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Paper Citation Record · LEDGER

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization

As of 18 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2505.10736.

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

pith.paper-citation-record.v1
2505.10736 v3

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:08:47.091294Z

measured 45 of 45 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

45 of 45 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved43
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fdb698c2-6a71-4938-8b32-0255bd990568 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 1

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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=2026-08-15T21:08:45.151923Z digest=sha256:77e2ba6d9c5faba0542dbd58bcff4bfcfd57bf9d5bf34a25d42993fdfd925cfc

Observation becbba86-6f86-4847-b8ad-a970a62a2c65 · outbound

This paper cites A Survey on Data Selection for Language Models.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization A Survey on Data Selection for Language Models

Reference 2

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source=arxiv_source observed=2026-08-15T21:08:45.160118Z digest=sha256:719ab5feed3b16a32f04983fc9ffc729db5330ef085daec7c199ca9c9a22f666

Observation f8da7fb6-85fb-4fd9-af64-62f0de3f71e6 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 3

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

source=arxiv_source observed=2026-08-15T21:08:45.166750Z digest=sha256:56f2a68fddfcc0f3dd76b21112f4e37477bf893a7c4abb96fba4285755789d79

Observation 04f487f4-639f-4d82-a1fd-ded5679fbd48 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 4

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source=arxiv_source observed=2026-08-15T21:08:45.173184Z digest=sha256:ac72ee003dfab453468b02a77e7508d5a24de66b214c01e796a46f34d9ae524c

Observation fc0822f3-4712-4a97-b41c-bd04e421cf5c · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 5

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Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-15T21:08:45.262401Z digest=sha256:67b84ffa4068d4b87dfd0a8c9f516f2fa8c31c58ad7b82829909602ee26c0fec

Observation f7dae928-bfcf-49a0-bed2-22685fc8a1c7 · outbound

This paper cites Super-Samples from Kernel Herding.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Super-Samples from Kernel Herding

Reference 6

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source=arxiv_source observed=2026-08-15T21:08:45.312117Z digest=sha256:eb590cd9964eaafe72cd1da919d60c75ae91139a3906204ab3cdb31496ea4df6

Observation a57bab15-3861-42b3-8cc8-f45be1d04e3a · outbound

This paper cites Selection via Proxy: Efficient Data Selection for Deep Learning.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Selection via Proxy: Efficient Data Selection for Deep Learning

Reference 7

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source=arxiv_source observed=2026-08-15T21:08:45.320302Z digest=sha256:5381e2b3c477a6888c9d05107302f8aebada39bde0208c931201fa645a2262a3

Observation e82a0709-eb30-4058-af32-21c08e0610a4 · outbound

This paper cites RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning

Reference 8

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source=arxiv_source observed=2026-08-15T21:08:45.421780Z digest=sha256:730e8ef7b2250bfcfc342fc7313969f3b03abd14ee33423e4ce69da09cf63586

Observation 3f3645a7-6335-47a2-b784-9422bc2aa3d4 · outbound

This paper cites Adversarial Active Learning for Deep Networks: a Margin Based Approach.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Adversarial Active Learning for Deep Networks: a Margin Based Approach

Reference 9

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source=arxiv_source observed=2026-08-15T21:08:45.500962Z digest=sha256:d53377547e8de09051b07dbbe5e6977c9f784bb47e55e1e82e633871fb6b226b

Observation 97f014f6-b0ce-448b-a7e6-8969fe648b78 · outbound

This paper cites Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution

Reference 10

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source=arxiv_source observed=2026-08-15T21:08:45.537546Z digest=sha256:97ced03fe3af7d92b865339772e199a705e6dda0392beab5007cb1be9926e37f

Observation 46eabe59-fa2f-4ecf-b349-439980cb2cd6 · outbound

This paper cites EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Reference 11

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source=arxiv_source observed=2026-08-15T21:08:45.546308Z digest=sha256:634dc80b0c465316bea4d4155a020cbcc95d9747ddc000258be780a2279b371c

