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Paper Citation Record · LEDGER

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis

As of 8 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2507.12126.

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

pith.paper-citation-record.v1
2507.12126 v1

Coverage vector

measured 63 of 63 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:58:25.312915Z

measured 63 of 63 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

63 of 63 outbound references displayed

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  • unresolved21
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0dd2406b-f1eb-4d8d-a437-18444fc9792b · outbound

This paper cites an unresolved cited work.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Unresolved cited work

Reference 1

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This paper cites an unresolved cited work.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Unresolved cited work

Reference 2

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Observation 7d83607f-cbc3-4691-9000-14a29942345d · outbound

This paper cites hot” and “cold.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis hot” and “cold

Reference 3

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This paper cites Topic models.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Topic models

Reference 4

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Source-reported events for the cited work

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Observation b8c357eb-8ed0-49c6-a4f1-734e96ab3555 · outbound

This paper cites Enhancing BERTopic with Pre-Clustered Knowledge: Reducing Feature Sparsity in Short Text Topic Modeling,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Enhancing BERTopic with Pre-Clustered Knowledge: Reducing Feature Sparsity in Short Text Topic Modeling,

Reference 5

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Source-reported events for the cited work

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Observation 41dd7e58-5a71-4d7c-9597-317aecf8a851 · outbound

This paper cites Natural language processing: state of the art, current trends and challenges,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Natural language processing: state of the art, current trends and challenges,

Reference 6

Resolution
verified exact
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Observation 39a23df3-eb7b-4bd6-b31d-39f2afa91da6 · outbound

This paper cites A survey on sentiment analysis methods, applications, and challenges,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis A survey on sentiment analysis methods, applications, and challenges,

Reference 7

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Source-reported events for the cited work

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Observation 1ffa23f0-9255-4884-ac1f-e20c9d17079a · outbound

This paper cites A complete process of text classification system using state‐of‐the‐art NLP models.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis A complete process of text classification system using state‐of‐the‐art NLP models

Reference 8

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Source-reported events for the cited work

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Observation 7bf00176-e150-4f8c-8a5a-e052792c83ce · outbound

This paper cites Topic Modeling for Small Data using Generative LLMs.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Topic Modeling for Small Data using Generative LLMs

Reference 9

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verified fuzzy
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Source-reported events for the cited work

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Observation 2f201c8c-f826-4f3f-a992-f2a5afe63dab · outbound

This paper cites An empirical survey of data augmentation for limited data learning in NLP,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis An empirical survey of data augmentation for limited data learning in NLP,

Reference 10

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Source-reported events for the cited work

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Observation 4b70ffac-6a89-4b12-85cd-43683124c16a · outbound

This paper cites Building the Bridge: Topic Modeling for Comparative Research,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Building the Bridge: Topic Modeling for Comparative Research,

Reference 11

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Source-reported events for the cited work

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Observation 58df5a73-9e4a-4b19-9003-54b5067935ac · outbound

This paper cites Latent dirichlet allocation,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Latent dirichlet allocation,

Reference 12

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c8ed2da4-2584-4ff9-9522-057c349c5de9 · outbound

This paper cites Topic modeling for the social sciences,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Topic modeling for the social sciences,

Reference 13

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation b78db2d6-54c0-4aaf-b9c5-45afa382e57b · outbound

This paper cites FastText.zip: Compressing text classification models.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis FastText.zip: Compressing text classification models

Reference 14

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8252fe15-5140-4f27-8581-a6670bb11252 · outbound

This paper cites Glove: Global vectors for word representation,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Glove: Global vectors for word representation,

Reference 15

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 088ca9e4-5222-4f57-966c-25c3488a7d90 · outbound

This paper cites Text data augmentation and pre-trained Language Model for enhancing text classification of low-resource languages,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Text data augmentation and pre-trained Language Model for enhancing text classification of low-resource languages,

Reference 16

Resolution
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Source-reported events for the cited work

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Observation 5c445b69-a5ff-472c-ad3e-0527e5df4ad1 · outbound

This paper cites Data expansion using back translation and paraphrasing for hate speech detection,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Data expansion using back translation and paraphrasing for hate speech detection,

