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Paper Citation Record · LEDGER

The Embedder's Dilemma: LLMs Are Better, but at What Cost?

As of 18 August 2026, this Paper Citation Record lists 100 of 106 outbound references and 0 inbound Pith citation observations for arXiv:2608.12875.

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

pith.paper-citation-record.v1
2608.12875 v1

Coverage vector

measured 100 of 106 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:37:01.523247Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

100 of 106 outbound references displayed

  • verified exact1
  • verified fuzzy28
  • unresolved71
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ae4ff998-20c5-42c2-a1d3-2a725c6433c3 · outbound

This paper cites OpenAI GPT-5 System Card.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? OpenAI GPT-5 System Card

Reference 1

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source=arxiv_source observed=2026-08-15T21:37:01.083703Z digest=sha256:3aa576debbbe0dc4d4d45a92c2a02edb25598273c854dbd40864cafa2df94adb

Observation 855299f5-830b-46fa-94ef-2c45c32d2229 · outbound

This paper cites The Llama 3 Herd of Models.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? The Llama 3 Herd of Models

Reference 2

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source=arxiv_source observed=2026-08-15T21:37:01.088983Z digest=sha256:59c8fcaf849387d7f05f747782345d93eb52f49488868d8e16b45ae6e19dc506

Observation 3a5a40a6-c248-45c0-9364-30527f67d643 · outbound

This paper cites Qwen3 Technical Report.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Qwen3 Technical Report

Reference 3

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source=arxiv_source observed=2026-08-15T21:37:01.093326Z digest=sha256:f9a89cf65284efccec87b187538dd1de86e628def50ff1ab5431e5a294fca7a0

Observation 6ad328f2-ccba-4311-bc7e-994ebba030c4 · outbound

This paper cites 2025 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2025 , eprint=

Reference 4

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source=arxiv_source observed=2026-08-15T21:37:01.097848Z digest=sha256:ba231cca5e936f714059f47f53e7f7498626755fb0408e80de915b35a254b9ba

Observation 37455dcc-b1e4-4af9-84ff-2bb4b1b0f5e1 · outbound

This paper cites 2025 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2025 , eprint=

Reference 5

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source=arxiv_source observed=2026-08-15T21:37:01.102228Z digest=sha256:79f7494b49f1b98655742b284a05de7f36a7a0b492c3de11340fb0c14a27d724

Observation 73527b16-bce6-464d-b89e-8301dab1b509 · outbound

This paper cites ACM Transactions on Information Systems , year=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? ACM Transactions on Information Systems , year=

Reference 6

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source=arxiv_source observed=2026-08-15T21:37:01.106829Z digest=sha256:6a243b734ef7f3b3d0140fc46f4c6fd2a0a4967016d8b4bfb7db10ed21ee783d

Observation f4b4c215-df1e-4d52-b70f-4b9b84c6b41c · outbound

This paper cites Humanity's Last Exam.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Humanity's Last Exam

Reference 7

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source=arxiv_source observed=2026-08-15T21:37:01.111106Z digest=sha256:8b7aec363eec9491139dc70b255bf306f4c7fc570a2900fd2907c320ce7abd68

Observation 5ec088fd-97bc-4708-858b-fa4d8505af05 · outbound

This paper cites Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics , pages=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics , pages=

Reference 8

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source=arxiv_source observed=2026-08-15T21:37:01.115508Z digest=sha256:724aedf4939c557219f37aff8db6c0479675062376c1d1075d1b6ea4865b5dd6

Observation 0cf45c39-ebe6-4417-ae8d-7e713436c0af · outbound

This paper cites 2025 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2025 , eprint=

Reference 9

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source=arxiv_source observed=2026-08-15T21:37:01.120875Z digest=sha256:e2676eb0a09f3bccfad58fe0b5b641f1dc148ec8520cd25ceca00314ee513d6a

Observation 41c0724b-0a5f-46b2-b47e-9d29da98cc77 · outbound

This paper cites 2025 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2025 , eprint=

Reference 10

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source=arxiv_source observed=2026-08-15T21:37:01.124770Z digest=sha256:a7c75cbf83212a60d1c78050d3cef713e69b9fe6f8c5382c44d4b5bc3a3c1292

Observation ba378468-b00c-4786-ac56-f51d63ad8ed2 · outbound

This paper cites 2026 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2026 , eprint=

