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Paper Citation Record · LEDGER

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI

As of 12 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2412.13942.

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

pith.paper-citation-record.v1
2412.13942 v2

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:42:05.436235Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

57 of 57 outbound references displayed

  • verified exact5
  • verified fuzzy2
  • unresolved48
  • parse uncertain0
  • malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e1b62f14-1740-4bba-95ed-df8fc4bf5dd6 · outbound

This paper cites online" 'onlinestring :=.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI online" 'onlinestring :=

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5b38205a-a6b9-4ba0-8029-50f423c409d6 · outbound

This paper cites write newline.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI write newline

Reference 2

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source=arxiv_source observed=2026-08-11T12:42:05.094358Z digest=sha256:ce0829bfc1b37162130037ff1f438751127f3b89275c3611682b20094212b6ad

Observation 7f547153-3e69-48b7-ab4a-2269113fcb88 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 3

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Observation 63b9161c-018d-4291-9155-3f8781f19958 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 4

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Observation 55eaaada-384b-46a5-a1b0-97b0eff2d009 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 5

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Unavailable: canonical work link unavailable.

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Observation 4167c3b4-1a42-4ae6-a200-88fc20887cf1 · outbound

This paper cites Bowman, Gabor Angeli, Christopher Potts, and Christopher D.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Bowman, Gabor Angeli, Christopher Potts, and Christopher D

Reference 6

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Observation caaad0d4-7d34-424f-818f-0ca8829bdcea · outbound

This paper cites seeing the big through the small.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI seeing the big through the small

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation f5631034-a683-402a-9546-0e03c101b76d · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 8

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Unavailable: canonical work link unavailable.

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Observation 6e0f5945-75ad-4823-be27-a5d3dfd47dcb · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 9

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This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 10

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Observation c108c62f-b9d1-462d-9246-f0ca90c500a8 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 11

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Source-reported events for the cited work

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Observation 7a3b830a-4453-4ceb-ad8b-1094fca02687 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 12

Resolution
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Source-reported events for the cited work

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Observation 25d8d07b-2b5a-4cbd-b5ed-d638071231e4 · outbound

This paper cites Questioning the Survey Responses of Large Language Models.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Questioning the Survey Responses of Large Language Models

Reference 13

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Observation 3eb7caea-48e2-4e05-ba8d-df6eadbd35d0 · outbound

This paper cites The Llama 3 Herd of Models.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI The Llama 3 Herd of Models

Reference 14

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Observation b94a8631-1e1e-4a23-9ce1-05e4007e4b66 · outbound

This paper cites Towards Measuring the Representation of Subjective Global Opinions in Language Models.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Towards Measuring the Representation of Subjective Global Opinions in Language Models

Reference 15

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Observation ce528564-924b-4288-8b6b-d20ef7c9e41e · outbound

This paper cites Schindelin.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Schindelin

Reference 16

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Observation ac94aaf9-145b-4f51-adb5-96de15225821 · outbound

This paper cites How well can a large language model explain business processes as perceived by users?.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI How well can a large language model explain business processes as perceived by users?

Reference 17

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Observation 4aace364-8915-4f05-a09e-e0f23b68051b · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 18

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Observation c1f669a1-da62-45d9-ac8e-d6b2a302a7a8 · outbound

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 19

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Source-reported events for the cited work

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Observation 81305353-dfda-446d-950f-68d8ad0d434a · outbound

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 20

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Observation 83ae7501-b4d8-4042-be76-06c7dfd9c419 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 21

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Observation 5815f4f6-cbde-40c7-a135-0b8e484b4c5a · outbound

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations

Reference 22

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Observation 1bbcac9a-c8da-4a58-9987-2b1f3c27407c · outbound

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Mixtral of Experts

Reference 23

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This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 24

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This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 25

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Observation 3d0211ef-7474-4b08-8119-d2169ed99c3a · outbound

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Properties and Challenges of LLM-Generated Explanations

Reference 26

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This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 27

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Explanations from Large Language Models Make Small Reasoners Better

Reference 28

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI u ksekg \

Reference 29

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This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 30

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 31

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Unavailable: canonical work link unavailable.