Reference 17

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7ec3effb-2a4d-493b-9ab5-d78adffcce4d · outbound

This paper cites EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks

Reference 18

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Source-reported events for the cited work

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Observation 46ad9e76-77b0-4645-a7c6-f965071b8d0b · outbound

This paper cites ChatGPT to Replace Crowdsourcing of Paraphrases for Intent Classification: Higher Diversity and Comparable Model Robustness,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis ChatGPT to Replace Crowdsourcing of Paraphrases for Intent Classification: Higher Diversity and Comparable Model Robustness,

Reference 19

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 55d66b7b-8e08-46ea-89fc-28e8394a6b02 · outbound

This paper cites Semantic Drift in Multilingual Representations,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Semantic Drift in Multilingual Representations,

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3599e7c1-2232-46d5-8c5e-f72da139b266 · outbound

This paper cites GPT-4o mini: advancing cost -efficient intelligence.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis GPT-4o mini: advancing cost -efficient intelligence

Reference 22

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 22aa39a8-2d24-47a2-a32f-98309f386c6f · outbound

This paper cites Claude 3.5 Sonnet.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Claude 3.5 Sonnet

Reference 23

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation df47457d-58e2-4940-b307-e39be03e336e · outbound

This paper cites Identifying Citizen-Related Issues from Social Media Using LLM -Based Data Augmentation,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Identifying Citizen-Related Issues from Social Media Using LLM -Based Data Augmentation,

Reference 24

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7f2ef618-90d0-492c-b61d-9a25b4b8b58b · outbound

This paper cites Exploring ChatGPT- Based Augmentation Strategies for Contrastive Aspect- Based Sentiment Analysis,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Exploring ChatGPT- Based Augmentation Strategies for Contrastive Aspect- Based Sentiment Analysis,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 010ebd2f-edfa-4245-b088-fe5b80ee6ac2 · outbound

This paper cites Evaluating large language models for health -related text classification tasks with public social media data,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Evaluating large language models for health -related text classification tasks with public social media data,

Reference 26

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 144d0ea5-9add-4f42-93e5-f51afd9745ba · outbound

This paper cites ChatGPT Label: Comparing the Quality of Human-Generated and LLM -Generated Annotations in Low -Resource Language NLP Tasks,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis ChatGPT Label: Comparing the Quality of Human-Generated and LLM -Generated Annotations in Low -Resource Language NLP Tasks,

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c2e561aa-47c9-4c10-8631-33ab108e6307 · outbound

This paper cites Leveraging Large Language Models for Code -Mixed Data Augmentation in Sentiment Analysis,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Leveraging Large Language Models for Code -Mixed Data Augmentation in Sentiment Analysis,

Reference 28

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:21.821973Z digest=sha256:3e8b4316d1fbd9a8a2ad44e65dfad432ebec7fd7f4ed3cd57de7fa2e10543649

Observation da150587-6bac-4528-8c46-63e7147b0145 · outbound

This paper cites an unresolved cited work.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Unresolved cited work

Reference 29

Resolution
unresolved
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 2ccc0a5d-178b-4881-ba6e-36395bdacc3e · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 30

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f4f7253a-9c32-4096-9f6a-e761323ed0c6 · outbound

This paper cites Auggpt: Leveraging chatgpt for text data augmentation.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Auggpt: Leveraging chatgpt for text data augmentation

Reference 31

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 076175c7-0c3f-4d4a-96fd-1c6853bdae45 · outbound

This paper cites LLM-powered Data Augmentation for Enhanced Cross-lingual Performance.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis LLM-powered Data Augmentation for Enhanced Cross-lingual Performance

Reference 32

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e7757ed1-b1e8-4b07-af58-9baf6f08c7c0 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Bleu: a method for automatic evaluation of machine translation,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:31.107524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 87d7fdc4-b423-41dd-9ba8-e33f61ba7d17 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Rouge: A package for automatic evaluation of summaries,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:30.934350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e2f41cdf-65c5-4222-af76-629810f80911 · outbound