Reference 11

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source=arxiv_source observed=2026-08-15T21:37:01.129097Z digest=sha256:33315f8966b0e23bfafd3fa3fc47a339e813803d940d364fa379087115d95f0a

Observation 252cbe4f-cbcf-4502-aac7-0aa7386349ce · outbound

This paper cites 2026 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2026 , eprint=

Reference 12

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source=arxiv_source observed=2026-08-15T21:37:01.135147Z digest=sha256:1eae2ba1dd3aed253d5a7ff3ebd32a489db8e0a57dfc702eb79a50bc35c4045c

Observation c8a5e49b-0cde-46b4-987a-3d5e147a8194 · outbound

This paper cites 2025 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2025 , eprint=

Reference 13

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source=arxiv_source observed=2026-08-15T21:37:01.139921Z digest=sha256:df4bed9cb36c7a307a2fab1420be598853b5d1da1b96c36ff869343e5020dbf8

Observation bef69da0-bb3c-4b44-b2f8-4a597bc7fdbb · outbound

This paper cites Sentence-.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Sentence-

Reference 14

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source=arxiv_source observed=2026-08-15T21:37:01.144849Z digest=sha256:c5f6692e8f9d9917920a4f1dc9f1755ea1d9c0583c0c1db68bc800b3c2cfb1d5

Observation 3e2ab919-26ec-45ed-963e-d62d23255eaa · outbound

This paper cites 2022 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2022 , eprint=

Reference 15

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source=arxiv_source observed=2026-08-15T21:37:01.149350Z digest=sha256:c8a4449f456234c3dd1e795ad4350ad1c2fd2f0ca02b42a5362546b422361ed2

Observation 16ec453a-9ddd-4c49-968e-fe1f6ed75330 · outbound

This paper cites 2024 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , eprint=

Reference 16

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source=arxiv_source observed=2026-08-15T21:37:01.153793Z digest=sha256:aacb13c8b70ffe25d229e7c2dba95c5317492338e89332d3586b2df08e706539

Observation 8e233e38-520c-438c-afa0-05a5c0bfecba · outbound

This paper cites 2023 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2023 , eprint=

Reference 17

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source=arxiv_source observed=2026-08-15T21:37:01.159050Z digest=sha256:ccb5b90e08eb1e79495309f0ad7b3d287e2b721dd2c9de3ed2303ccc5ae36967

Observation 26b5f8e1-449c-4875-a35c-e952952e9b5f · outbound

This paper cites 2024 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , eprint=

Reference 18

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source=arxiv_source observed=2026-08-15T21:37:01.163490Z digest=sha256:328d9df7eae35aa4d153b33a3137d7dcd6338fbbfe2980e9feaaa1835a5bb92d

Observation 764c5d9c-98e6-4f0a-acbf-65121ab7f060 · outbound

This paper cites 2024 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , eprint=

Reference 19

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source=arxiv_source observed=2026-08-15T21:37:01.167699Z digest=sha256:88d174fa4dee017c475ae6083dc2afeb05991fc3fc883bffdbb6e950220fccd1

Observation 4a754ffc-3d3f-4748-8b73-8f492fec5854 · outbound

This paper cites 2024 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , eprint=

Reference 20

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no resolver link, observed 2026-08-15T21:37:01.172329Z

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source=arxiv_source observed=2026-08-15T21:37:01.172329Z digest=sha256:95ca8fc83759b09c5e16d56168ab057bdd57131430f99a7a4d4f6c75b0093694

Observation aaabbb91-f8e1-448d-ae23-81699ea6df2a · outbound

This paper cites 2025 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2025 , eprint=

Reference 21

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source=arxiv_source observed=2026-08-15T21:37:01.177659Z digest=sha256:ea5e8dd9237d1fb09c533ea21df423b306d1a55647655f3795f40a652debd710

Observation d273c932-1b2b-459d-9a67-33a9bdd809ec · outbound

This paper cites an unresolved cited work.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Unresolved cited work

Reference 22

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source=arxiv_source observed=2026-08-15T21:37:01.182840Z digest=sha256:0d95f62cdfb91cd3b0f02d3e02970e5e112cd4e5ebc1a559ba4efdd146be9608

Observation 1600072f-ed8f-4a84-8263-c8d8c334d337 · outbound

This paper cites 2023 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2023 , eprint=