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This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 32

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Source-reported events for the cited work

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Observation e2a8e865-ad7a-4e9a-88d9-aec9a2e75332 · outbound

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Lost in Inference: Rediscovering the Role of Natural Language Inference for Large Language Models

Reference 33

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 34

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Source-reported events for the cited work

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A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 35

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Observation ec374fd4-25bf-49eb-aa3f-a252781ac958 · outbound

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Reference 36

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Observation 94ac5c23-9fba-4ceb-a4ff-8babe5f5c694 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 37

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ce4e8fdd-a2fa-475e-b304-4d29ed54a9eb · outbound

This paper cites GPT-4 Technical Report.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI GPT-4 Technical Report

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T12:42:05.316520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 7f1c8d29-44d0-4389-b09c-2b170e3c2662 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-08-11T12:42:07.160711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 93174d5c-1913-4954-b3a8-e8ef3f81f17d · outbound

This paper cites Understanding The Effect Of Temperature On Alignment With Human Opinions.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Understanding The Effect Of Temperature On Alignment With Human Opinions

Reference 41

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation bc259f0c-ec4e-4158-af53-aebc0bf360f1 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 42

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 770dd892-2485-4bb9-ba4b-55b08a8b628b · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 43

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation af8c011b-4c4e-4ec6-8589-82244194be8c · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 44

Resolution
verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0270e013-3493-462e-b544-85d4c64c1afd · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-11T12:42:07.129690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation c07254b3-6c63-4ee5-9255-6fc2b39f3fd9 · outbound

This paper cites Brown, Adam Santoro, Aditya Gupta, Adri \` a Garriga - Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Brown, Adam Santoro, Aditya Gupta, Adri \` a Garriga - Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T12:42:07.093670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 10a505e6-34d3-429b-aed5-bd58dc8ba665 · outbound

This paper cites Székely, Maria L.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Székely, Maria L

Reference 47

Resolution
verified exact
raw_fallback, observed 2026-08-11T12:42:06.551588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation daabbf6d-a1af-4a75-a2cb-643a56433bb0 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-11T12:42:05.375371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:42:05.375371Z digest=sha256:e4ed4375db591c12fc0fb7f197ec38866eba6c51bbb3fd4bc6e4333a5caa9ceb

Observation 99487e48-8745-42f4-9d8c-614508337d8a · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-11T12:42:07.049587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 833d1d85-fb22-4e03-a7e6-1fba2636d685 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 50

Resolution
malformed identifier
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 118d0d3a-846b-4311-b383-97f623d0893f · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T12:42:05.392939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4bc1ca67-1956-4536-b2d1-4a3c977c0a88 · outbound

This paper cites Using Natural Language Explanations to Rescale Human Judgments.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Using Natural Language Explanations to Rescale Human Judgments

Reference 52

Resolution
verified exact
local_arxiv, observed 2026-08-11T12:42:05.543844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 52d6fdb9-c6c6-4d05-abd8-1184356cd1a6 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T12:42:05.404322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 869aa0fc-9189-40cc-9f4d-787a545fabf4 · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-11T12:42:05.409759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:42:05.409759Z digest=sha256:c3991483efe85a2226ffeea53cbb479197bef2eaeb3bac0c03accc8952d060fd

Observation 3fe7866d-eef9-471c-a38b-3c0d127f84fe · outbound

This paper cites Riedl, and Yejin Choi.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Riedl, and Yejin Choi

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-11T12:42:05.418100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation cfc4327d-78c0-435e-9ddf-32c7ca814cda · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-11T12:42:05.423506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T12:42:05.423506Z digest=sha256:a914b6276f61265e6ebb8c959926fa6f752da1a6e3a93113cdcff26c3843497e

Observation e36f61ea-15a0-4b17-b5ec-e215c31ea91c · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 57

Resolution
unresolved
raw_fallback, observed 2026-08-11T12:42:07.017982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T12:42:05.430676Z digest=sha256:aba78c3ef18444cc973672838898af0ad22054d592c68d157f402d7c43561173

Observation ab39ddbd-3d04-4c90-a042-e200f071c1cd · outbound

This paper cites an unresolved cited work.

A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI Unresolved cited work

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-11T12:42:05.436235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.