Observation ee426de1-24c4-477b-8db2-0f7708f60632 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 12

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source=arxiv_source observed=2026-08-15T21:08:45.634522Z digest=sha256:cf9f2a379037e12c94093765b2dfc9d0958ee138c9855af8051a3d9e9d30cdd2

Observation 4fa4642a-95dd-4c61-a24f-a0c887afda78 · outbound

This paper cites Efficient Universal Goal Hijacking with Semantics-guided Prompt Organization.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Efficient Universal Goal Hijacking with Semantics-guided Prompt Organization

Reference 13

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:08:45.649648Z digest=sha256:0b619d77a591e4250a2f823d02162ace0bf17cd126e8067e1aa970f0a2e13e3f

Observation c9403401-8470-4c28-ae56-a1cb5b9b9657 · outbound

This paper cites Task Facet Learning: A Structured Approach to Prompt Optimization.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Task Facet Learning: A Structured Approach to Prompt Optimization

Reference 14

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no resolver link, observed 2026-08-15T21:08:45.717835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:08:45.717835Z digest=sha256:439a82cb12dab625584a4f90a43abaa3a81c8458ad0a5cafcce8b62b8a0af997

Observation 3abb6e08-4da3-4929-b099-bd4bcb7375aa · outbound

This paper cites Confident Coreset for Active Learning in Medical Image Analysis.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Confident Coreset for Active Learning in Medical Image Analysis

Reference 15

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verified exact
local_arxiv, observed 2026-08-15T21:08:47.839120Z

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=2026-08-15T21:08:45.725463Z digest=sha256:5e6f70feb4634ee0c42fccab278ac79dd893d97280b734d12d2894c671e7d069

Observation 967d4a45-0ea5-4a0e-82f1-ef4af418374b · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 16

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source=arxiv_source observed=2026-08-15T21:08:45.733087Z digest=sha256:fede4b4c64e47354ac49318e20e0ea9e9883188d39747dd31cc5e262f29c890e

Observation 929b9bb0-213f-4ba3-9107-cf34bd76702e · outbound

This paper cites Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning

Reference 17

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source=arxiv_source observed=2026-08-15T21:08:45.841314Z digest=sha256:8f6b72a48b3cb558bfdc5cdaa842654775164b64d3d962a6eef0919c729e5c07

Observation 2d720f93-19c2-41dc-81d4-e7bec1da49c8 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 18

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Source-reported events for the cited work

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

source=arxiv_source observed=2026-08-15T21:08:45.884277Z digest=sha256:bf1b7e237723dfea50001f9138a2566a3f679ba44d78e7e6c07f19bb9555b31a

Observation c2bdf39c-b920-47ff-8697-544dcd55a9d8 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 19

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source=arxiv_source observed=2026-08-15T21:08:45.974517Z digest=sha256:56c3af757c717ff1f4e1ed581c917f9451bf0f148a6f97a2ee1419385a152a08

Observation d3634353-e02c-43a8-aae4-53451f49be3b · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 20

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source=arxiv_source observed=2026-08-15T21:08:46.024422Z digest=sha256:957d93fc8bb7860b8ad947f1320c2bdf1b09695db12de7e7880d706645657ba6

Observation f0805446-b1c2-41dc-b9a1-16db12793ee3 · outbound

This paper cites Active Learning by Acquiring Contrastive Examples.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Active Learning by Acquiring Contrastive Examples

Reference 21

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source=arxiv_source observed=2026-08-15T21:08:46.030607Z digest=sha256:f472310a89e5683cb2efea3c4412382da3b451f4153b01727ad37cd9b0f62722

Observation a53c8169-a05e-4f10-a958-77e1b9311bfb · outbound

This paper cites 100 instances is all you need: predicting the success of a new LLM on unseen data by testing on a few instances.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization 100 instances is all you need: predicting the success of a new LLM on unseen data by testing on a few instances

