Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:09:03.573177Z
Paper Citation Record · LEDGER
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection
As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2505.16258.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-21T02:35:37.724212Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T02:39:25.964686Z
Reference resolution
41 of 41 outbound references displayed
- verified exact0
- verified fuzzy35
- unresolved6
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 3a5a2a63-8995-438c-95f1-2b02bd946207 · outbound
This paper cites Cross-modal coherence modeling for caption generation.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Cross-modal coherence modeling for caption generation
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:11.912573Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 92ad9ca2-34a6-4614-bb7f-e922db442860 · outbound
This paper cites Cross-modal coherence for text-to-image retrieval.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Cross-modal coherence for text-to-image retrieval
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:11.595677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation af115155-6fa4-4b0e-a645-682fa3ef30d0 · outbound
This paper cites ANNA : Abstractive text-to-image synthesis with filtered news captions.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection ANNA : Abstractive text-to-image synthesis with filtered news captions
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:11.308545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5582b82c-bb1a-4c1b-bb7c-4b86a42ba27d · outbound
This paper cites CORDIAL : Can multimodal large language models effectively understand coherence relationships? arXiv [cs.CL], February 2025 a.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection CORDIAL : Can multimodal large language models effectively understand coherence relationships? arXiv [cs.CL], February 2025 a
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:11.131997Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a497f7ef-1c21-4e44-999f-95400ca4ec89 · outbound
This paper cites RONA : Pragmatically diverse image captioning with coherence relations.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection RONA : Pragmatically diverse image captioning with coherence relations
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:10.995349Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d62e1474-574a-4282-841e-8363eb0696bb · outbound
This paper cites Multi-modal sarcasm detection in twitter with hierarchical fusion model.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Multi-modal sarcasm detection in twitter with hierarchical fusion model
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:10.702654Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 034d8466-84f5-47cd-bd4e-d80baa525ef9 · outbound
This paper cites Sarcasm, pretense, and the semantics/pragmatics distinction.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Sarcasm, pretense, and the semantics/pragmatics distinction
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:10.385442Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a498d1c5-5b7d-4d7a-aecd-3039b711a837 · outbound
This paper cites Towards multimodal sarcasm detection (an \_obviously\_ perfect paper).
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Towards multimodal sarcasm detection (an \_obviously\_ perfect paper)
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:10.117748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 846bf5c1-930c-4395-825f-2b08d79246cb · outbound
This paper cites Sarcasm detection on facebook: a supervised learning approach.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Sarcasm detection on facebook: a supervised learning approach
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:09.996201Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 335c94a2-26e1-4fbc-8a72-43dd73443eb1 · outbound
This paper cites Why is discourse coherent?, volume 176.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Why is discourse coherent?, volume 176
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:09.791324Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation acf94d64-6cbc-447f-8239-a5112f724760 · outbound
This paper cites Exploring and evaluating multimodal knowledge reasoning consistency of multimodal large language models.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Exploring and evaluating multimodal knowledge reasoning consistency of multimodal large language models
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:09.539237Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 60dfa831-830c-4f7a-b816-a65640528177 · outbound
This paper cites Debiasing multimodal sarcasm detection with contrastive learning.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Debiasing multimodal sarcasm detection with contrastive learning
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:09.336114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e4aa7d10-8d2e-4c2c-a4ae-ca2788028823 · outbound
This paper cites When did you become so smart, oh wise one?! sarcasm explanation in multi-modal multi-party dialogues.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection When did you become so smart, oh wise one?! sarcasm explanation in multi-modal multi-party dialogues
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:09.211668Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 01723fcc-7b49-4e20-abaa-3a014ed13bf8 · outbound
This paper cites Pragmatic metacognitive prompting improves LLM performance on sarcasm detection.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Pragmatic metacognitive prompting improves LLM performance on sarcasm detection
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:09.092117Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8be67962-d6ae-4c23-aade-2f552bb035cb · outbound
This paper cites Multi-modal sarcasm detection via cross-modal graph convolutional network.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Multi-modal sarcasm detection via cross-modal graph convolutional network
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:08.968698Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 736c02cb-2a41-4628-ad7f-46a583853cb9 · outbound
This paper cites FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimization
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:09:00.626417Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57b4e2be-6d70-433d-abea-629a0468369d · outbound
This paper cites Diverse image captioning with context-object split latent spaces.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Diverse image captioning with context-object split latent spaces
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:08.700333Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation eb5ed7e4-9c4f-42f9-9d07-f772123e000e · outbound
This paper cites GPT - 4o system card.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection GPT - 4o system card
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:08.472232Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6f3ab39c-c808-4196-93b9-90d1ee5de723 · outbound
This paper cites Modeling intra and inter-modality incongruity for multi-modal sarcasm detection.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Modeling intra and inter-modality incongruity for multi-modal sarcasm detection
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:08.246794Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation fbc23488-ac9e-4528-88c5-d132eeadec69 · outbound
This paper cites Opinion mining and sentiment analysis.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Opinion mining and sentiment analysis
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:08.041244Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c2467411-8bbe-4293-907d-a1aae6b87cb7 · outbound
This paper cites MMSD2 .0: Towards a reliable multi-modal sarcasm detection system.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection MMSD2 .0: Towards a reliable multi-modal sarcasm detection system
