Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-10T18:14:50.245621Z
Paper Citation Record · LEDGER
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection
As of 31 July 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2604.08381.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-07-31T06:34:12.847434+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
59 of 59 outbound references displayed
- verified exact0
- verified fuzzy59
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 4efe42db-4dcf-44cc-9bf4-9922fd1ae9e3 · outbound
This paper cites Sarcasm as contrast between a positive sentiment and negative situation.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Sarcasm as contrast between a positive sentiment and negative situation
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.331669Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 288cac97-0cc3-42dc-bd06-3fef94cc2f87 · outbound
This paper cites From humor recognition to irony detection: The figurative language of social media.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection From humor recognition to irony detection: The figurative language of social media
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.325501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 4de3c646-d968-4fdd-88e7-0a4270479df8 · outbound
This paper cites Irony detection in twitter: The role of affective content.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Irony detection in twitter: The role of affective content
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.334327Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation dcb8fd92-febf-4e5f-a2b8-06c271648d1b · outbound
This paper cites Detecting ironic intent in creative comparisons.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Detecting ironic intent in creative comparisons
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.340229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 63bb0630-cbf7-48bd-bae8-765119b352d2 · outbound
This paper cites An emoticon- based novel sarcasm pattern detection strategy to identify sarcasm in microblogging social networks.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection An emoticon- based novel sarcasm pattern detection strategy to identify sarcasm in microblogging social networks
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.317150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 8c0a220a-6b2d-45c3-8a72-52194636ec90 · outbound
This paper cites Cascade: Contextual sarcasm detection in online discussion forums.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Cascade: Contextual sarcasm detection in online discussion forums
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.352925Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 83545caa-63a6-4d8b-8b70-6313252685b4 · outbound
This paper cites Contextualized sarcasm detection on twit- ter.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Contextualized sarcasm detection on twit- ter
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.337245Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation f1f886b8-6724-495d-acbe-79e8d0332d3a · outbound
This paper cites Harnessing context in- congruity for sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Harnessing context in- congruity for sarcasm detection
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.349684Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 8c1b14ad-95ef-4230-a223-01aff1e4555f · outbound
This paper cites The perfect solution for detecting sarcasm in tweets# not.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection The perfect solution for detecting sarcasm in tweets# not
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.320007Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 42d186e2-917f-43a8-8f36-f7134924d45b · outbound
This paper cites Sincere: A hybrid framework with graph-based compact textual models using emotion classification and sentiment analysis for twitter sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Sincere: A hybrid framework with graph-based compact textual models using emotion classification and sentiment analysis for twitter sarcasm detection
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.310585Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 7f330584-30bd-447a-832d-2dabf631b13c · outbound
This paper cites Enhancement of a multi-dialectal sentiment analysis system by the detection of the implied sarcastic features.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Enhancement of a multi-dialectal sentiment analysis system by the detection of the implied sarcastic features
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.314239Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation fac8959e-9b24-42f7-aab1-e0d937f10ad7 · outbound
This paper cites Sarcasm analysis using conversation context.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Sarcasm analysis using conversation context
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.322729Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation fb184f79-0f98-447f-8aff-66d3972ef43a · outbound
This paper cites Deepmsd: Advancing multimodal sar- casm detection through knowledge-augmented graph reasoning.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Deepmsd: Advancing multimodal sar- casm detection through knowledge-augmented graph reasoning
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.411733Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation c5210f1d-10f7-4c40-bc9d-d583b6cfe25a · outbound
This paper cites Mimicking the brain’s cognition of sarcasm from multidisciplines for twitter sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Mimicking the brain’s cognition of sarcasm from multidisciplines for twitter sarcasm detection
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.438752Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation e7587814-a91a-4420-be22-a208e8d32fcf · outbound
This paper cites Multi-modal sarcasm detection on social media via multi-granularity information fusion.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Multi-modal sarcasm detection on social media via multi-granularity information fusion
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.456592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 50f1e64a-823a-473c-962d-ff95a9315a31 · outbound
This paper cites Multi-modal sarcasm detection via knowledge-aware focused graph convolutional networks.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Multi-modal sarcasm detection via knowledge-aware focused graph convolutional networks
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.444725Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 3883ad1f-da31-480d-b7e8-001ed58c2e29 · outbound
This paper cites Fine-grained semantic disentanglement network for multimodal sarcasm analysis.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Fine-grained semantic disentanglement network for multimodal sarcasm analysis
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.465965Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 3c3ef997-2100-472d-9f7d-0f6a4ca5964a · outbound
This paper cites S3 agent: Unlocking the power of vllm for zero-shot multi-modal sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection S3 agent: Unlocking the power of vllm for zero-shot multi-modal sarcasm detection
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.484054Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation bf9d01bc-7393-4e36-9137-2b19ac5618ae · outbound
This paper cites Self-adaptive representation learning model for multi-modal sentiment and sarcasm joint analysis.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Self-adaptive representation learning model for multi-modal sentiment and sarcasm joint analysis
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.393418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation e62cb886-3b0b-4911-8790-6cc4d34340cb · outbound
This paper cites A novel retrospective-reading model for detecting chinese sarcasm comments of online social network.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection A novel retrospective-reading model for detecting chinese sarcasm comments of online social network
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.441676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation c9e3cbee-edfa-4a90-b8a8-455da11aa682 · outbound
This paper cites A quantum probability driven frame- work for joint multi-modal sarcasm, sentiment and emotion analysis.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection A quantum probability driven frame- work for joint multi-modal sarcasm, sentiment and emotion analysis
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.433198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation db8a468e-3cb0-4eef-9aaf-7d26113f5e74 · outbound
This paper cites Elevating knowledge-enhanced entity and relationship understanding for sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Elevating knowledge-enhanced entity and relationship understanding for sarcasm detection
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.362335Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation dc158bed-452f-491f-9c04-d67d20afcbaa · outbound
This paper cites Clues for detecting irony in user-generated contents: Oh...!! it’s so easy ;-).
