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Paper Citation Record · LEDGER

Causal Prompting for Implicit Sentiment Analysis with Large Language Models

As of 19 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2507.00389.

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

pith.paper-citation-record.v1
2507.00389 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:26:00.140899Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

43 of 43 outbound references displayed

  • verified exact0
  • verified fuzzy35
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 87b8c3f9-096a-4eb4-8060-51da303a782f · outbound

This paper cites Exploring public sentiment during covid-19: A cross country analysis,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Exploring public sentiment during covid-19: A cross country analysis,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation cc9be122-da75-474d-98b6-7cdaccfa11cf · outbound

This paper cites Reasoning implicit sentiment with chain-of-thought prompting,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Reasoning implicit sentiment with chain-of-thought prompting,

Reference 2

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raw_fallback, observed 2026-08-06T21:26:00.592768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation fb37cc58-7ede-4be7-bad3-a1db13f7f0e4 · outbound

This paper cites Causal prompting: Debiasing large language model prompting based on front-door adjust- ment,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Causal prompting: Debiasing large language model prompting based on front-door adjust- ment,

Reference 3

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raw_fallback, observed 2026-08-06T21:26:00.582604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 516ebf11-27cf-4959-9ac7-3e5b82e699f7 · outbound

This paper cites Decot: Debiasing chain-of-thought for knowledge-intensive tasks in large language models via causal intervention,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Decot: Debiasing chain-of-thought for knowledge-intensive tasks in large language models via causal intervention,

Reference 4

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raw_fallback, observed 2026-08-06T21:26:00.572405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 598fa410-3dd2-41c7-946a-369423021a2d · outbound

This paper cites Implicit aspect extraction in sentiment analysis: Review, taxonomy, oppportunities, and open challenges,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Implicit aspect extraction in sentiment analysis: Review, taxonomy, oppportunities, and open challenges,

Reference 5

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raw_fallback, observed 2026-08-06T21:26:00.561085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c1f34dd7-c03b-45a5-8ec2-3635e1aa9932 · outbound

This paper cites Convolutional neural network for sentence classification,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Convolutional neural network for sentence classification,

Reference 6

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raw_fallback, observed 2026-08-06T21:26:00.551077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8f46d6b7-31c1-452a-bd9e-995cb0df6d04 · outbound

This paper cites Document modeling with gated recurrent neural network for sentiment classification,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Document modeling with gated recurrent neural network for sentiment classification,

Reference 7

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raw_fallback, observed 2026-08-06T21:26:00.540342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d6125f39-d566-45c0-8bc3-7863cd7679a6 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 8

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raw_fallback, observed 2026-08-06T21:26:00.530407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 05cacac0-a469-498f-9255-ccc04bbef77b · outbound

This paper cites A contrastive cross-channel data augmentation framework for aspect-based sentiment analysis,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models A contrastive cross-channel data augmentation framework for aspect-based sentiment analysis,

Reference 9

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raw_fallback, observed 2026-08-06T21:26:00.519567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e91abc3d-112d-4d9e-a6ca-24357218dfef · outbound

This paper cites Learning implicit sentiment in aspect-based sentiment analysis with supervised contrastive pre-training,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Learning implicit sentiment in aspect-based sentiment analysis with supervised contrastive pre-training,

Reference 10

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raw_fallback, observed 2026-08-06T21:26:00.508000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 86792e57-8383-46bf-a58f-8a5b16fc447e · outbound

This paper cites Relational graph attention network for aspect-based sentiment analysis,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Relational graph attention network for aspect-based sentiment analysis,

Reference 11

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raw_fallback, observed 2026-08-06T21:26:00.497328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 26b6055d-dae1-42d7-bea4-99518d7e843e · outbound

This paper cites Sentiment analysis in the era of large language models: A reality check,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Sentiment analysis in the era of large language models: A reality check,

Reference 12

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raw_fallback, observed 2026-08-06T21:26:00.486850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7086f2a0-b9e8-47d2-b217-4ca6b8ee36a9 · outbound

This paper cites Aspect- based sentiment analysis with explicit sentiment augmentations,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Aspect- based sentiment analysis with explicit sentiment augmentations,

Reference 13

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raw_fallback, observed 2026-08-06T21:26:00.475788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 0904d507-de26-4b10-aac8-6b14644538df · outbound

This paper cites Rvisa: reasoning and verification for implicit sentiment analysis,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Rvisa: reasoning and verification for implicit sentiment analysis,

Reference 14

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raw_fallback, observed 2026-08-06T21:26:00.464848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation d129f991-2ae9-48c1-b1a9-802191d5227a · outbound