Reference 23

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source=arxiv_source observed=2026-08-15T21:37:01.187232Z digest=sha256:4312ef4b9e1312af7d729926905210051e28e2f93d064671027f027eef5b591b

Observation c99ec19a-4cfb-4839-94a5-14b8b35dd15f · outbound

This paper cites Can Long-Context Language Models Subsume Retrieval,.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Can Long-Context Language Models Subsume Retrieval,

Reference 24

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source=arxiv_source observed=2026-08-15T21:37:01.191506Z digest=sha256:0a6767391231a021c327aeb16d937509fef27ec541b08e4f3de0f9a9764c8851

Observation 16122feb-8240-4bcf-9c15-07e6fc391572 · outbound

This paper cites SGPT: GPT Sentence Embeddings for Semantic Search.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? SGPT: GPT Sentence Embeddings for Semantic Search

Reference 25

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source=arxiv_source observed=2026-08-15T21:37:01.195989Z digest=sha256:4ec9990d076454ff217a79fc3ede18e6b5f68182f4d82ce9534bdad49275a06b

Observation d02bbb46-db68-49b2-9b22-d1cd093b6c77 · outbound

This paper cites 2023 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2023 , eprint=

Reference 26

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no resolver link, observed 2026-08-15T21:37:01.201206Z

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source=arxiv_source observed=2026-08-15T21:37:01.201206Z digest=sha256:8760f9f2cbd0614d5e9e6fd7bfcbc1b3c8d44ddfdf56cf059e690d7ba2751aa9

Observation a0656260-378f-4882-976f-c9f194dd33bb · outbound

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

The Embedder's Dilemma: LLMs Are Better, but at What Cost? LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

Reference 27

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source=arxiv_source observed=2026-08-15T21:37:01.205498Z digest=sha256:b8c2251652167a2560e137c6f840669fdfabad313266a9bddda5d21d135095a7

Observation 3243fbb0-046d-4357-bb8d-be7179e51a6f · outbound

This paper cites Repetition Improves Language Model Embeddings.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Repetition Improves Language Model Embeddings

Reference 28

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source=arxiv_source observed=2026-08-15T21:37:01.210656Z digest=sha256:9b55827ecd6f9c75e37140beda991343224ca5a836bebf5956616c22a26daffa

Observation 0c9ee3e4-59b2-4b90-9f26-8e8d9abf23ca · outbound

This paper cites Green AI.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Green AI

Reference 29

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source=arxiv_source observed=2026-08-15T21:37:01.215234Z digest=sha256:baa89b4c000968aa08266d5501d801bfdb333e78ed3f3abc4681f756120fed9e

Observation da37eb54-13b0-48c7-b8cc-c7f5b252818a · outbound

This paper cites Energy and Policy Considerations for Deep Learning in.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Energy and Policy Considerations for Deep Learning in

Reference 30

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source=arxiv_source observed=2026-08-15T21:37:01.220934Z digest=sha256:8616bcb5a79671e05f1fc54560d12ea4b6cc180f8566c862b43e364855b63755

Observation 5a5b9cb0-bb50-462a-bd12-d1c9bd59b82f · outbound

This paper cites 2021 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2021 , eprint=

Reference 31

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source=arxiv_source observed=2026-08-15T21:37:01.225139Z digest=sha256:c48fcfc4e31f44a5b8511d46b701abaa414a6cee95042f589c38c726f7f4b595

Observation 1d96dd29-4d33-4019-b441-fa50a9a38df1 · outbound

This paper cites FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance

Reference 32

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source=arxiv_source observed=2026-08-15T21:37:01.229370Z digest=sha256:a315a583bb0e7a1f2184b094ea34e056c95690d443136ce1b78334bd57bf0dc7

Observation 897b92b3-3160-4319-ae8c-0c4e2b0b2df7 · outbound

This paper cites Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track , year=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track , year=

Reference 33

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source=arxiv_source observed=2026-08-15T21:37:01.234094Z digest=sha256:7988dc96e52165646c7c25d447c70afe3acb3404b361b5f83c7f657ca999802e

Observation f2ec7561-455c-4481-a9e2-24ffa0239a4d · outbound

This paper cites Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing , pages=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 34

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source=arxiv_source observed=2026-08-15T21:37:01.238412Z digest=sha256:3051f869ae5a723a7cb3733a238a3fe1004d1db78e7c5b67181468b2a55c5fc2

