Paper Citation Record · LEDGER

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis

As of 10 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2506.07148.

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

pith.paper-citation-record.v1
2506.07148 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:46:24.438580Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

34 of 34 outbound references displayed

verified exact1
verified fuzzy30
unresolved3
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 93ced546-f187-4001-8428-a187de92fb04 · outbound

This paper cites Cognitive- inspired deep learning models for aspect-based sentiment analysis: A retrospective overview and bibliometric analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Cognitive- inspired deep learning models for aspect-based sentiment analysis: A retrospective overview and bibliometric analysis,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T05:46:24.341091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63cb0180-0eb1-45a7-a7b2-a1fdc8da217b · outbound

This paper cites Exploring cognitive and aesthetic causality for multimodal aspect-based sentiment analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Exploring cognitive and aesthetic causality for multimodal aspect-based sentiment analysis,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.760888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5b6611d1-611e-4dff-898b-b05eb4d9eed4 · outbound

This paper cites MER 2025: When Affective Computing Meets Large Language Models.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis MER 2025: When Affective Computing Meets Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T05:46:24.348755Z

Source-reported events for the cited work

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Observation 009e7698-4fcb-4948-9117-3c5894045d0b · outbound

This paper cites Semantically consistent data aug- mentation for neural machine translation via conditional masked language model,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Semantically consistent data aug- mentation for neural machine translation via conditional masked language model,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.751698Z

Source-reported events for the cited work

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Observation 331b6866-acd3-4baa-a78d-b3e5835710fe · outbound

This paper cites Semantics-preserved data aug- mentation for aspect-based sentiment analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Semantics-preserved data aug- mentation for aspect-based sentiment analysis,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.742008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 184036af-f24d-4b8d-8ac9-aa9f497344dd · outbound

This paper cites Refining and synthesis: A simple yet effective data augmentation frame- work for cross-domain aspect-based sentiment analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Refining and synthesis: A simple yet effective data augmentation frame- work for cross-domain aspect-based sentiment analysis,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.731816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5b61b645-8123-43d2-860c-adf7d8504504 · outbound

This paper cites DS$^2$-ABSA: Dual-Stream Data Synthesis with Label Refinement for Few-Shot Aspect-Based Sentiment Analysis.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis DS$^2$-ABSA: Dual-Stream Data Synthesis with Label Refinement for Few-Shot Aspect-Based Sentiment Analysis

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:46:24.482877Z

Source-reported events for the cited work

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Observation 0a89f7a6-e4fc-4da0-97ec-2d97859a3b69 · outbound

This paper cites Beta distribution guided aspect-aware graph for aspect category sentiment analysis with affective knowledge,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Beta distribution guided aspect-aware graph for aspect category sentiment analysis with affective knowledge,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.722218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7edeb28a-917c-49af-9abe-158577e8359a · outbound

This paper cites Multi-instance multi-label learning networks for aspect-category sentiment analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Multi-instance multi-label learning networks for aspect-category sentiment analysis,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.712833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2277c0f2-477d-4903-af78-55f4cb1813e6 · outbound

This paper cites Aspect category sentiment analysis based on prompt-based learning with attention mechanism,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Aspect category sentiment analysis based on prompt-based learning with attention mechanism,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.704237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f03b0786-272b-49e8-a709-52dbf15bef41 · outbound

This paper cites Solving aspect category sentiment analysis as a text generation task,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Solving aspect category sentiment analysis as a text generation task,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.695424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 27fe605e-1f6e-4440-9c39-5d213158640d · outbound

This paper cites Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehen- sion,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehen- sion,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.687017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d68d294d-52c1-438b-ab81-077af3e41077 · outbound

This paper cites A comprehensive framework for aspect- category sentiment analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis A comprehensive framework for aspect- category sentiment analysis,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.678351Z

Source-reported events for the cited work

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Observation c6beb5d5-9185-4772-9783-bafaec29c3ab · outbound

This paper cites Scaling instruction-finetuned language models,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Scaling instruction-finetuned language models,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.669945Z

Source-reported events for the cited work

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Observation c9247c59-1492-4e98-bad0-126610dd601c · outbound

This paper cites Lego- absa: A prompt-based task assemblable unified generative framework for multi-task aspect-based sentiment analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Lego- absa: A prompt-based task assemblable unified generative framework for multi-task aspect-based sentiment analysis,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.661909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 27be9ecc-b7ff-4d70-826b-8654f5b91983 · outbound

This paper cites Is compound aspect-based sentiment analysis addressed by llms?.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Is compound aspect-based sentiment analysis addressed by llms?

