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Paper Citation Record · LEDGER

Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization

As of 17 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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raw_fallback, observed 2026-08-15T21:08:49.329095Z

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=sha256:79a766fcf488cf06caa6f8406a3aa009904368594e8a873a1229cf8acba0a30e

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:b4c9b5a12d2df15fc469e7ebe4e52c0e996457e0c8499d694bc30e77e50d0f4e

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:d073e6cf36b11fc4fe57b8c3761604a522b72f04531fd5595bd9686183256f82

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=sha256:7a0162705451960219ef4dad1a45a40055bc12446db64755e6bf726963af6824

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:c3413e8d47487212e75b9eab8b785c35531065021836eec00886b490da72993d

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=sha256:0136cf7a8e76f5c2595ce0c588ad73efbcaa2666e9ccb3df4be49038ee52effb

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:dbc5edc4ac4cbdae066fed4a9ec95a6db5a68da0fd608e64008adacc000eacbb

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=sha256:5fd37167b0eaa54fa6dc6eb0b0c877db1dceb9756bdc1dfa80db8a335ad02d04

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=sha256:3901f334074a7de85feceda086dffd7faadec87ff9b3ceaa76762508e5952813

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=sha256:276e941ebbf6799e2e0aec2d2df12b59b31b5af7e7edf12ab4b65bb9f08dd203

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=sha256:5ddd715a533d0e9eec75a82faa502184b42dd1d4922050441a8860ae38a3585a

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=sha256:40607eec56e35515a8c299e2a22965c81ddfb682debaedbba5f0a809e5fb9a32

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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source=arxiv_source observed=2026-08-15T21:08:45.649648Z digest=sha256:ec5c8cafb4033223b4787b647c65916acb349d7376aad6d97950ce976927baa2

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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source=arxiv_source observed=2026-08-15T21:08:45.717835Z digest=sha256:88ae3fb83d2ddf5ac60c099e13c7ac0e83eb55dcd87bd3aca8c5e439d0a32b32

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=sha256:4ce289be43829e5dfe86bf666bb0434c4d4387e69c18769778b77760bc7b1ac2

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:d060538119869cafeb2ccbea695588c32f086e37e8a48672ca3c89e7f6df23a4

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=sha256:799bebbe4455bb8fe51f878b3746c38850625aea80a516bfc6aef1b24dea00e7

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:a4a830f31703b74d1cd99007c5232227c62bbc5ea039f2e4e5ad89e469a2eaa1

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=sha256:862bb384d1c066fadcc8998ccf941975997a105c039aff617bb148eeb751ca2d

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:a60221798ac7ab24c1300322978a1099cdd2e83e04373d40a34fa7bd0b146de4

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=sha256:0de007b6cff4a71f9e65d15c09089c8f8fe60e1482efba3783e91ca41010167e

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:f876499633056b55b4a2e672e93c63c3e6882a555995e17278c1ec766be83211

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:ebab2ba336d82547b0b051d13c07223fc5a92fa9662aa5b2dbc348d7422ffe07

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=sha256:014b3c2432fe455c80a2f78f3db7afc66576de664c0ae4854582b721fba72c07

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:c61ad106bacf530c1e0fe2e7a8aae2d06a29d7828f0c36e5a79677012e6158ce

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:bb92440c3c8ea36c65fe057ca61a1bf1321f4cd556021552e2efc63b16bc55df

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:f41e22c888515d6656146cab288ecbff18c1870cf50fdd38575678ba74c6a97b

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=sha256:99def5ec870a45e64bbb63c685b8f5b061dbdf804e483b5ec55f9c7533bbde06

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=sha256:9c834298774916493713ebf7d5e397960227f603b592843fdc9b49714d97075f

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=sha256:85a6955b8a7d18d3820e09b072dd959288c7808052d88dff47ababd06f797f6a

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=sha256:210b2b3156d433c64305b6b79de701ac813f23c181d60800da40bf0237143e58

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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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=sha256:359aabe325cbbac6e6858a4654fd991110402a59643875ff4622364518a42dcb

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=sha256:9fae9f6b9b5891113112cca9f61f00fae7a2c01182bc583d8aa76cb7bbfb0e22

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:08:46.630311Z digest=sha256:f7971555fd2824ce496f5101bb9a04bd262604e1a7ac518297434e9c639bb28f

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=sha256:3527a37ac70748ea6c8addbad91450ef1b05f26e4cd403b9cf13335416442405

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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source=arxiv_source observed=2026-08-15T21:08:46.705488Z digest=sha256:c4b4d64be08d3d8742b08199093f587569e6abe4b5c426f26b5959e5be693e58

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=sha256:64d96c65a0151a5cf6a3a57bac74928f461a88122faaaaab6276ca45d193fc0f

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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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
doi, observed 2026-08-15T21:08:47.308306Z

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=2026-08-15T21:08:46.829163Z digest=sha256:bfedc7e71af12f6e5d38174a12d4eaea10bc4ce87cee00b63e20bdc9d2f9530a

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:b752c4a064b81ae6217990fe41056db99d82373e04991925d03a01042a45434a

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=sha256:1094f4b6b211999565a272424c9846538ff180016627dd8b2258cb6346d3a391

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=sha256:2c258a8e2fbccb3174b4a3bffb8043cc74ed6189be244d7aab4fccb11cd8764e

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:c27b53dc23ccd9cb9b3525c6cf0dd8e7866861099dc4da922394a3470e110f3c

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=sha256:1bff5e89e67b8587b258029f00a06cfd5177fc7bcd0caca4d3f03267829f51a0

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:e44a0d0a6b4c5d79026bf3c5673da20eb2a8696d47548ced4d3b9134f53ba8c3

Pith citing papers

No inbound Pith citation observations are available.