Observation e84f3cb2-720f-4e8d-b1ba-5aad3050c4e4 · outbound

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

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Retrieval-Augmented Generation for Knowledge-Intensive

Reference 35

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source=arxiv_source observed=2026-08-15T21:37:01.242708Z digest=sha256:2e73201e422d385b718f9fbea4c743d69c661eed2fa5a23250297f1cbd1ffe90

Observation ef0dc68b-61b8-4d20-848a-e3be34c6d3f1 · outbound

This paper cites 2024 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , eprint=

Reference 36

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source=arxiv_source observed=2026-08-15T21:37:01.246967Z digest=sha256:176ca4e141ee6d22a3c049354620916c88f404838bea621bd1068d7ee1cabe99

Observation 27ae7aa9-b3c7-43fe-917e-4807f2d6639f · outbound

This paper cites an unresolved cited work.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-15T21:37:02.495544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.251229Z digest=sha256:8c30339dff633f2b846ad1e1cf37a68a4723caa52921be0b8014ed39f22b1f20

Observation 2b21ade4-4866-4195-ad18-1af8c5c239a6 · outbound

This paper cites 2022 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2022 , eprint=

Reference 38

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source=arxiv_source observed=2026-08-15T21:37:01.255516Z digest=sha256:34f35da4e66c39117b3cf18c457352cb13eabe8fd6ec1b6eb51b664f6d344e40

Observation 8110a7a4-d576-41c6-a73c-eac1284d09a8 · outbound

This paper cites 2020 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2020 , eprint=

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.259770Z digest=sha256:051d2c12a6ce75069322ef902de7c4ed5783da37d6b2b0e4d5156304716c98d3

Observation bcd3f3cc-c845-406a-802e-f5e4c07d51ea · outbound

This paper cites Advances in Neural Information Processing Systems , title=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Advances in Neural Information Processing Systems , title=

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.474385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.263948Z digest=sha256:9c8d7ac1e016f06db3f4c87b3a474c4c8cb32f64f6ab867db57c28d01d4c1e3f

Observation 3da7826a-3ed9-4728-b4f1-78608029b937 · outbound

This paper cites 2019 , url=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2019 , url=

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.268535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.268535Z digest=sha256:f36ad43a569525950038121be823f1ad67415393a560ba4966c1989d8b5a768d

Observation ec3b8f3c-41e5-4931-af10-f194166b2e21 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Advances in Neural Information Processing Systems , volume=

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.272587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.272587Z digest=sha256:87612dadd44985035793da8486709c30446a20867e0c4e709ac3fc2126e8c622

Observation 60123f80-a341-41a7-b6f1-8944c12245c8 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Advances in Neural Information Processing Systems , volume=

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.276683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.276683Z digest=sha256:0f2d0aee11725f786883166b61b8f6570b0bb165ba58f65a207c0f7d136dcd8d

Observation 87351ebf-32d3-46f4-899e-e78ed9d21df7 · outbound

This paper cites 2506.20923 , archivePrefix=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2506.20923 , archivePrefix=

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.280687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.280687Z digest=sha256:e4afea2b3ea1a578c133af77677a195b2d3450f93d3b15824be81513946c5eab

Observation b32b00dd-aa01-4761-ab03-0208e8818c67 · outbound

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

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.284865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.284865Z digest=sha256:a49263472f5954fc95d76e0ef1c867c815b91c8c18d767d31e08cfd4ff59aa3d

Observation 542f48c2-6cad-496e-a7a5-9f69c9a5eb19 · outbound

This paper cites jina-embeddings-v3: Multilingual Embeddings With Task.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? jina-embeddings-v3: Multilingual Embeddings With Task

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.447980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.289540Z digest=sha256:9be15f27cf537e24b53c78f46e62e2d089d151f5b7723d20d4b69ac92e5643ba

Observation 3780ae5a-b235-4ef1-aa03-c62c6e1ff00f · outbound

This paper cites 2024 , url=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , url=

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.293660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.293660Z digest=sha256:c2825a30e437fc65c6e1518c26351eed4864707480e462df6bd13aad479490ea

Observation 46c74d85-165d-4ac0-a165-02be8961538d · outbound

This paper cites Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.297834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.297834Z digest=sha256:14892fc91fdcc40352126c1c0bbcd8a59ac50adb5e293dbfbc51401c555e2fbc