This paper cites Causal prompting: Debiasing large language model prompting based on front-door adjust- ment,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Causal prompting: Debiasing large language model prompting based on front-door adjust- ment,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.454896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9798ccde-d5bc-409c-8226-8ab33e227bf7 · outbound

This paper cites A comprehensive survey of prompt engineering techniques in large language models,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models A comprehensive survey of prompt engineering techniques in large language models,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 2227735b-7f38-4a67-961a-9878e3beed35 · outbound

This paper cites Language models are few-shot learners,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Language models are few-shot learners,

Reference 17

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raw_fallback, observed 2026-08-06T21:26:00.433103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9085265a-10c7-4a54-b79f-1dbc4d04cdf5 · outbound

This paper cites Prompt programming for large language models: Beyond the few-shot paradigm,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Prompt programming for large language models: Beyond the few-shot paradigm,

Reference 18

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raw_fallback, observed 2026-08-06T21:26:00.422849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation fd599780-7e69-4f7d-a86c-3153370ab525 · outbound

This paper cites A Survey of Automatic Prompt Engineering: An Optimization Perspective.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models A Survey of Automatic Prompt Engineering: An Optimization Perspective

Reference 19

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Source-reported events for the cited work

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Observation c90f97b7-626d-45ad-8f7e-2fb7c4c05959 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Chain-of-thought prompting elicits reasoning in large language models,

Reference 20

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no resolver link, observed 2026-08-06T21:25:59.054940Z

Source-reported events for the cited work

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Observation c5d2e467-e642-4482-b1b4-d458b0b1910a · outbound

This paper cites Self-consistency improves chain of thought reasoning in language models,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Self-consistency improves chain of thought reasoning in language models,

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e90979d1-215b-4061-b22c-dc612bbf0b5c · outbound

This paper cites Pearl, M.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Pearl, M

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3fcb468e-8bbd-49e3-8f88-20ef167c263e · outbound

This paper cites Disen- tangled representation learning for causal inference with instruments,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Disen- tangled representation learning for causal inference with instruments,

Reference 23

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raw_fallback, observed 2026-08-06T21:26:00.396258Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:25:59.251382Z digest=sha256:67e6968dcc14aba29f5fba8627c2cc53f58661cedc2020fe602f9c82492fdfe3

Observation 6d7c18b5-3046-451b-be43-57f03be6b537 · outbound

This paper cites Causal infer- ence with conditional front-door adjustment and identifiable variational autoencoder,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Causal infer- ence with conditional front-door adjustment and identifiable variational autoencoder,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.385471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation ac27b5de-7c5b-4e39-97a7-5e698bbf63d0 · outbound

This paper cites Conditional instrumental variable regression with representation learning for causal inference,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Conditional instrumental variable regression with representation learning for causal inference,

Reference 25

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raw_fallback, observed 2026-08-06T21:26:00.374602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation f6f673a1-7109-49d2-8a26-d63d4c4474ee · outbound

This paper cites Instrumental variable estimation for causal inference in longitudinal data with time-dependent latent confounders,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Instrumental variable estimation for causal inference in longitudinal data with time-dependent latent confounders,

Reference 26

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raw_fallback, observed 2026-08-06T21:26:00.361759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 08f26a11-14a4-4aef-91cb-28b5791b3be1 · outbound

This paper cites Causal inference with conditional instruments using deep generative models,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Causal inference with conditional instruments using deep generative models,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.349895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation afb118c9-c8b7-42d0-8288-5774b5888c53 · outbound

This paper cites Learning condi- tional instrumental variable representation for causal effect estimation,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Learning condi- tional instrumental variable representation for causal effect estimation,

Reference 28

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raw_fallback, observed 2026-08-06T21:26:00.339740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation aa00b3f4-249a-455d-af5f-b193709d0470 · outbound

This paper cites Causal intervention improves implicit sentiment analysis,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Causal intervention improves implicit sentiment analysis,

Reference 29

Resolution
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raw_fallback, observed 2026-08-06T21:26:00.329088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:25:59.619993Z digest=sha256:10217a1510fbe65177dc39c8782a445426f2796c693b1684cb56a2edeba2ffc8

Observation 66f6ee0a-b0fe-4c5e-8efa-904caec81f41 · outbound

This paper cites Causalqa: A benchmark for causal question answering,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Causalqa: A benchmark for causal question answering,

Reference 30

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raw_fallback, observed 2026-08-06T21:26:00.316492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:25:59.685946Z digest=sha256:31f56626ae62c6621b71addfc67f69b6981bbd777940c0f72b75fa361ceaced3

Observation 2b939bd8-0728-4cd9-9ac6-192160424ee5 · outbound

This paper cites Pearl, Causality.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Pearl, Causality

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T21:25:59.757433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:25:59.757433Z digest=sha256:a08e8ee8c65e7f4d48d8e2f8696a8a76f97ea8af99a8434f703f94f4c774d4c7