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:07.754230Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4b0e6d73-55d7-47ce-813f-aceed553dd52 · outbound
This paper cites Learning Transferable Visual Models From Natural Language Supervision.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Learning Transferable Visual Models From Natural Language Supervision
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:09:01.176218Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d48ea64f-e027-4d2a-8941-b16324952b1d · outbound
This paper cites A multimodal corpus for emotion recognition in sarcasm.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection A multimodal corpus for emotion recognition in sarcasm
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:07.461196Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d048eafa-f5ad-473c-b05f-fbd406c800b2 · outbound
This paper cites Detecting sarcasm in multimodal social platforms.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Detecting sarcasm in multimodal social platforms
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:07.245285Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9965d1af-db77-4e9e-bd25-b951382f8497 · outbound
This paper cites Using the image-text relationship to improve multimodal disaster tweet classification.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Using the image-text relationship to improve multimodal disaster tweet classification
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:07.052160Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8bbe2545-26f9-468e-8f22-e582f221e25a · outbound
This paper cites Leveraging generative large language models with visual instruction and demonstration retrieval for multimodal sarcasm detection.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Leveraging generative large language models with visual instruction and demonstration retrieval for multimodal sarcasm detection
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:06.777758Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5486d4a8-58c3-4d8f-acf5-a971919e912b · outbound
This paper cites Eyes wide shut? exploring the visual shortcomings of MultiModal LLMs.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Eyes wide shut? exploring the visual shortcomings of MultiModal LLMs
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:06.483886Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ecebb3c8-a2a0-43e1-850e-b2575789eb76 · outbound
This paper cites Categorizing and inferring the relationship between the text and image of twitter posts.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Categorizing and inferring the relationship between the text and image of twitter posts
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:06.226514Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0a60ec2e-aaf3-4089-ad76-0cf579359e77 · outbound
This paper cites S ^ 3 agent: Unlocking the power of VLLM for zero-shot multi-modal sarcasm detection.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection S ^ 3 agent: Unlocking the power of VLLM for zero-shot multi-modal sarcasm detection
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:05.967174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ba5f6957-40aa-40fa-bfcd-2159a2ee2758 · outbound
This paper cites Metacognitive prompting improves understanding in large language models.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Metacognitive prompting improves understanding in large language models
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:05.740984Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0013f334-a5ef-4c4a-a0ef-4a1f4fe1e074 · outbound
This paper cites Chain-of-thought prompting elicits reasoning in large language models.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Chain-of-thought prompting elicits reasoning in large language models
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:05.458869Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 46d4efbc-1bb8-48a6-b959-210d76ac6cc5 · outbound
This paper cites Modeling incongruity between modalities for multimodal sarcasm detection.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Modeling incongruity between modalities for multimodal sarcasm detection
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:05.237335Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation efee240a-752f-483a-9f9a-125f4d888fd4 · outbound
This paper cites Understanding social media cross-modality discourse in linguistic space.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Understanding social media cross-modality discourse in linguistic space
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:04.978188Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 755429ae-16d4-4819-82fb-656387af40ba · outbound
This paper cites Is sarcasm detection a step-by-step reasoning process in large language models? Proc.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Is sarcasm detection a step-by-step reasoning process in large language models? Proc
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:04.724576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0141e4b4-440b-4d7c-83ae-ea06e19cc730 · outbound
This paper cites RATT : A thought structure for coherent and correct LLM reasoning.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection RATT : A thought structure for coherent and correct LLM reasoning
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:04.417109Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4113ed44-2dff-46ef-b007-1b446fa2cafe · outbound
This paper cites Commander- GPT : Fully unleashing the sarcasm detection capability of multi-modal large language models.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Commander- GPT : Fully unleashing the sarcasm detection capability of multi-modal large language models
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:04.134418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0c233e9f-9885-49ce-a830-c0f949ffe2d6 · outbound
This paper cites InternVL3 : Exploring advanced training and test-time recipes for open-source multimodal models.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection InternVL3 : Exploring advanced training and test-time recipes for open-source multimodal models
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T15:09:03.878041Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 02254966-51c1-464e-a576-ccbfffdc2edc · outbound
This paper cites write newline.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection write newline
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:09:03.245111Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8d544896-5f9a-42b0-8a7e-292d5279738f · outbound
This paper cites @esa (Ref.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection @esa (Ref
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:09:03.316965Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea89cdbd-3623-4e22-9338-e29fccfc3664 · outbound
This paper cites an unresolved cited work.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Unresolved cited work
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:09:03.443313Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6d923547-fa45-45ef-b61c-8fad7987f91e · outbound
This paper cites an unresolved cited work.
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection Unresolved cited work
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:09:03.573177Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation 6a75e03b-77c2-45ba-a649-21da91705d14 · inbound
ProCrit: Self-Elicited Multi-Perspective Reasoning with Critic-Guided Revision for Multimodal Sarcasm Detection cites this paper.
ProCrit: Self-Elicited Multi-Perspective Reasoning with Critic-Guided Revision for Multimodal Sarcasm Detection IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm Detection
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T02:39:25.967227Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.