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.652838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c5e3c677-0c58-42d1-82f8-ac46e4ad6127 · outbound

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

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.644576Z

Source-reported events for the cited work

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Observation 4ed2e7b0-d186-4e25-b24c-42f71e6d9560 · outbound

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

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Language models are few-shot learners,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.636015Z

Source-reported events for the cited work

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Observation 58fde9fb-d196-4038-9567-aad27094c3dc · outbound

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

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Chain-of-thought prompting elicits reasoning in large language models,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.627550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1d0e7fb3-f36c-4cfb-8318-b6ad1218cddf · outbound

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

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Self-consistency improves chain of thought reasoning in language models,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.619020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 01c5c5dd-e928-4893-8701-35b975551290 · outbound

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

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Rvisa: Reasoning and verification for implicit sentiment analysis,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.610689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 46f34a78-e681-403b-b2f8-eae59a9d0fa0 · outbound

This paper cites Text Data Augmentation for Large Language Models: A Comprehensive Survey of Methods, Challenges, and Opportunities.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Text Data Augmentation for Large Language Models: A Comprehensive Survey of Methods, Challenges, and Opportunities

Reference 22

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Source-reported events for the cited work

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Observation 3cc28ebc-5ba6-489b-8ad7-1f1c29e202e9 · outbound

This paper cites Sentence-bert: Sentence embeddings using siamese bert-networks,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Sentence-bert: Sentence embeddings using siamese bert-networks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.602294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation eaae83a4-2447-4688-92d4-6b11b1eef11f · outbound

This paper cites Semeval-2015 task 12: Aspect based sentiment analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Semeval-2015 task 12: Aspect based sentiment analysis,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.593555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1eb83ce4-5cc3-4c03-b882-3fe62ba3096c · outbound

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

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Semeval-2016 task 5: Aspect based sentiment analysis,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.585078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5ad63c60-df78-4f28-8169-1c41b05b32f0 · outbound

This paper cites Enhanced coherence-aware network with hierarchical disentanglement for aspect-category sentiment analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Enhanced coherence-aware network with hierarchical disentanglement for aspect-category sentiment analysis,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.576575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5469a6e4-d9cc-4791-830c-45bff56d7d1c · outbound

This paper cites Context-aware embedding for targeted aspect-based sentiment analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Context-aware embedding for targeted aspect-based sentiment analysis,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.567869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e5ce3f75-e457-43e9-88d8-7d2b315d8be2 · outbound

This paper cites Sentence constituent-aware aspect-category sentiment analysis with graph attention networks,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Sentence constituent-aware aspect-category sentiment analysis with graph attention networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.558840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 095d1a99-4234-4fd3-8e05-49f33403964f · outbound

This paper cites Locate and combine: A two- stage framework for aspect-category sentiment analysis,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Locate and combine: A two- stage framework for aspect-category sentiment analysis,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.549594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 54410467-8a33-49f0-9d01-e00ff080f73b · outbound

This paper cites Edu-capsule: Aspect-based sentiment analysis at clause level,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Edu-capsule: Aspect-based sentiment analysis at clause level,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.539910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2da3ccb1-a973-4954-9c5b-b944173cceb5 · outbound

This paper cites Aspect-category based sentiment analysis with hierarchical graph convolutional network,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Aspect-category based sentiment analysis with hierarchical graph convolutional network,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.530387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2f6f098b-25e4-41cb-924d-2e1f8b8691f0 · outbound

This paper cites Mvp: Multi-view prompting improves aspect sentiment tuple prediction,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Mvp: Multi-view prompting improves aspect sentiment tuple prediction,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.521096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c2c1184b-1d41-4abe-87b8-f146c09d50a1 · outbound

This paper cites Joint aspect and polarity classification for aspect-based sentiment analysis with end-to-end neural networks,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Joint aspect and polarity classification for aspect-based sentiment analysis with end-to-end neural networks,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.511942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b2cc4e4f-43c5-4018-bc5c-5d5dc2d4c08c · outbound

This paper cites Dual-attention based joint aspect sentiment clas- sification model,.

Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis Dual-attention based joint aspect sentiment clas- sification model,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:46:24.502525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

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