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Clues for detecting irony in user-generated contents: Oh...!! it’s so easy ;-)
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.462911Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 63d108ee-d8f0-48fc-b84b-97f3fd9f6cae · outbound
This paper cites Who cares about sarcastic tweets? investigating the impact of sarcasm on sentiment analysis.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Who cares about sarcastic tweets? investigating the impact of sarcasm on sentiment analysis
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.435923Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation a165c444-14d6-40f8-a8c7-21cae2d94f2f · outbound
This paper cites Semi-supervised recognition of sarcastic sentences in twitter and amazon.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Semi-supervised recognition of sarcastic sentences in twitter and amazon
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.473884Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 4e637ce5-e628-464c-9cea-a8163470a198 · outbound
This paper cites A deeper look into sarcastic tweets using deep convolutional neural networks.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection A deeper look into sarcastic tweets using deep convolutional neural networks
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.448198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation d168c14d-2724-47b0-9507-7aac73c0899e · outbound
This paper cites Fracking sarcasm using neural network.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Fracking sarcasm using neural network
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.423705Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 8de871c9-d7cd-421f-bb4b-1539d9161586 · outbound
This paper cites Reasoning with sarcasm by reading in-between.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Reasoning with sarcasm by reading in-between
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.402649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 023eb301-6ec7-4f49-8ee6-081cfbd4cb59 · outbound
This paper cites Sarcasm detection using deep learning and ensemble learning.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Sarcasm detection using deep learning and ensemble learning
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.430130Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation caa33d31-0cfb-4667-aaaf-20582149164b · outbound
This paper cites Affective representations for sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Affective representations for sarcasm detection
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.418074Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 4f65d323-f413-41f5-81de-d6cd3f65d2bb · outbound
This paper cites Humans require context to infer ironic intent (so computers probably do, too).
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Humans require context to infer ironic intent (so computers probably do, too)
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.420837Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 6d0ce3d9-537a-4cc7-ae55-6f116eff37eb · outbound
This paper cites Sparse, contextually informed models for irony detection: Exploiting user communities, entities and sentiment.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Sparse, contextually informed models for irony detection: Exploiting user communities, entities and sentiment
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.480694Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 20fc5169-6b3a-4858-8ece-5b765d170f7d · outbound
This paper cites Affective and contextual em- bedding for sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Affective and contextual em- bedding for sarcasm detection
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.426828Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation ed9d9be8-00ee-4701-b0ad-062f65546cb3 · outbound
This paper cites A novel hierarchical bert architecture for sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection A novel hierarchical bert architecture for sarcasm detection
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.459680Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation be80e468-098d-4267-9087-cc50df3a2d45 · outbound
This paper cites A transformer- based approach to irony and sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection A transformer- based approach to irony and sarcasm detection
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.388458Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 1cbcbb4f-d30f-48d8-b5e6-2d4d875edff0 · outbound
This paper cites Enhancing semantic awareness by sentimental constraint with automatic outlier masking for multimodal sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Enhancing semantic awareness by sentimental constraint with automatic outlier masking for multimodal sarcasm detection
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.470701Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 10b9fa49-188c-4d03-a83b-a7336c091b9d · outbound
This paper cites Hybrid quantum-classical neural network for multimodal multitask sarcasm, emotion, and sentiment analysis.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Hybrid quantum-classical neural network for multimodal multitask sarcasm, emotion, and sentiment analysis
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.405983Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 078e96c5-3db2-4961-8ab9-577cf269f671 · outbound
This paper cites Fusion and discrimination: A multimodal graph contrastive learning framework for multimodal sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Fusion and discrimination: A multimodal graph contrastive learning framework for multimodal sarcasm detection
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.384087Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 0791235d-79fa-4378-9f7e-e1325e9d0f98 · outbound
This paper cites Chinese irony corpus construction and ironic structure analysis.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Chinese irony corpus construction and ironic structure analysis
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.415169Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 08bc0dfd-1a5e-4239-a24a-6f4865cfc62a · outbound
This paper cites Sarcasm detection in chinese using a crowdsourced corpus.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Sarcasm detection in chinese using a crowdsourced corpus
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.476956Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 06b0094e-5de4-4e37-8133-66b3f9d0f629 · outbound
This paper cites Ciron: a new benchmark dataset for chinese irony detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Ciron: a new benchmark dataset for chinese irony detection
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.359248Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation de680815-daef-44ff-8c75-8277ebf7398c · outbound
