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Paper Citation Record · LEDGER

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

As of 22 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 2026-08-22T06:32:14.747728+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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:37:01.083703Z digest=sha256:25ea0823c510125ed00c6d2cbcc2ae3f739ab4cff9b4f847008418cef8c68ed0

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:e85c14354bf2cbe3ee3e67b59aac2ed34dcb90aa629a9f557f195c05f448c411

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=sha256:993949eaf2d601a0abbb44c9a956f2cccda1f47cc49b3e727deca305efa97f40

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:ca832b28898ba70de08f9493f094be7f955dd7463a46a82af08af755f5338937

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=sha256:475dce526fa0035a9e6b307e7e509906fb162e02e264c8996fe16807f4947494

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:b4c4a6432ed877eea7730ef0a901fa6ea5746a91177562de3df4bba41023c797

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:da1c765bffeadb6b9dd0215b058b6be1e59b9076cc60c41f7ac65c4d5a831553

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=sha256:0e1dabe053129b58028c1706d3424fe9a3fea6890b4b66f352968c9a5b864c3f

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=sha256:113d8ec3a891aafbf417526cc98b5b2ea0bba27081698dd0aacefc1445e46907

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:ec83ad1091ee5f4c372a8be4759c42eb17624d24deda12a97cff6f4f607eb0a5

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=sha256:54a1cd9a52bf40aa2109baa916dd0e04964f111c17b7c395d766be8d7f3fae50

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=sha256:6c0c1fede40dd0208d2aff621e970f592763e478e757492dabf3d0f1402c9ad4

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=sha256:2175db5eb41145c2d75bfc93987a1f2967da7d8654e4a2ad36a0e06c12da20f3

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=sha256:9e37a03ae6f7be6965c33648955a1eb213c8eb25892d4dfad70d8bb6380f4d1d

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=sha256:9bc035822e19cfce5542896d3bd8ff1049193da7622b67d0859fb3df4f2ecacb

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=sha256:4d990c3a2c4348ee037f0781aa3908b1926917d802786da08d4952a9618cf494

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:caab84144fa148e6a04874318a30af5e35aeba665ecb24aa26e9a8ef34b66407

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:fabc0177016dc8121d8b159349f9b63d4b6e792c039f69f5b8cefd4d45ed8319

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:c775c27312166cb2635e004ebbde557e40545e6ecdb451b05cb945210ea02520

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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source=arxiv_source observed=2026-08-15T21:37:01.172329Z digest=sha256:d7e016097ef8421c0f6bd56ae679e9904c078c98e2914e9f1f65e84eeed2aa29

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=sha256:1362c2c0cab9a17d9b19d1c475a20f1195143a53bc41e963433a82c0004f4fbe

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=sha256:86683813af315100c52f4961a32e98f82d7d1db7d59fab52498f1e740886f400

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=sha256:54a604b1fe8bb239bf11443fc7d6aa2055ce216ba5dd171ae29c9418d85c056f

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:e084b634a24e1288f971c5801ea88fc529697273622a48778d33cc3c7b33d2f1

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=sha256:7acf223bacf445f2e2d4c47d3093dcc67e4f47b07245514b9ede533a175eb657

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=sha256:62d4d034260bd3cde80d90b15b850dbc1e6eac3b97a450803a5a8ab4561fd674

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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no resolver link, observed 2026-08-15T21:37:01.205498Z

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source=arxiv_source observed=2026-08-15T21:37:01.205498Z digest=sha256:2fda4b73f3c6a70d2a48ce02b6c4a708990cf287f4551fd961007a0353ac6111

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:f1bf7fe3e8d2f725ca7b89df0eafc96bd2d164ecb899beca03546e51c21ef894

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=sha256:500aeb3a1478b713de67dce74b945d5967a7c9e5c631746a0c236ca2c9ec9afa

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=sha256:508b20bee5b844038d5d33e0a17c252c6d0b27aeb94b92db173beae1c60003b0

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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no resolver link, observed 2026-08-15T21:37:01.225139Z

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source=arxiv_source observed=2026-08-15T21:37:01.225139Z digest=sha256:d5af1f6a0314b55c2bf79129c77f61ba216b7d96899ad3ed3b51a0e42f1a3a14

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=sha256:527716bcda6a425f66e73ac96e7c8ae6a28c040aa6035650cef7e376389c6501

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=sha256:21181428c15081d6e097d095482c830963bbe674d452a0aa87436cc6df036630