This paper cites Synthetic and Natural Noise Both Break Neural Machine Translation.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Synthetic and Natural Noise Both Break Neural Machine Translation

Reference 35

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no resolver link, observed 2026-08-06T16:58:22.680940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:22.680940Z digest=sha256:c43e24c3bb49958d599e73c00b1cc65bee08e67b8559748303e49cbf3ea79d57

Observation 2557f974-8337-4a23-b7e0-12c99ff7e9cd · outbound

This paper cites Statistical Uncertainty in Word Embeddings: GloVe- V,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Statistical Uncertainty in Word Embeddings: GloVe- V,

Reference 36

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no resolver link, observed 2026-08-06T16:58:22.279906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:22.279906Z digest=sha256:51df6f6fbbcadb9f6a9bad64595e4d8041cc2e78023518839f45fa517998cfa7

Observation ffd5bd72-2ac2-46cc-aaf2-0a7683f567a0 · outbound

This paper cites SummIt: Iterative Text Summarization via ChatGPT.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis SummIt: Iterative Text Summarization via ChatGPT

Reference 37

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no resolver link, observed 2026-08-06T16:58:22.356870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:22.356870Z digest=sha256:ad7a70d1883acd605153f2ee43239c652d422284fd4461d0fddf6667dfe8e240

Observation 2f98a0ab-29a6-4f0e-8347-a7be6bfb2dd5 · outbound

This paper cites Prompt chaining or stepwise prompt? refinement in text summarization,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Prompt chaining or stepwise prompt? refinement in text summarization,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:30.762321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:22.501208Z digest=sha256:3f4d13a4e62111703eaaa8bd7a2117a2536239cf5139dcd82771863b310300de

Observation d88a17f0-eee4-49ad-acc6-aad0409e10be · outbound

This paper cites Text data augmentation for deep learning,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Text data augmentation for deep learning,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:30.585577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:22.580520Z digest=sha256:19384bf7050d59dd564e99cca7bc383d14bbc7e2087e81f3b4d4aa8c962c60ee

Observation d0c2d682-1940-4e89-a86b-466370836cb0 · outbound

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

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:29.967632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:23.127835Z digest=sha256:8978707f396a1a828cfd704ebd1d469190b9946a2c933ea915535dd60cf167a9

Observation f82e5c7c-d475-4dae-8f92-26bc7bad0804 · outbound

This paper cites WordNet: a lexical database for English,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis WordNet: a lexical database for English,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:30.396350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:22.769524Z digest=sha256:cb7c88a5e364f1e633926183b1a5cabe8658242514be71f1d46cef23ef842c23

Observation aade6d69-5d88-408d-a894-7f703970bd68 · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Efficient Estimation of Word Representations in Vector Space

Reference 42

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unresolved
no resolver link, observed 2026-08-06T16:58:22.860523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:22.860523Z digest=sha256:1e59be6f86c1f29c3e0cdbafa7ee21f10e392b902e93456727f6f843d28611ef

Observation db327b2c-cb25-49c8-adb7-0f770913a48e · outbound

This paper cites From word to sense embeddings: A survey on vector representations of meaning,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis From word to sense embeddings: A survey on vector representations of meaning,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:30.189788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:22.943141Z digest=sha256:e60371b1650d3af13c70d21dc950cf7fd4f0cf7cce638e13eb704418fb3118ea

Observation 2050ac50-cc1a-448a-a969-52d0b8931f8d · outbound

This paper cites Generating Natural Language Adversarial Examples.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Generating Natural Language Adversarial Examples

Reference 44

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unresolved
no resolver link, observed 2026-08-06T16:58:23.043556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:23.043556Z digest=sha256:ba5dfddd788922e0ed0a4749f8befb7c5d0179d25d3e159c4a3715bb3975934a

Observation 235ea5ac-fdfc-4adf-8c26-73358e500085 · outbound

This paper cites Training language models to follow instructions with human feedback.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Training language models to follow instructions with human feedback

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:29.349566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:23.603737Z digest=sha256:324e7ca04b88f45b97ed6373b0b08e0324822af275066f6878cdf72ede81814e