Observation b1aefd97-fd05-4856-a66f-dc6532ae5d42 · outbound

This paper cites Findings of the Association for Computational Linguistics:.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Findings of the Association for Computational Linguistics:

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.432981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.302203Z digest=sha256:a8dc28facf06a4f9df2ae2c277c2f0ce166f7263e56be8d6f9bf270ba3e8f29c

Observation 99253ee4-9149-4b27-a5d5-53cb5a98d807 · outbound

This paper cites Cost-Aware Model Selection for Text Classification: Multi-Objective Trade-offs Between Fine-Tuned Encoders and.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Cost-Aware Model Selection for Text Classification: Multi-Objective Trade-offs Between Fine-Tuned Encoders and

Reference 50

Resolution
verified exact
raw_fallback, observed 2026-08-15T21:37:01.858646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.306444Z digest=sha256:b2e3487c41a2285f53cf009f5444cda8f08a2cc0c3b21ad6e9b569a7dce7efbe

Observation 33c02e6b-30f7-42ea-9069-62758716826d · outbound

This paper cites Fine-Tuned `Small'.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Fine-Tuned `Small'

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.423485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.310567Z digest=sha256:630bb9da0b540d1aca422eed5e50d8f9c148df6bfd67a89a53b47ad63238d76d

Observation 32edaf2f-3fb8-410c-b794-2902e73d00ac · outbound

This paper cites BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive Retrieval

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.314760Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.314760Z digest=sha256:9b2a7da475d3c872b74424ac79aa9280124d8b1c8f93766fcd3c21a558fb7181

Observation b87e48f5-32b8-425c-9ecc-eb57de13858c · outbound

This paper cites 2025 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2025 , eprint=

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.414599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.319143Z digest=sha256:c788d36005ac25b3bc90627524d14e01703040123c5b6224bfdc29b8be2803ac

Observation 8d190c2a-9d7b-4af9-b162-1436af760b1e · outbound

This paper cites Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Retrieval Augmented Generation or Long-Context LLMs? A Comprehensive Study and Hybrid Approach

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.323413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.323413Z digest=sha256:440667d4783b2db689b70f1a73835f97dd9e6481167d82962293f6e3e6b34659

Observation 9b405c16-e6e4-4896-a378-8588f18dbd12 · outbound

This paper cites 2025 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2025 , eprint=

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.404636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.327838Z digest=sha256:6609b77768e93de25c0f98f9fb3102c45d44c59f6814569edbd4a41ec0cfc3d3

Observation 0dc0da09-e7b8-4117-9729-9be4d96940d9 · outbound

This paper cites Proceedings of Machine Learning and Systems , volume=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Proceedings of Machine Learning and Systems , volume=

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.394888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.332088Z digest=sha256:2d6692d4df2c8e54a3e2f68822d7693f50a37b094fc08bdf8e6ab87795ea0a0b

Observation 72ec50ab-e5e6-48e0-a2b9-55491210f552 · outbound

This paper cites Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing , pages=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.384863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.336885Z digest=sha256:ed386ecb72b33e8c46c27e04908cdce35525a8588a6aeb09bfe0821b96442aa5

Observation aba4af04-162f-472d-aa2d-32bc164538c1 · outbound

This paper cites 2021 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2021 , eprint=

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.341414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.341414Z digest=sha256:7cd8ec7523fa6a54b5b1ab699c31eb6376cf4ed39d26b11b6287d63ba8f097d1

Observation cc5710ed-f6b3-496d-bcca-ed9387fd0959 · outbound

This paper cites Efron , journal =.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Efron , journal =

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.345641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.345641Z digest=sha256:dd3a7190f6ac40fb9441a5925962da713bc9e46df1229bbf2aa885c77f415281

Observation 647b5ab7-8229-4927-9e63-94c09c0b4dcb · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Advances in Neural Information Processing Systems , volume=

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.362286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.349799Z digest=sha256:d525899dbfcf5c60a8ced4682f881c7aba5b1f3c30a65fc08d137efb9d98100c

Observation 225d2735-3c17-445a-98ba-fe876916647a · outbound

This paper cites G lo V e: Global Vectors for Word Representation.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? G lo V e: Global Vectors for Word Representation

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.354165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.354165Z digest=sha256:d67a0db6538396915c2ea8cb58732d71d03cd005cfba9034165f1c4b573ad723