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:dc39deba2dc0fb3486a706f0ccff79a947c204a7867febfebcfb79cbcec509f8

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:e9e5d082067bf7dedae1c87855fb59e4d319e67ed8c93a0d379e370c33131c31

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=sha256:6dc0159218f9d4f212d1cd97e8fa45d2d5f66e04d8ce4f58c208c6965c1896c6

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.251229Z digest=sha256:f9313fd74aafdc80fd1c94863528254578480fb6ed6b37af2a0c58a4fe482761

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=sha256:8cf8a8828bf0555bd77859f06504ceeec385eacdf96fe223681d0a42e14a13c6

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=sha256:8e4028a3a857b0ede380c648806523d0acdb494f4ce214446ae8c700531b12e6

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.263948Z digest=sha256:85595944632793a065749c4220498a6de5c88afbb034a5a4347f68e9dd6e5103

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=sha256:2ae6b3c282006f38e8bb35e34245c7e64c0be3d3b76bce53fbf879d599f7b10a

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=sha256:277b29540c23fce59b23bd1261db0479d7c275c00fc1ad9cf5e8f791fe957f3f

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:c841893628f5d1652e0401998b9c971b65bd973efa9c0561aae3ab500ecfece6

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=sha256:2291d8a17114ea089bd8f653ebd6f2b64eaa22215b7c6916fe4c768ec46ed889

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=sha256:56980d394b40dfb018135436058e1bf6cde15a8f6f0af98cea77cb533e042646

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.289540Z digest=sha256:c6c39e64cafadd5a2666470a017193827b20840ef2071de8804359cc2062fc5f

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=sha256:43d246875d966174c1fc868cac7d6e4fb9818b365cd65c2f5c099ded1f3c78b3

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=sha256:41a457a6f4876f7a0baebd8906742d84ad55d76565404f4465405e9ed44a2c92

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.302203Z digest=sha256:6b640463b80946ba9e009f80ad6fceeb39cc0444e6031f480a1e64cee7603256

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.306444Z digest=sha256:0fafdb5f3c4de2b97595764609f4ad5e2a83690148015b529bf7506c6c06ad49

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.310567Z digest=sha256:7a2d145e1d175b68a56748427f8f60dd3d17afe5a1d7eed457ed95f40fd04318

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=sha256:7fa0b795f2356b0741418a60ab59fd66f554a4b36eca52bea0f3f27ff5c2981f

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.319143Z digest=sha256:6e537eac8a74c9846631132b6d1cca2fd39eae300e8a69f748773fab45ee6b01

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:c5ddce2797015a40036843bc9384011d1de61ebe0c38d3639de841ea969803d9

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.327838Z digest=sha256:64c4311efff0304cbe32feee2c9a939e6d4899f411a484193cc682fac28ac476

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.332088Z digest=sha256:c8d8757b31198c7183796da79806cf99f6a16fe3c3a175f81ca1f6972a1c3c7c

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.336885Z digest=sha256:aeeb81ce01197af927964dd8db2148ba676dd9cf68a2cae960bf4fc3b20413cd

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=sha256:4d0f26e602d84bd36f277777cbc069469c536f81b5f63c09ae2016ee25bffda2

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=sha256:6f8da569ac67da19290ac64d18187911cdebccef83babd1129c35b22648c0727

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.349799Z digest=sha256:bbfdc75f1ae20c1166239d644df488b193d157e2aa99f509aaca2d26ba972e73

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:fbaf30c6b449686d7c465eb10a5d778c33c249ccb8df6ea0e53c0aefed9fec3a

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.358699Z digest=sha256:d1a029f21fe613a22523e68740f653df0e17032cc17dfc533db5a71019b6cf8e

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=sha256:83c2da01d3bd1390d55e5657d5db27d71d7c48e7cda6d8605cbe57e2807bfa8c

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=sha256:48d4e3343e00f2b85eec464f28dd66108a67745189b422f38ad8afe4a9629774

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.371345Z digest=sha256:36845c526e3579b58565d5fa05b0243bcf8cca5b7dc074d86de4d4ce0268bf3d

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.375561Z digest=sha256:849aa8f0eb500162abbbf7c9e838f59e559059392b269e41047b5af64d8632d3

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=sha256:5602dad9c1657a5296e161cf8e6fe6b2dc82fe463ee6b1c232c5d400e77f9ed0

