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Paper Citation Record · LEDGER

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals

As of 21 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2506.15208.

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

pith.paper-citation-record.v1
2506.15208 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

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measured 57 of 57 standing notices

One-hop event checks from named stored sources.

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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

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External citation measurements

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Outbound references

Observation d04c0814-c265-4ff1-b6d1-7105117d0366 · outbound

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 1

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 2

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This paper cites Hirai and F.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Hirai and F

Reference 3

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This paper cites Ziegler et al., ‘‘How to Measure Sustainability? An Open-Data Ap- proach’’,Sustainability, vol.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Ziegler et al., ‘‘How to Measure Sustainability? An Open-Data Ap- proach’’,Sustainability, vol

Reference 4

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 5

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Observation 626ab4f9-b71f-4212-bbe3-5a6cb9e43ff4 · outbound

This paper cites La Fleur, ‘‘Using large language models to help train machine learning SDG classifiers’’, UN DESA, Working Paper 180, Nov.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals La Fleur, ‘‘Using large language models to help train machine learning SDG classifiers’’, UN DESA, Working Paper 180, Nov

Reference 6

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Observation 46724535-ae6b-4a85-9bc2-bd4312d94a00 · outbound

This paper cites Nilashi, G.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Nilashi, G

Reference 7

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 8

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 9

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Guisiano and R

Reference 10

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Observation 67909d0b-9392-4520-ba57-59ee6f0b8864 · outbound

This paper cites Heras-Saizarbitoria, L.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Heras-Saizarbitoria, L

Reference 11

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Observation f6049b72-0764-47be-84d3-607b8e428e37 · outbound

This paper cites OSDG -- Open-Source Approach to Classify Text Data by UN Sustainable Development Goals (SDGs).

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals OSDG -- Open-Source Approach to Classify Text Data by UN Sustainable Development Goals (SDGs)

Reference 12

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals V aswani et al., ‘‘Attention is all you need’’, inProc

Reference 13

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This paper cites Devlin, M.-W.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Devlin, M.-W

Reference 14

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Observation 1191388b-1203-4b4a-8e07-20259c95a3a8 · outbound

This paper cites Brown et al., ‘‘Language Models are Few-Shot Learners’’, inAdvances in Neural Information Processing Systems, vol.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Brown et al., ‘‘Language Models are Few-Shot Learners’’, inAdvances in Neural Information Processing Systems, vol

Reference 15

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This paper cites Joshi, L.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Joshi, L

Reference 16

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This paper cites A Survey on Knowledge Organization Systems of Research Fields: Resources and Challenges.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals A Survey on Knowledge Organization Systems of Research Fields: Resources and Challenges

Reference 17

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Sovrano, M

Reference 18

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Schmidt and M

Reference 19

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Bolanos, A

Reference 20

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Y ang, T

Reference 23

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Motta, F

Reference 24

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Cascini, A

Reference 25

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Savelka and K

Reference 26

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Cadeddu, A

Reference 28

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Reference 29

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Pushing The Limit of LLM Capacity for Text Classification

Reference 30

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Reference 31

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection

Reference 32

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This paper cites MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals MiniCheck: Efficient Fact-Checking of LLMs on Grounding Documents

Reference 33

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Observation ce97d9ef-24a9-425c-b6c2-146feb0c6925 · outbound

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A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Cadeddu, A

Reference 34

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Observation e71f9d84-56ec-4f30-85d6-59fcc3b83501 · outbound

This paper cites Radford and K.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Radford and K

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c02c39b5-ab32-4694-91c4-f68153ce9cab · outbound

This paper cites Fields, K.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Fields, K

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation ef412a23-b1b8-468c-add0-26d19c89cc09 · outbound

This paper cites an unresolved cited work.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 72c1887e-53ad-4775-b49f-5ef1df25f374 · outbound

This paper cites an unresolved cited work.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ddb3c3b8-70c0-4488-bd47-48dd52165e8e · outbound

This paper cites Gasparetto, M.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Gasparetto, M

Reference 39

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d3b7321e-a0e6-4a2e-b029-8995e803df6f · outbound

This paper cites Y ang, H.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Y ang, H

Reference 40

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no resolver link, observed 2026-08-15T19:44:40.115384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:44:40.115384Z digest=sha256:a23ee8c6609de5883f470ea59fd72b58e0bc708e96271b4b6307eee3d8b638bd

Observation eab5515b-6bfd-474c-8050-14f61bc130a2 · outbound

This paper cites Bisong,Building Machine Learning and Deep Learning Models on Google Cloud Platform: A Comprehensive Guide for Beginners.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Bisong,Building Machine Learning and Deep Learning Models on Google Cloud Platform: A Comprehensive Guide for Beginners

