactual contrastive learning Passage Re-ranking with BERT

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.483821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.483821Z digest=sha256:18cccf50e4aa15dc13e949b10cc04b954af0a6c17eed30e5d36cc57e69c10077

Observation 084de725-e948-4cf1-b5d3-79f7513b9208 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-10T23:18:16.136439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.488742Z digest=sha256:6374267b209f169f099b08740a41cf13f7d7c16caf0db158970de441dc70f1c2

Observation 370a7743-fc15-4a02-bf76-45410d6d8b1c · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.493147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.493147Z digest=sha256:0f0a9df66356f256f52dd65e27807076a47f4255e337ce2f5b4b0e77f837bcf7

Observation 52bf8090-fa64-4e58-a05e-76470023b036 · outbound

This paper cites Bruce Croft, and Mohit Iyyer.

Unsupervised dense retrieval with conterfactual contrastive learning Bruce Croft, and Mohit Iyyer

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:18:16.122635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.497999Z digest=sha256:cc847c36bedf7333c7c28ef99d4464f0bc13342cfe3996e613eb663c4e539e69

Observation 90ac18ea-0a92-4dec-80e5-81f83e7e3b96 · outbound

This paper cites RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering.

Unsupervised dense retrieval with conterfactual contrastive learning RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.505790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.505790Z digest=sha256:1ae5b0cf1ae05ae199e8d573b559faf8574206d4c6152ec170755cf81c0b891a

Observation fe46f21d-0950-445d-a84b-d1e8e2c6de7e · outbound

This paper cites Certified Defenses against Adversarial Examples.

Unsupervised dense retrieval with conterfactual contrastive learning Certified Defenses against Adversarial Examples

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.510095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.510095Z digest=sha256:a4ddc2a503f800da42ea2f7d395fd6b12032460406085cab0ec518b7a4336cb1

Observation 70c8eecc-a590-4321-90d5-a0b89b564a6e · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-10T23:18:16.108866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.514383Z digest=sha256:8b75d72534e731b165e2d779b0807fc0ba18eff23e37194a1092e4784dd07f94

Observation a7a93cf9-be20-4d11-a319-e402f8a2166e · outbound

This paper cites Why should i trust you?.

Unsupervised dense retrieval with conterfactual contrastive learning Why should i trust you?

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.518531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.518531Z digest=sha256:5edd3a517bfd86eb18ac96e1172d2145d95f3cdc4be5864eb3a3e48fdf52eb1d

Observation 3b105656-c3c9-4cfe-b9ca-07b295e1b93e · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-10T23:18:16.087572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.522350Z digest=sha256:5ff301c4d61f5079ba1892af53c9dbe2a54602524eed8eb3481c1346b8fabb5e

Observation 54572386-265a-444b-a8d3-1708f5c25a6a · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-10T23:18:16.074216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.526406Z digest=sha256:75ce86d22f402e77cddb6c8ca3b047430eb6c9c3160b7cb18639a2aea759b001

Observation 2fd8c7bb-91f6-4d2c-88fe-899e84ab69db · outbound

This paper cites Evidentiality-aware Retrieval for Overcoming Abstractiveness in Open-Domain Question Answering.

Unsupervised dense retrieval with conterfactual contrastive learning Evidentiality-aware Retrieval for Overcoming Abstractiveness in Open-Domain Question Answering

Reference 53

Resolution
verified exact
local_arxiv, observed 2026-08-10T23:18:15.023851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.530124Z digest=sha256:3f9fe77383845a4fdf1fe22c263c3b5ee3aa122b724c500f01b24047291ef31d

Observation f39cb4d2-356c-4960-a06e-3f406ac366df · outbound

This paper cites Intriguing properties of neural networks.

Unsupervised dense retrieval with conterfactual contrastive learning Intriguing properties of neural networks

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.534185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.534185Z digest=sha256:0a59bda0a63ee85c6f0e81dc4da7b8c4082243968f32134a7cc813f0282e33bd

Observation 447fff53-c3da-44e7-bd5a-3cab8547b399 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 55

Resolution
verified exact
doi, observed 2026-08-10T23:18:14.658996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.538423Z digest=sha256:1a54cc9016dff4e337dcee8ce560dd3815abd165014e676acc1a1d4c64d6f383

Observation d79978ad-b7aa-4088-a023-ac793b7d73a2 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.542302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.542302Z digest=sha256:3a8a45fe3da2ec8cf307858c5f0a5e4069bd9888edee8a77a42ccd035038ef1e

Observation 1f1cf634-dceb-40de-9f99-d6084c07234a · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.546296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.546296Z digest=sha256:08cfe934084bb5b020e89d600bcef1d02552a10bbbb2f71dcbbb94ceec3afa60

Observation bca67eba-b43f-401c-8624-8b24343de6d5 · outbound

This paper cites On the Convergence and Robustness of Adversarial Training.