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:ac7508192ccfc6b51730755abf27655e1da659f018f02b4b60ffc52bb63947f3

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.388683Z digest=sha256:78f5583952f22b2239011cbaf67c2150fc9a7d6cad1a37db3723bcce849dc34c

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=sha256:681eda94696fe4da84ce4cb1ffe69120f555cc4fec7bc1ab7bdb9e2be752a149

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:bfb07762afb936ac9f5792ebb94120d915b15e96199c8e069952e681b0a7c4c9

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.402083Z digest=sha256:aadc4ebf5285b60e67523129ef529a8116b2afbc0bc69f635a88b9cd902deb0f

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.406772Z digest=sha256:7620c0dc47a2e94d9dfefadb446674a1815ed4b9f085e4bc29e343db227acf17

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.410930Z digest=sha256:dab6efe4a9a686ef6c7e2cb3134b3edfbe02ade16e2e4ebdbe6a8ece0d7b3ab3

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.415291Z digest=sha256:cc81267ff6006761f7fce3ef251e0e23c545ec49de4dc97ecd2e253bb1ad0bcf

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.419560Z digest=sha256:ad6243130ce4cc7edb3baa8e39938a9b2e187e1f830a16542edc9c554e2408b2

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=sha256:3bc5e7afb9268758e08ac17c2bb2ea964ca85c0991efd9255f2e7865dbd67017

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.428582Z digest=sha256:e1ae6b620747ae81d080f58228fdb2ac8b3b2a8e3fbf18d03b56bf4634ca2c6c

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.433104Z digest=sha256:a86cdc9e3a5bbdc4a90e98be1e51b48335810c294373a301668941d44faac858

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:cafceede8921dd753f869aa41120429ac4072039f63eacda2f20c5b280c9ac86

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.441867Z digest=sha256:b2d509f21f4fb283a2d477a205f0d02221603d59344f851d8dbdcd1f79600207

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.445995Z digest=sha256:7ca5bb7c77793f0ef8aeed1564c9cd619d067e848f680f3ba0beb1db2148b980

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:a4fbfd7d199ef05d876dfb38afff813074e80c9182bd1ca94ba4a3c283bd218c

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.454276Z digest=sha256:67902dbf380b6dfa15cab0e877f13b3e6c57622886c8b6151d1194e94ff34c4e

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.458694Z digest=sha256:7147716040c76c1528eb1203c5ec16829b63adb6a18a4e1debeace61ff2cd7cb

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.462920Z digest=sha256:11bf0f3dbc380064576a5231bdfa09d78144cb09f854fb85ba90c3eccc8ea11d

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=sha256:5c2c0df1dcc026036eadeb33a4bf9285c694d7649cac86f1094d39697d7f36fa

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=sha256:949d9bd4f88f80e64574cf6ad788feeb231be12544b6de40977618e524f3c131

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=sha256:2fad4e23c829afaee958c84de304824e933bd593f911f24adc425b115085d6f3

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=sha256:58fe88f4750083b497a05497f6c3fa569e7bec3b7f45c6cca8e157718c4fa1bd

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=sha256:366b0270acabe4063ef7dbd62c3fe2497a3d5c4c4f068f016fb547dc0ce13b87

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=sha256:297b4d385d1d8f1639a98ab05a0e3a246e4f2345a80323b1f05bdddeb365d6a5

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=sha256:96f3de1e6446902c819d9bfeef4efc0684dbef3413645c652528d34b81c1fbac

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:b4cbc41136f234427b0ecbb0f7fdc7cd6a31be453a6078f723cf0c3cf9bc2137

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.501361Z digest=sha256:0d17d2a8d41e54c164e77ee3b73195d8c9731da5e88f7aad3e6d598ee4d62d5d

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=sha256:1a189f5d399192ad6849ebd320a25622072edb2acda782698594792ace761c33

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.510452Z digest=sha256:38aa0d13707990667ed544200c3427b7be4b39e5e6512643330dcf92e286f401

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=sha256:0f951bd9d613d99c88f6cd435599c7874be1dafa4996eaf162f37814d25e2ea9

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:ff405ed7fa3612473d251bad6c5780acd63289c260f8a20307aa9a4ba1c2b37d

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 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-15T21:37:01.523247Z digest=sha256:d79e8582f51c652de292af6aaf05674a5bf70904c7718756aab514489a76d002

Pith citing papers

No inbound Pith citation observations are available.