Observation e50dcecf-3e74-48ec-b456-141b2db97fbb · outbound

This paper cites Improving Neural Machine Translation Models with Monolingual Data.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Improving Neural Machine Translation Models with Monolingual Data

Reference 46

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unresolved
no resolver link, observed 2026-08-06T16:58:23.235611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:23.235611Z digest=sha256:d9b9d496c9999f722746061059731f11079c4da2d1fd0a6a8b2a0c317fe93b7a

Observation af3640aa-2689-46a6-bf68-4fd95bf1d748 · outbound

This paper cites Improving language understanding by generative pre-training,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Improving language understanding by generative pre-training,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:29.752405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:23.354252Z digest=sha256:8ed828ac6ef597f8a32619c3e6476a3549827cfdb6d6e8bfb223b081e4f2fa97

Observation f17ce832-6b64-4cb8-a38a-b2e296536ba0 · outbound

This paper cites Exploring the limits of transfer learning with a unified text- to-text transformer.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Exploring the limits of transfer learning with a unified text- to-text transformer

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-06T16:58:29.525938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:23.407247Z digest=sha256:00cf460a3ceb0bd71f483a08b8842a00fa2341cc855b52d454039071e362ce2f

Observation 9fe9188e-9b4e-408c-b219-fb6edac63a35 · outbound

This paper cites Paraphrase the following text:.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Paraphrase the following text:

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:34.094952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:20.185614Z digest=sha256:ae6a1103ea89afeebc835ca142cf4b5e546a8f5fbb018c5a479d4bb011633313

Observation 5a13a3a5-71f9-46f6-86bc-4acf18f5c5ed · outbound

This paper cites Promptagator: Few-shot Dense Retrieval From 8 Examples.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Promptagator: Few-shot Dense Retrieval From 8 Examples

Reference 50

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unresolved
no resolver link, observed 2026-08-06T16:58:23.526840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:23.526840Z digest=sha256:4a0c9ccee552cab882b948e51ac5f895b4188e44a8bfa43f23c1e2a20bcca70c

Observation d6910168-bf92-4339-8f68-1c26e06788c3 · outbound

This paper cites Data augmentation using llms: Data perspectives, learning paradigms and challenges.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Data augmentation using llms: Data perspectives, learning paradigms and challenges

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:29.159573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:23.718401Z digest=sha256:f861e3fd9a6d3238abb2a3b370e1baa7553838b6a29994e88e0c11fb7b9f7c0c

Observation aeee30b2-b896-4982-a987-f79117541545 · outbound

This paper cites Optimizing semantic coherence in topic models,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Optimizing semantic coherence in topic models,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:28.982467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:23.817781Z digest=sha256:9ab4b1919650d1ac9e7479a8c077f0c8f215e9c20a8b2cd5ce5ad529837bfd5a

Observation b6b94f72-776b-4fb3-b4a7-5ecaebbda0f4 · outbound

This paper cites BERTopic: Neural topic modeling with a class-based TF-IDF procedure.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis BERTopic: Neural topic modeling with a class-based TF-IDF procedure

Reference 53

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unresolved
no resolver link, observed 2026-08-06T16:58:23.901467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:23.901467Z digest=sha256:7b1d20c9bbe821e0c001bdd1ccc0aff621779db6cf2aacc83ec2ecc48ff01fc8

Observation a8c21c48-2074-43a1-84d6-3a59f2c872c6 · outbound

This paper cites Full- text or abstract? examining topic coherence scores using latent dirichlet allocation,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Full- text or abstract? examining topic coherence scores using latent dirichlet allocation,

Reference 54

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verified fuzzy
raw_fallback, observed 2026-08-06T16:58:28.803391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:24.057771Z digest=sha256:3722f985875f088beaae76c4ac3a462af0c1e6210202628f824fde9876531f13

Observation d16087ec-d66f-4d1f-83bf-7f82dbb1d6df · outbound

This paper cites A joint model of conversational discourse and latent topics on microblogs,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis A joint model of conversational discourse and latent topics on microblogs,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:28.623193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:24.208151Z digest=sha256:d23bf8216670478a6d1646249c02beb850a781b8d4370be3fb1a6b20f19c3cb6