This paper cites The design and construction of a chinese sarcasm dataset.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection The design and construction of a chinese sarcasm dataset
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.378583Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation b2cde2a4-e1dd-463a-bef6-ca857410dc7f · outbound
This paper cites Attention is all you need.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Attention is all you need
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.408829Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 5c820b37-e9ae-43ca-84ec-c14ea404c583 · outbound
This paper cites Improved training of wasserstein gans.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Improved training of wasserstein gans
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.398551Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation f50a80d6-0028-454a-af6b-a2a09bddd8aa · outbound
This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Bert: Pre-training of deep bidirectional transformers for language understanding
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.373946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation d9284970-248c-4785-98f0-d22f9e9629f9 · outbound
This paper cites Convolutional neural networks for sentence classification.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Convolutional neural networks for sentence classification
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.369494Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation fd862da4-f0a1-4262-a229-04bdd13421c6 · outbound
This paper cites Generating behavior features for cold- start spam review detection with adversarial learning.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Generating behavior features for cold- start spam review detection with adversarial learning
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.365826Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 958000b4-0bf6-489a-ac06-989c9cacc204 · outbound
This paper cites Sarcasm detection in social media based on imbalanced classification.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Sarcasm detection in social media based on imbalanced classification
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.451649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation c950ecfb-ad7d-47cb-9562-44f913fa0aac · outbound
This paper cites Sememe knowledge and auxiliary information enhanced approach for sarcasm detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Sememe knowledge and auxiliary information enhanced approach for sarcasm detection
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.297324Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation fd0b1472-1ee2-4b39-b3f9-619f0296344a · outbound
This paper cites Sarcasm detection on twitter: A behavioral modeling approach.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Sarcasm detection on twitter: A behavioral modeling approach
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.307217Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation ce9fb5c5-f6fd-4762-af49-f57e68f2f549 · outbound
This paper cites An improved random forest classifier for multi-class classification.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection An improved random forest classifier for multi-class classification
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.287521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 92ff4228-f763-4511-b938-d99b1c62ff07 · outbound
This paper cites Explaining the success of adaboost and random forests as interpolating classifiers.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Explaining the success of adaboost and random forests as interpolating classifiers
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.290960Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 3146f0be-b216-48d7-ba2c-28f0ec6888ef · outbound
This paper cites Atalaya at semeval 2019 task 5: Robust embeddings for tweet classification.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Atalaya at semeval 2019 task 5: Robust embeddings for tweet classification
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.294111Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 55365bff-3746-4578-9773-45a1535f3a6b · outbound
This paper cites A hybrid transformer based model for sarcasm detection from news headlines.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection A hybrid transformer based model for sarcasm detection from news headlines
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.304248Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 9e656f23-35a9-4f01-9b0e-1c0739aa8392 · outbound
This paper cites Addressing unintended bias in toxicity detection: An lstm and attention-based approach.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Addressing unintended bias in toxicity detection: An lstm and attention-based approach
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.301224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 0a2838e9-e487-42e3-a4a8-395e3fe0b6aa · outbound
This paper cites A deep learning framework for assamese toxic comment detection: Leveraging lstm and bilstm models with attention mechanism.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection A deep learning framework for assamese toxic comment detection: Leveraging lstm and bilstm models with attention mechanism
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.328732Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 171e5ece-1b2c-4f27-bf0d-f794088feb73 · outbound
This paper cites Revisiting pre-trained models for chinese natural language processing.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Revisiting pre-trained models for chinese natural language processing
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.343168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation cfe5a2c9-18d6-43ec-9029-5c70d5fa0e12 · outbound
This paper cites Detecting offensive speech in conversational code-mixed dialogue on social media: A contextual dataset and benchmark experiments.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection Detecting offensive speech in conversational code-mixed dialogue on social media: A contextual dataset and benchmark experiments
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.346154Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Observation 296573ec-0fdf-4b64-87dc-7e14b5108396 · outbound
This paper cites A simple and interactive transformer for fine-grained emotion detection.
A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection A simple and interactive transformer for fine-grained emotion detection
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T06:19:11.356120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-31T06:34:12.847434+00:00.
Pith citing papers
No inbound Pith citation observations are available.