Observation 8df5e34f-3ba8-415b-b22c-baf5ad66cd20 · outbound

This paper cites Intrinsic dimensionality explains the effectiveness of language model fine-tuning,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Intrinsic dimensionality explains the effectiveness of language model fine-tuning,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.300506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:25:59.799912Z digest=sha256:2e2580a822fc8a84b33cb3754f95353672e2cf2ca933ade60984107ce862e18d

Observation 6648a983-91f8-4077-8f2a-f9bd5104492e · outbound

This paper cites Parameter-efficient fine-tuning of large- scale pre-trained language models,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Parameter-efficient fine-tuning of large- scale pre-trained language models,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.288499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:25:59.888571Z digest=sha256:c411fb4fc3a50d4af7f8353fde4c46640229b339ab70bcf2bf1492bb709279e8

Observation 87e65173-cb9b-4a0d-b805-af9e84f2afde · outbound

This paper cites Debiasing nlu models via causal intervention and counterfactual reasoning,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Debiasing nlu models via causal intervention and counterfactual reasoning,

Reference 34

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raw_fallback, observed 2026-08-06T21:26:00.277408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:25:59.961011Z digest=sha256:74fcb0ec3765e6355d78f8c1118aa65337c2e8bc0ce85a597a71552216dda45f

Observation 8a5c15bc-68fc-42d0-9b6d-cf347899073b · outbound

This paper cites Causal intervention and counterfactual reasoning for multi-modal fake news detection,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Causal intervention and counterfactual reasoning for multi-modal fake news detection,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.266951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:26:00.018447Z digest=sha256:8538307e513bdf100ab8d43a157004bf0ade9ba7b72bbf29ccf45681d1503661

Observation f9ec50bc-6a3d-4f87-8e16-3e2d7b26fe2f · outbound

This paper cites Active learning principles for in-context learning with large language models,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Active learning principles for in-context learning with large language models,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.254875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:26:00.073461Z digest=sha256:01bcf9979999693ee13592d119dc03d6e3bcce24432d0382df8c7f283466ccf0

Observation 237517f3-6040-48f5-8fd3-b1504528b9ad · outbound

This paper cites Semeval-2016 task 5: Aspect based sentiment analysis,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Semeval-2016 task 5: Aspect based sentiment analysis,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.242895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:26:00.109585Z digest=sha256:bb60c7b0cdc2fe85cde78a30d825d2fc31074d8ba85be3b70dcede226fc34d57

Observation 1cb7fb46-5c63-4644-91cb-b1c6e19a0e24 · outbound

This paper cites Language models are few-shot learners,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Language models are few-shot learners,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.230895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:26:00.122166Z digest=sha256:08cfbcdafb045005625876b3cb93fb9739cc8ec715de02070c83faa5fa5ad87c

Observation b2a7c403-7a8c-4164-9c6c-114735db61cc · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Chain-of-thought prompting elicits reasoning in large language models,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T21:26:00.125835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:26:00.125835Z digest=sha256:921d5b592c75ffc7a7be81fecbfe02050a39f9fc09b56becff5a4cfcf638f077

Observation ddc6ee54-7522-43e0-90ef-5aae1f8c5a09 · outbound

This paper cites Trusting your evidence: Hallucinate less with context-aware decoding,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Trusting your evidence: Hallucinate less with context-aware decoding,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.212821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:26:00.129499Z digest=sha256:26ef156e35f2145b48fd9ee26cb7ceca3039bc45325501c6a1d25f98196e3cf2

Observation cd1afb36-c7e0-4aa4-ac3d-3e8cf845283f · outbound

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

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T21:26:00.133244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:26:00.133244Z digest=sha256:b4d71923b4ee06c02413b1a17677191b4ffc5c6293c017ccc4cd4fc0792fc27b

Observation 3e2d27dd-489a-4c57-86b8-fadaa5e24094 · outbound

This paper cites How Likely Do LLMs with CoT Mimic Human Reasoning?.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models How Likely Do LLMs with CoT Mimic Human Reasoning?

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T21:26:00.136729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:26:00.136729Z digest=sha256:22036e7db6eb44fb4f10038a700491858124db672ec86290699e07a4dfbb8ff2

Observation cdd981fe-0664-4dd9-86fe-15ed17441a81 · outbound

This paper cites Language models are few- shot learners,.

Causal Prompting for Implicit Sentiment Analysis with Large Language Models Language models are few- shot learners,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:26:00.202960Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T21:26:00.140899Z digest=sha256:bcc099d51d410cec24456ab255ef7a81b23d6e2238e22baadb0f3b131e797d80

Pith citing papers

No inbound Pith citation observations are available.