Unsupervised dense retrieval with conterfactual contrastive learning On the Convergence and Robustness of Adversarial Training

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.550398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.550398Z digest=sha256:af0841d67d5e918a875174e1cd5f222e7c6218a74035621ca10bc37bfa90799c

Observation 59253d4d-150d-494d-bd06-ae000723bd14 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-10T23:18:16.060413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.554627Z digest=sha256:e41c8c19aabefb357187c6e3937304c28bca4685369b1cca377306ad8b30397b

Observation a2273358-4263-458e-a366-207d09a26c1a · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.559127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.559127Z digest=sha256:d3c48dfbdd25a599f0c44f28b648804ccc2679cfcba2cd3fe651d393ef7e4dac

Observation 72b1d7fb-af84-4912-a12f-47f40a0e9daf · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 61

Resolution
unresolved
raw_fallback, observed 2026-08-10T23:18:16.034679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.568221Z digest=sha256:fbcc68b219acdcce0a3e27ce8c6676bdcfa744e8143f0ea627c54f9d0692bd4e

Observation 48a9f268-c400-4455-83d6-44b2fabe2406 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.572612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.572612Z digest=sha256:bf8f45c40b09558b171d4dbbcb411b320c4a3a1258a7313cec8a1555fec260e7

Observation 0293c3e0-22a6-4d1b-a7de-306efb477886 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Unsupervised dense retrieval with conterfactual contrastive learning HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.563835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.563835Z digest=sha256:913d15261ff14787f4ff7e4ac794a80dfe7ffa19d8351bca6404fd3f45cb261a

Observation c8dac8a3-074f-4ac9-a9cd-50a655b2872d · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.580801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.580801Z digest=sha256:7fd5c7a963b7c57f336c3a90a4964a320ca5ec5332134d1b154d7a814be82fda

Observation 871ef13c-2df5-4fae-837f-cce7396c410e · outbound

This paper cites Bennett, Junaid Ahmed, and Arnold Overwijk.

Unsupervised dense retrieval with conterfactual contrastive learning Bennett, Junaid Ahmed, and Arnold Overwijk

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.590194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.590194Z digest=sha256:cbd3550408db7ad78ebc6aec778cfb65bc8afcf0cae971ddbd35cd09f2f23054

Observation 01a86af2-1845-45a3-a6d0-27ae574dc2c9 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 66

Resolution
unresolved
raw_fallback, observed 2026-08-10T23:18:16.020048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.576733Z digest=sha256:674391d9177dbb931a3623be9e5f1ccc98fe5f56dff60144e202e5bef8ee73ec

Observation 1bc6b4df-6fb9-4277-8897-99db89391b2a · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 67

Resolution
unresolved
raw_fallback, observed 2026-08-10T23:18:15.986914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.601190Z digest=sha256:7be7b4373d7f94ce3d8727becd213c38c22c79e052ccb620cafff4db06609288

Observation d2c07cbd-19fe-4ca9-a07b-a2bd6abd3cc3 · outbound

This paper cites SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions.

Unsupervised dense retrieval with conterfactual contrastive learning SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions

Reference 68

Resolution
verified exact
local_arxiv, observed 2026-08-10T23:18:14.744159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.606104Z digest=sha256:6cdea89805356f292794227d935f2d2552de3616f2c3dff9ac728a90c5a8d401

Observation a8a7119d-5975-4751-ba8f-6eabf44b568a · outbound

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

Unsupervised dense retrieval with conterfactual contrastive learning Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.594670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.594670Z digest=sha256:5bb022661ad52d22560b1839e1e487608a792227f8227228fc078f19f4dcfebf

Observation 9f6fbab9-2742-4dbc-b783-37def24ec618 · outbound

This paper cites an unresolved cited work.

Unsupervised dense retrieval with conterfactual contrastive learning Unresolved cited work

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.585299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.585299Z digest=sha256:d5b5634d6b2d0325c019a4437ad16b2cca958014c8f6ac7180eb3a10777b750e

Observation 4da935df-ed13-4652-b40d-483101057ad1 · outbound

This paper cites In Proceedings of the 36th Interna- tional Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA (Proceedings of Machine Learning Research, Vol.

Unsupervised dense retrieval with conterfactual contrastive learning In Proceedings of the 36th Interna- tional Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA (Proceedings of Machine Learning Research, Vol

Reference 2019

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:18:16.335444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-10T23:18:14.346258Z digest=sha256:90256d036d01a3cf4a08bcbe445e0070ec3f066f418fa35bc43cfb8d392685a5

Observation 5a3a2340-361a-4e81-a054-afa7112c12ea · outbound

This paper cites In Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, SIGIR 2020, Virtual Event, China, July 25-30, 2020 , Jimmy X.

Unsupervised dense retrieval with conterfactual contrastive learning In Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, SIGIR 2020, Virtual Event, China, July 25-30, 2020 , Jimmy X

Reference 2020

Resolution
malformed identifier
no resolver link, observed 2026-08-10T23:18:14.501870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.501870Z digest=sha256:266fa768d01d857f2301cf55dfa235e6f0ce9ff9c94bd198390ccece75354bb8

Pith citing papers

No inbound Pith citation observations are available.