Reference 41

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a24bc0d2-9606-42f3-ab09-9beec4fff656 · outbound

This paper cites Dettmers, A.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Dettmers, A

Reference 42

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d60ba7a6-2033-40fd-8eae-c6a07c95b68a · outbound

This paper cites an unresolved cited work.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 43

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b5fe3a78-3c5f-420b-a9ec-d0c13ca29e4f · outbound

This paper cites GPT-4 Technical Report.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals GPT-4 Technical Report

Reference 44

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a24545bf-714e-4d62-a5ff-7a76a659b127 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 45

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no resolver link, observed 2026-08-15T19:44:40.143438Z

Source-reported events for the cited work

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Observation 669c1a21-d68e-47e3-9f56-4650a027d4e0 · outbound

This paper cites Ainslie, J.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Ainslie, J

Reference 46

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 97400bba-207a-4012-b4ef-0834a7862df9 · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Scaling Instruction-Finetuned Language Models

Reference 47

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no resolver link, observed 2026-08-15T19:44:40.155747Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T19:44:40.155747Z digest=sha256:389668ee9bed6095f791e8c4fb816258156cbb3dbbf55960aa5f4940e7c40e7b

Observation 1f4dc4a7-5111-4138-bea9-60aa1eb34506 · outbound

This paper cites Raffel et al., ‘‘Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer’’,J.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Raffel et al., ‘‘Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer’’,J

Reference 48

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 182526fd-38bc-45e7-9f6d-d74d4e429df4 · outbound

This paper cites Mistral 7B.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Mistral 7B

Reference 49

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no resolver link, observed 2026-08-15T19:44:40.170240Z

Source-reported events for the cited work

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Observation 691c7377-5ff1-42d9-bf04-2fcaa91f7bd1 · outbound

This paper cites Mixtral of Experts.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Mixtral of Experts

Reference 50

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Observation cddada89-bd31-415c-87ce-0b7c10cbeebd · outbound

This paper cites Zephyr: Direct Distillation of LM Alignment.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Zephyr: Direct Distillation of LM Alignment

Reference 51

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no resolver link, observed 2026-08-15T19:44:40.182810Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:44:40.182810Z digest=sha256:05a95d3b636906c5c0dd41e99ea448a295911167a4d8a8981407b0cf124baeac

Observation aaaef0e0-7bf5-4996-9148-b8254546f991 · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 52

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no resolver link, observed 2026-08-15T19:44:40.188151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:44:40.188151Z digest=sha256:fe7f8de2a5d3ae657aee0460dcc8079bec4cb64b3e5438431e4c6f9559cc9245

Observation 96518f8c-c173-4eca-a2e4-6d0c18be8f6e · outbound

This paper cites an unresolved cited work.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:44:40.863959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d75b4cda-50a4-4b0b-9b07-f1be791149a3 · outbound

This paper cites Language Models for Text Classification: Is In-Context Learning Enough?.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Language Models for Text Classification: Is In-Context Learning Enough?

Reference 54

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no resolver link, observed 2026-08-15T19:44:40.199124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:44:40.199124Z digest=sha256:ccc861fcc4b5d00c4eadccd354b928396f042d1d12fed958cfa94de1da1dacdd

Observation d2117541-21df-4a9c-8c37-7b12e0694e2f · outbound

This paper cites Open, Closed, or Small Language Models for Text Classification?.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Open, Closed, or Small Language Models for Text Classification?

Reference 55

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no resolver link, observed 2026-08-15T19:44:40.204377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:44:40.204377Z digest=sha256:3d63d2d1fdbb02a88bc6483d0ded0cce501094fd191185ca1ff1c239575b74ce

Observation 56291963-6f27-4e29-9a54-b1f4063f8ee3 · outbound

This paper cites an unresolved cited work.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-15T19:44:40.842804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T19:44:40.210090Z digest=sha256:0373a87f3623da774bf88be752b4a19a930116013c08adf0cc4a8c28feea1b3d

Observation 29c45efa-774c-4ee8-a325-a809e3f772d6 · outbound

This paper cites an unresolved cited work.

A Comparative Study of Task Adaptation Techniques of Large Language Models for Identifying Sustainable Development Goals Unresolved cited work

Reference 2007

Resolution
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raw_fallback, observed 2026-08-15T19:44:40.825295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T19:44:40.215433Z digest=sha256:7fd1a596bb0c3a4f52a0fcdcd8cf19687986c7db271a3da5eb3d58f4553f3931

Pith citing papers

No inbound Pith citation observations are available.