Observation 683c54a0-2a62-479f-b836-89f4bfaef3fa · outbound

This paper cites Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing , pages=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.353115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.358699Z digest=sha256:94c6e84b0a93057dc06499503a1f91d5eb460fd167f2bc2683a067ed35df226a

Observation 44590bcc-211e-4994-a71b-2e73f3237ae0 · outbound

This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Efficient Memory Management for Large Language Model Serving with PagedAttention

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.362774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.362774Z digest=sha256:9feabf2e277ab10e0fc366b643e19939616c90f158ee39d435d81dc926807ceb

Observation 107d418a-f0ff-4b6b-a97e-a78829960128 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.367022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.367022Z digest=sha256:eac38ba6684b6927ca520cfb86bffdc9ad9645c29b98b4fc513552f1b3f1bb26

Observation 818ae23a-fb85-4f8d-be2a-b221a75c4974 · outbound

This paper cites 2020 , url=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2020 , url=

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.344049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.371345Z digest=sha256:ccca6f01e83b48b72aae2f9b470cf5c0ddca286a4336e1d809d203a7a047ec39

Observation 4628c8b0-5f0f-4f63-b847-6549da4687e0 · outbound

This paper cites The Thirteenth International Conference on Learning Representations , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? The Thirteenth International Conference on Learning Representations , eprint=

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.335047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.375561Z digest=sha256:8f638c704e5081875df046c3fac4b7e7b13240ac3369149cf6b4479397f5b6ec

Observation 8c1e3d72-2e7f-4e5a-a418-cddee7f3148a · outbound

This paper cites 2024 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , eprint=

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.379859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.379859Z digest=sha256:44f4e02104e0ab8c4191f3b166a7e38dbb2f2b7bf1b2ba9303726b9173437cf6

Observation a4f5a72a-6c8e-448e-a220-b2332d08430e · outbound

This paper cites 2025 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2025 , eprint=

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.384058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.384058Z digest=sha256:480d862c4486b235898c5ac3c9740a25969f61d14c0018bfa72f09053fd3fc54

Observation 2d2c3a6a-813a-4d08-9f17-799ef8df5eb2 · outbound

This paper cites 2024 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , eprint=

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.313703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.388683Z digest=sha256:4f6c3296fd9e4528a8eedd8d0a7e92d35c0244ab405ff2878f1983fd3d86b29d

Observation 58f80f4b-b34c-435e-bd29-6e1c1f5211b4 · outbound

This paper cites 2025 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2025 , eprint=

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.392771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.392771Z digest=sha256:c6533557b02f8d71d78a55232c350c7a4a1367a8847dd169c5c331b2ad588ab0

Observation 7eaaa773-4d6c-4805-8a00-c2d47bf868fd · outbound

This paper cites RouteLLM: Learning to Route LLMs with Preference Data.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? RouteLLM: Learning to Route LLMs with Preference Data

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.397225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.397225Z digest=sha256:7fab8fa86f9b581d9f09288a514b2693871a961e0ef3328fd7e3318e6a7ab6e8

Observation 2a19e08b-0183-4676-bd32-2ae6a50d4567 · outbound

This paper cites Gemini Embedding: Generalizable Embeddings from.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Gemini Embedding: Generalizable Embeddings from

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.296589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.402083Z digest=sha256:d69aaab8429669fab7a2651461738825bcb76762767a9345dd3e2581e3226b54

Observation 83399042-5224-42e7-9231-dfb3ba94a3b9 · outbound

This paper cites 2022 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2022 , eprint=

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.284963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.406772Z digest=sha256:c8317b8ece2b66f375f98dc5637c79c4ec5a343914a9abf5e3af6ed04cf7efae

Observation c7defb17-654c-40ae-b725-e831e075c4b6 · outbound

This paper cites 2024 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , eprint=

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.274183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.410930Z digest=sha256:f1b165d4aec6c72bf1d30f92c90481856321a886c067780674420e37fbdbd809

Observation d9b49a9a-0ca8-404c-9b6f-e459d90c894c · outbound

This paper cites 2021 , publisher=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2021 , publisher=

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.263949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.415291Z digest=sha256:5ad220c1f35ef270ba85999a5d98ae2d27b5accc1780af92a1f0a6105056801b

