Paper Citation Record · LEDGER

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models

As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2506.03182.

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

pith.paper-citation-record.v1
2506.03182 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

41 of 41 outbound references displayed

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External citation measurements

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Outbound references

Observation da9dc144-4d66-48d5-a5cf-4c870c1057f2 · outbound

This paper cites Numbers of insects (species and individuals).

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Numbers of insects (species and individuals)

Reference 1

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Unresolved cited work

Reference 2

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Unresolved cited work

Reference 3

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This paper cites Forces of change.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Forces of change

Reference 4

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Observation d01dff3c-fea6-443e-a154-26d6bc823c0e · outbound

This paper cites Xprize rainforest names limelight rainforest winner of biodi- versity tech competition.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Xprize rainforest names limelight rainforest winner of biodi- versity tech competition

Reference 5

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Observation b0a7f6ba-e652-439c-9329-247349bb9564 · outbound

This paper cites Our team | limelight rainforest.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Our team | limelight rainforest

Reference 6

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Observation 6c22a689-3ca3-4bf2-be35-e2c6702ac9ed · outbound

This paper cites From bugs and birds to drones and dna.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models From bugs and birds to drones and dna

Reference 7

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Observation 9d148786-4d7c-4335-b399-0f4790ee47d7 · outbound

This paper cites Experts in insect taxonomy threat- ened with extinction, reveals first european red list.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Experts in insect taxonomy threat- ened with extinction, reveals first european red list

Reference 8

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Observation 4f6f9b91-dd4e-4bf4-8bdf-264244da8ff9 · outbound

This paper cites BioCLIP: A vision foundation model for the tree of life.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models BioCLIP: A vision foundation model for the tree of life

Reference 9

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Observation 72dfcbc8-cbac-4098-8a39-44f36bc09e73 · outbound

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Unresolved cited work

Reference 10

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Observation 1121a038-288e-4d54-bc16-f38f293d5e09 · outbound

This paper cites Wang, Xiaoliang Huo, Joakim Bruslund Haurum, Scott C.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Wang, Xiaoliang Huo, Joakim Bruslund Haurum, Scott C

Reference 11

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Observation ea209812-247e-4a1f-bc62-f3c15f39e003 · outbound

This paper cites The inaturalist species classification and detection dataset.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models The inaturalist species classification and detection dataset

Reference 12

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This paper cites What is gbif? https://www.gbif.org/ what-is-gbif.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models What is gbif? https://www.gbif.org/ what-is-gbif

Reference 13

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Observation 7cd68418-37a1-41fd-8eff-134388ed0a74 · outbound

This paper cites Benchmarking Representation Learning for Natural World Image Collections.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Benchmarking Representation Learning for Natural World Image Collections

Reference 14

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Observation 6f733d95-39f5-4109-9e27-7f5cadb33cd3 · outbound

This paper cites Scheirer, Anderson de Rezende Rocha, Archana Sapkota, and Terrance E.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Scheirer, Anderson de Rezende Rocha, Archana Sapkota, and Terrance E

Reference 15

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This paper cites Yanayacu biological station and center for creative studies.https: //www.facebook.com/Yanayacustation/, 2025.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Yanayacu biological station and center for creative studies.https: //www.facebook.com/Yanayacustation/, 2025

Reference 16

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Observation 0caeac12-dc52-4d64-9a9f-66c80d4a5335 · outbound

This paper cites Pitkin, Nadine Hilt, and Konrad Fiedler.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Pitkin, Nadine Hilt, and Konrad Fiedler

Reference 17

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This paper cites A new led lamp for the collection of nocturnal lepidoptera and a spectral comparison of light-trapping lamps.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models A new led lamp for the collection of nocturnal lepidoptera and a spectral comparison of light-trapping lamps

Reference 18

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Observation 7117fca8-c9ce-48a1-ae71-49b9294cc66d · outbound

This paper cites Moths are strongly attracted to ultraviolet and blue radiation.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Moths are strongly attracted to ultraviolet and blue radiation

Reference 19

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Observation f68a6d1a-e64c-4b19-a2f5-2e6a60689430 · outbound

This paper cites Lowe, Jaclyn T.A.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Lowe, Jaclyn T.A

Reference 20

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This paper cites Lowe, ZeMing Gong, Pablo Millan Arias, Nicholas Pellegrino, Austin T.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Lowe, ZeMing Gong, Pablo Millan Arias, Nicholas Pellegrino, Austin T

Reference 21

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This paper cites A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks

Reference 22

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This paper cites Singh, Soumik Sarkar, Arti Singh, and Baskar Ganapathysubramanian.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Singh, Soumik Sarkar, Arti Singh, and Baskar Ganapathysubramanian

Reference 23

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Unresolved cited work

Reference 24

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This paper cites Out-of-distribution detection via deep multi-comprehension ensemble, 2024.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Out-of-distribution detection via deep multi-comprehension ensemble, 2024

Reference 25

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This paper cites Deep Anomaly Detection with Outlier Exposure.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Deep Anomaly Detection with Outlier Exposure

Reference 26

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This paper cites Feed two birds with one scone: Exploiting wild data for both out-of-distribution generalization and detection, 2023.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Feed two birds with one scone: Exploiting wild data for both out-of-distribution generalization and detection, 2023

Reference 27

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Neco: Neural collapse based out-of-distribution detection, 2024

Reference 28

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This paper cites Christian Schmidt, Aditya Jain, Yves Basset, Sara Beery, Maxim Larrivée, and David Rolnick.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Christian Schmidt, Aditya Jain, Yves Basset, Sara Beery, Maxim Larrivée, and David Rolnick

Reference 29

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This paper cites Insectset459: an open dataset of insect sounds for bioacoustic machine learning, 2025.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Insectset459: an open dataset of insect sounds for bioacoustic machine learning, 2025

Reference 30

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This paper cites Taxonomic bias in biodiversity data and societal preferences.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Taxonomic bias in biodiversity data and societal preferences

Reference 31

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks

Reference 32

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Energy-based Out-of-distribution Detection

Reference 33

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Long-tailed out-of-distribution detection via normalized outlier distribution adaptation, 2024

Reference 34

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Learning multiple layers of features from tiny images

Reference 35

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Open-set recognition in the age of vision-language models

Reference 36

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Benchmarking out-of-distribution detection in visual question answering

Reference 37

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This paper cites Classifying the unknown: Insect identification with deep hierarchical bayesian learning.

TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Classifying the unknown: Insect identification with deep hierarchical bayesian learning

Reference 38

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Open-set recognition: a good closed-set classifier is all you need?, 2022

Reference 39

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models From coarse to fine-grained open-set recognition

Reference 40

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TerraIncognita: A Dynamic Benchmark for Species Discovery Using Frontier Models Unresolved cited work

Reference 2024

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Pith citing papers

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