Observation 432d5f91-8869-4875-ad4c-6daafbf932a3 · outbound

This paper cites Few-Shot Data Synthesis for Open Domain Multi-Hop Question Answering.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Few-Shot Data Synthesis for Open Domain Multi-Hop Question Answering

Reference 56

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unresolved
no resolver link, observed 2026-08-06T16:58:24.324238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:58:24.324238Z digest=sha256:bdf5c9969ae4fedd0d433c54f0f8dc58b246b72514b8e97bd9e453a801829c2d

Observation 5b7ea47e-050c-42ad-ab9d-1d7d32a7939c · outbound

This paper cites Minilm: Deep self-attention distillation for task -agnostic compression of pre -trained transformers,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Minilm: Deep self-attention distillation for task -agnostic compression of pre -trained transformers,

Reference 57

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verified fuzzy
raw_fallback, observed 2026-08-06T16:58:28.442059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:24.419556Z digest=sha256:73c778845a9638155f16d6c504043df812235fb20b3ef6658aec11602a967d49

Observation fd599765-a224-4385-896e-2824263486a6 · outbound

This paper cites Claude 3.5 Sonnet vs GPT-4o,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Claude 3.5 Sonnet vs GPT-4o,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:28.212448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:24.562786Z digest=sha256:4d1207006b1e0ed543db544b0523061ef966a6b590b56f793585b94267b22c4f

Observation b301b9aa-f57c-4ada-a590-ba9c40dedc26 · outbound

This paper cites GPT-4o Mini vs. Claude 3.5 Sonnet: A Detailed Comparison for Developers,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis GPT-4o Mini vs. Claude 3.5 Sonnet: A Detailed Comparison for Developers,

Reference 59

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verified fuzzy
raw_fallback, observed 2026-08-06T16:58:28.030209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:24.672413Z digest=sha256:67f826c57898364116d3564c68cc8930e82dc593e3b7d7928db44692bf399a5c

Observation 9e95c660-50e5-48b0-b6f4-f0ffa8a3b17b · outbound

This paper cites Claude 3.5 Sonnet vs. GPT -4o and GPT -4o mini — key differences,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Claude 3.5 Sonnet vs. GPT -4o and GPT -4o mini — key differences,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:27.847046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:24.765822Z digest=sha256:97c253cf07c5b0c2e4eae53217ced0dcea78f0fb75cbb935b66ee60a0cb37338

Observation 11d5061c-d163-42de-bf9b-e8025dc0bdf3 · outbound

This paper cites Cosine similarity and its applications in the domains of artificial intelligence,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Cosine similarity and its applications in the domains of artificial intelligence,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:27.659993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:24.887748Z digest=sha256:6728866707313f0909bf4c5745ccb156f24ae15f1fbed7ef4ec587888b87d96b

Observation 82f3154a-cea6-4f58-93db-d69c363d8cb8 · outbound

This paper cites A comprehensive survey of text classification techniques and their research applications: Observational and experimental insights,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis A comprehensive survey of text classification techniques and their research applications: Observational and experimental insights,

Reference 62

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T16:58:26.193176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:25.047654Z digest=sha256:219a304ab28002c9a0a40dd908cbaf4a6ca81084513c1b2655ab1ca583e737f6

Observation eec97009-5d9d-426a-95ca-ad8fd8c3c554 · outbound

This paper cites Scaling up all pairs similarity search,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Scaling up all pairs similarity search,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:27.481964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:25.199771Z digest=sha256:0e94c1eb4d94270836ae9519b6cc2e166259dbb74671dd641047fead4c9184f3

Observation 224a9d62-2032-4520-adb1-f9b29dc1ab29 · outbound

This paper cites Probabilistic topic models,.

Iterative Augmentation with Summarization Refinement (IASR) Evaluation for Unstructured Survey data Modeling and Analysis Probabilistic topic models,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:58:27.306466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:58:25.312915Z digest=sha256:1274f9993c5f151f0463f036b8d0be506a8b513ffdc3d113695f147934a4016c

Pith citing papers

No inbound Pith citation observations are available.