Reference 22

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source=arxiv_source observed=2026-08-15T21:08:46.069427Z digest=sha256:e4fa9d357a83d2c820b95a78d8eb4d2acb1ed35680d17ba82fc364379af79538

Observation 0649a8b1-0119-4ac9-9bdf-e1a88bfb537b · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 23

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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=2026-08-15T21:08:46.110102Z digest=sha256:e6d94b31ad35a5d0af3ab98b1f3dcb4bac1fd7f517c8c51f2f7bdd8173ec6c7d

Observation 6abe9604-0898-4f4a-a764-db9bffa04569 · outbound

This paper cites tinyBenchmarks: evaluating LLMs with fewer examples.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization tinyBenchmarks: evaluating LLMs with fewer examples

Reference 24

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source=arxiv_source observed=2026-08-15T21:08:46.116666Z digest=sha256:a2d03396b2626c0da9bb1a9624a4b9b452320e97d669dbab28e8ab4579d74f55

Observation 68c6f579-4b73-4c96-a89c-7fa29cd3b437 · outbound

This paper cites Automatic Prompt Optimization with "Gradient Descent" and Beam Search.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Automatic Prompt Optimization with "Gradient Descent" and Beam Search

Reference 25

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source=arxiv_source observed=2026-08-15T21:08:46.207594Z digest=sha256:13501b67e011c7e5568f9c9c12e732d7fdb9292b5307b059c910ae5219d7863a

Observation 9304d62b-8f34-42a1-aa30-07551831dabd · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 26

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

source=arxiv_source observed=2026-08-15T21:08:46.292643Z digest=sha256:4df04503d3a3f3c509e5c7639b1ca24af954b5cee1c02a58fe23cb1b8c51ab31

Observation f0125ce7-bd1a-480a-b056-b8817cff4f90 · outbound

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

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 27

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source=arxiv_source observed=2026-08-15T21:08:46.391741Z digest=sha256:928684604e97d6267e08c4169da87f186cf13767b344bb1501427f77968e1ac3

Observation 7fa6ca6e-9ab1-44ad-bebc-ab9877d86ef8 · outbound

This paper cites Active Learning for Convolutional Neural Networks: A Core-Set Approach.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Active Learning for Convolutional Neural Networks: A Core-Set Approach

Reference 28

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source=arxiv_source observed=2026-08-15T21:08:46.398642Z digest=sha256:ee0135d5c63b02de80347259357558899aed04666a0fa1c824904733accc1ba4

Observation a885d317-e090-46d2-b1b3-09f829acbe28 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 29

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raw_fallback, observed 2026-08-15T21:08:48.563914Z

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=2026-08-15T21:08:46.404071Z digest=sha256:61a5989cb8d1483805809638da317a883c426334895f77caff84792d0fe38d2e

Observation ec5aeb86-0ae1-4621-b711-2e20184fb56b · outbound

This paper cites An Empirical Study of Example Forgetting during Deep Neural Network Learning.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization An Empirical Study of Example Forgetting during Deep Neural Network Learning

Reference 30

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source=arxiv_source observed=2026-08-15T21:08:46.470263Z digest=sha256:f186a483b0a025b927b83d9ca6b2d5ecf8d10610d9cad84634e66a542b590f4b

Observation 880a68df-56a8-4e17-9744-8ed3c31a3048 · outbound

This paper cites Anchor Points: Benchmarking Models with Much Fewer Examples.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Anchor Points: Benchmarking Models with Much Fewer Examples

Reference 31

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source=arxiv_source observed=2026-08-15T21:08:46.539418Z digest=sha256:b6f4661f21eaefb2cd3318d639c39ed80b45111dde95afd5e5a4826a1e1e20e9

Observation 47b47f51-37ec-426f-8a33-b0471e40ecaa · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 32

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raw_fallback, observed 2026-08-15T21:08:48.459157Z

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=2026-08-15T21:08:46.617421Z digest=sha256:2b4787a036dcdbe6e909728c095f4fc777687eed3883ddf0c18e0adcc4520339