Observation db861156-17a3-4994-b78c-f17fa55dbbe6 · outbound

This paper cites Proceedings of the 2nd Workshop on Natural Language Processing for Conversational AI , year=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Proceedings of the 2nd Workshop on Natural Language Processing for Conversational AI , year=

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.254752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.419560Z digest=sha256:605812b9571ea333c6e6c862ec2abdda7536e67c25ede07d6f6950894a61b12a

Observation 6c44d333-42d4-43a6-b91d-f13504dad467 · outbound

This paper cites MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.423713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.423713Z digest=sha256:316999f75276dc65001427fb14f1ee75cc0fc2abf0717b349fce646c213bff12

Observation eb3f0109-ff4d-4681-b221-569b5dcca6a8 · outbound

This paper cites Bioinformatics , volume=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Bioinformatics , volume=

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.245560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.428582Z digest=sha256:c77eb7dafea29cb887450561594dae10b4fcdd135ae2aaba17881a1be46dbb52

Observation 61ebbce4-7842-4201-ac70-9172fcb38a26 · outbound

This paper cites Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017) , year=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017) , year=

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.234812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.433104Z digest=sha256:dbc923507cf0f448605b96be5fd06b17ca98f4aeac1d35599eca92bdcc47c423

Observation fd513335-9f58-4325-8611-52b1940f0f7a · outbound

This paper cites A SICK cure for the evaluation of compositional distributional semantic models.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? A SICK cure for the evaluation of compositional distributional semantic models

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.437337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.437337Z digest=sha256:159dfba5321fbce159c0065764a9919e1185c54b74bbc57c23cad2df7f30a9d6

Observation 962880de-a582-4c9c-ba91-7fc9ec657a84 · outbound

This paper cites Ho and Christopher R.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Ho and Christopher R

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.216980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.441867Z digest=sha256:0c290c84682344449156e0ec57eb05a03d78119bfa3469cb7ecd2e30ab8f43a6

Observation 00fb1e68-b43c-4bbf-83ba-c97e3f97334c · outbound

This paper cites 2021 , url=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2021 , url=

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.204213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.445995Z digest=sha256:eaa74891022d68c5a15ebafe64477f1cc3548eed879aa15616fc467b317c39cd

Observation 57f25c55-7fb3-4c95-8680-e39f8e72b94e · outbound

This paper cites and Daly, Raymond E.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? and Daly, Raymond E

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.450207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.450207Z digest=sha256:b71fe03b8f7e6c3d9e1df09fbe6feb560b8d9422960807a817b3640d3d5b1929

Observation 9d096fda-df42-4534-ae68-3fc42e03bf0c · outbound

This paper cites 2019 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2019 , eprint=

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.184858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.454276Z digest=sha256:cce8950b96e67e47b4b764d4008bb6e49788e15285478ca14d2c814b3f8f7bfd

Observation 4c55538a-8c3b-4461-b049-7a9b148295e6 · outbound

This paper cites 2021 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2021 , eprint=

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.172232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.458694Z digest=sha256:ef1d50b7c06f12831d7406aa19041816148e01182ab0baa9ae09316cee5c4c34

Observation 85271285-f939-4559-9a02-25b87c48371e · outbound

This paper cites 2021 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2021 , eprint=

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.159793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.462920Z digest=sha256:6cb4e358444db0ad92b64548bd0b2759cedf9a25055c4a40a04a4a8c7943cab8

Observation 16e09ab6-0bb1-4e8c-9c56-08ee3b09c87b · outbound

This paper cites S em E val-2012 Task 6: A Pilot on Semantic Textual Similarity.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? S em E val-2012 Task 6: A Pilot on Semantic Textual Similarity

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.467114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.467114Z digest=sha256:d6773ff9de335d908def3716bae8885bd42fc29df1fb8f4805b15a2a1d340df4

Observation e368797e-4fcf-4673-b945-aa1195079758 · outbound

This paper cites * SEM 2013 shared task: Semantic Textual Similarity.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? * SEM 2013 shared task: Semantic Textual Similarity

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.471213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.471213Z digest=sha256:623ebb187f4cd30870cda1957dd18743725e9c0d7d6d07be2e6a1ba891a3c192

Observation 49dbc2b6-b3f3-4844-9031-7f6a45cde2e3 · outbound

This paper cites S em E val-2014 Task 10: Multilingual Semantic Textual Similarity.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? S em E val-2014 Task 10: Multilingual Semantic Textual Similarity