Observation f18b0cb6-53b2-40ea-add9-9986a47c7082 · outbound

This paper cites "Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization "Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection

Reference 33

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source=arxiv_source observed=2026-08-15T21:08:46.623696Z digest=sha256:375e8545762af7d6f2247455f7ff11738dda47bb829290998953730b34b4560c

Observation dd03d039-b190-457b-a32d-b5e0a402d607 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:08:46.630311Z digest=sha256:ca6b320281eb1b6125ff3a42911f98a8575daaa23ffd39844154ac3e0bd0628f

Observation e6030d55-fd56-4b90-8823-d0094f7a8e63 · outbound

This paper cites Large Language Models as Optimizers.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Large Language Models as Optimizers

Reference 35

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source=arxiv_source observed=2026-08-15T21:08:46.677735Z digest=sha256:d86ea3352fbff2c636ea86fe4f469b26533679b79475f9d727113c129afada6d

Observation 5078c01b-bbcd-4c12-a041-e024a5cc104b · outbound

This paper cites Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization

Reference 36

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:08:46.705488Z digest=sha256:6f37b714eabbc28ee80bb1fbb3a7c3e6d841c91f8a3fc1bed21455fa09e63442

Observation 01f3d289-8db2-426c-8ac4-55c77d653cb6 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-15T21:08:48.378702Z

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=2026-08-15T21:08:46.712768Z digest=sha256:7c8426cd26028dba224bbb7c894de78025ec17e0a61f9d66b5b84788b254f330

Observation 58c76913-35af-45f4-a988-b43349a20ece · outbound

This paper cites TEMPERA: Test-Time Prompting via Reinforcement Learning.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization TEMPERA: Test-Time Prompting via Reinforcement Learning

Reference 38

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Unavailable: canonical work link unavailable.

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Observation bcd2c9e3-2e9c-41df-999c-b3ed66a53694 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 39

Resolution
verified exact
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Source-reported events for the cited work

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

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Observation 4092c3f0-2f1a-47bd-a327-bdd68d4509b6 · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:08:48.244094Z

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=2026-08-15T21:08:46.837162Z digest=sha256:e1224c2ce8f491aea08aeac8aef1db181554dcc4637262fb257e5481a20d0f25

Observation fb5314c8-f3d5-45a1-9896-f1f134b83120 · outbound

This paper cites Predictable Artificial Intelligence.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Predictable Artificial Intelligence

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T21:08:46.925854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:08:46.925854Z digest=sha256:51b0657f7c8a3bc776a79c5de5f26edb041fa896e7c9cdfc37a598453bf7b5a9

Observation bf9a77ae-772a-4cf1-a33f-c1bbc1b4f41d · outbound

This paper cites Large Language Models Are Human-Level Prompt Engineers.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Large Language Models Are Human-Level Prompt Engineers

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T21:08:46.936065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:08:46.936065Z digest=sha256:20e827c44f4f03851758750ceba3510877380fdfec62455d80e62e4c3da0f8a4

Observation c3f059eb-766d-4a61-95e2-af5f4c04e2d3 · outbound

This paper cites online" 'onlinestring :=.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization online" 'onlinestring :=

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T21:08:47.045425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:08:47.045425Z digest=sha256:3fa12de68d1c06fc785aa8379bacc4dd277a0d65a3e42433899ed4283da782f6

Observation af9c4d93-6f9e-4cd6-9aa2-faacdd53b0d0 · outbound

This paper cites write newline.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization write newline

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T21:08:47.084080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:08:47.084080Z digest=sha256:3c2e2be83795c598881a8e83cd26baceb2c6e65238fc70bac6632735efc42460

Observation 2f501037-58b3-4d81-bd50-db54aaeb94df · outbound

This paper cites an unresolved cited work.

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:08:48.171504Z

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=2026-08-15T21:08:47.091294Z digest=sha256:a35736d0cd0b4845b224cbb33779021153e8b0dc089efeb7b97b30c663b0b476

Pith citing papers

No inbound Pith citation observations are available.