Reference 89

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.475515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.475515Z digest=sha256:16793276a185ee1374c3bffe49be36a0ac84fa3a5e4aa217e5a9fe301430dac1

Observation 602637bf-b8ac-48a6-8bd5-e9e57d40f5b3 · outbound

This paper cites S em E val-2015 Task 2: Semantic Textual Similarity, E nglish, S panish and Pilot on Interpretability.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? S em E val-2015 Task 2: Semantic Textual Similarity, E nglish, S panish and Pilot on Interpretability

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.479767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.479767Z digest=sha256:863bae1efde753ee23b6ec49427daf2087cce4ad8c9181f3e0618474d96063a1

Observation 59538e61-dea9-4885-b5e9-9f8399108010 · outbound

This paper cites S em E val-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? S em E val-2016 Task 1: Semantic Textual Similarity, Monolingual and Cross-Lingual Evaluation

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.483978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.483978Z digest=sha256:f73bb6ecaf467365ea29f1bb4346819b346d804cbe956fce8c4708634fc7399d

Observation 4fac0ee8-f27a-4cb2-9437-cedf6511ceae · outbound

This paper cites S em E val-2022 Task 8: Multilingual news article similarity.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? S em E val-2022 Task 8: Multilingual news article similarity

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.488247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.488247Z digest=sha256:ec67222682b81b1262fe68a42bcd71d4b864786d7913310a57ad12210bb25450

Observation eb0d2f5c-379d-47a8-9723-e643abfbadff · outbound

This paper cites BIGPATENT : A Large-Scale Dataset for Abstractive and Coherent Summarization.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? BIGPATENT : A Large-Scale Dataset for Abstractive and Coherent Summarization

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.492844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.492844Z digest=sha256:018124e8e1ff2fcc7d0d12d7137dccb193c991748d05df7249d296e938566419

Observation 9982193b-4aca-4564-8d69-f2d4413d0578 · outbound

This paper cites A Continuously Growing Dataset of Sentential Paraphrases.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? A Continuously Growing Dataset of Sentential Paraphrases

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.496977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.496977Z digest=sha256:a1d85565af7d2ac1f4b41c9fbb7d2e34ee7154f9d6d9e23c3745c28e3d668210

Observation 3f37a77e-42fe-4ddb-a9b8-937e201b57cb · outbound

This paper cites The Third PASCAL Recognizing Textual Entailment Challenge.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? The Third PASCAL Recognizing Textual Entailment Challenge

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.134116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.501361Z digest=sha256:d821f78262fdf69cf240d4613d420a21117771885d34847b40475f1895fd88c1

Observation a348eee8-0308-4df5-962b-adc5c7d09b08 · outbound

This paper cites Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models

Reference 96

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.505799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.505799Z digest=sha256:692f55a186a20c093e9005b5e7b608c996d5a74e09e27fe3fe6ee4b2250b9f00

Observation 3db80afe-322c-4c2c-b63a-104b7986cf1c · outbound

This paper cites Danoliteracy of Generative Large Language Models.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Danoliteracy of Generative Large Language Models

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.121749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.510452Z digest=sha256:6b44c7c0c514e98f48ba1fbbf83aea4d2252481f522ac33e513bb4838bae5acc

Observation d34534e2-1b6c-4f41-8c87-050a2f71b506 · outbound

This paper cites Adversarial Domain Adaptation for Duplicate Question Detection.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? Adversarial Domain Adaptation for Duplicate Question Detection

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.514690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.514690Z digest=sha256:4ecdc62e28ab64e4cd6714c076de4bc0f5e267f061fee481e8abf48474930ac0

Observation 672d0cea-9ca4-4f10-98d3-6d9131fe2e58 · outbound

This paper cites 2024 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , eprint=

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-15T21:37:01.518926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.518926Z digest=sha256:d8ce8b26c318af8cee03350cf0b82c29ae0fffa379e346673f6ecebb04fb1293

Observation d3acb081-14a7-4f2f-85f0-66eb0211e5bb · outbound

This paper cites 2024 , eprint=.

The Embedder's Dilemma: LLMs Are Better, but at What Cost? 2024 , eprint=

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:37:02.102693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.523247Z digest=sha256:d7b0e9c9e7e14362bc7247276f145ca8b719593da15ed01eb9befa38cf96ce5f

Pith citing papers

No inbound Pith citation observations are available.