Paper Citation Record · LEDGER

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction

As of 22 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2508.13826.

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

pith.paper-citation-record.v1
2508.13826 v4

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T18:56:01.581932Z

measured 28 of 28 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

28 of 28 outbound references displayed

verified exact1
verified fuzzy25
unresolved2
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 346050ee-0be5-4451-8d1e-e18a85b17da1 · outbound

This paper cites When it’s all piling up: investigating error propagation in an NLP pipeline.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction When it’s all piling up: investigating error propagation in an NLP pipeline

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:08.852057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation de12e0e3-40cf-44f3-b29a-3aa92f335e72 · outbound

This paper cites Evaluat- ing large language models trained on code,.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Evaluat- ing large language models trained on code,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:08.032718Z

Source-reported events for the cited work

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Observation d9944ec9-bbb0-4f9c-be1f-277179c3e77b · outbound

This paper cites UProp: Investigating the uncertainty propagation of LLMs in multi-step decision-making,.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction UProp: Investigating the uncertainty propagation of LLMs in multi-step decision-making,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:07.169414Z

Source-reported events for the cited work

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Observation 6981c8ed-1377-4028-8b04-068b8572bb4b · outbound

This paper cites Pal: Program-aided language models,.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Pal: Program-aided language models,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:06.587726Z

Source-reported events for the cited work

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Observation 753affb8-51e0-4b42-a0fe-73dc9b3acbba · outbound

This paper cites LLMGuard: Guarding Against Unsafe LLM Behavior.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction LLMGuard: Guarding Against Unsafe LLM Behavior

Reference 10

Resolution: verified exact; local_arxiv, observed 2026-08-05T18:56:01.900325Z

Source-reported events for the cited work

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Observation 6db87725-31b9-4537-84b3-96ebde03f3b4 · outbound

This paper cites Lam, Ranjay Krishna, et al.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Lam, Ranjay Krishna, et al

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:06.029062Z

Source-reported events for the cited work

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Observation b75e4ac4-c86f-46bd-9bce-b18b67a589b1 · outbound

This paper cites Ashraful Islam, Mohammed Eunus Ali, and Md Rizwan Parvez.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Ashraful Islam, Mohammed Eunus Ali, and Md Rizwan Parvez

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:05.802868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 116fbd93-6cb9-4413-9e0b-954d34226370 · outbound

This paper cites Efficient memory management for large language model serving with pagedattention.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Efficient memory management for large language model serving with pagedattention

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:05.494569Z

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Observation 0a67db17-e592-4c89-a2ba-2ece67286700 · outbound

This paper cites How far are llms from being our digital twins? a bench- mark for persona-based behavior chain simulation,.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction How far are llms from being our digital twins? a bench- mark for persona-based behavior chain simulation,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:05.283234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 4f30e398-699d-41a8-bb1f-781bc0824223 · outbound

This paper cites Self-refine: Iterative refinement with self- feedback.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Self-refine: Iterative refinement with self- feedback

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:05.112681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 0d1af677-e622-4245-b72e-520e6cb9e94c · outbound

This paper cites SelfcheckGPT: Zero-resource black-box hallucination detection for generative large language mod- els.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction SelfcheckGPT: Zero-resource black-box hallucination detection for generative large language mod- els

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:04.804208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 83c16cff-9c24-4439-80b8-443d4681e31e · outbound

This paper cites Stepwise reasoning error disruption attack of llms,.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Stepwise reasoning error disruption attack of llms,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:04.503061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8c7a84e3-168f-486b-a695-7a9673039c72 · outbound

This paper cites Scaling large language model-based multi-agent collab- oration.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Scaling large language model-based multi-agent collab- oration

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:04.248336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 53176b3c-c8f2-44c0-82bb-e849b8bb02a4 · outbound

This paper cites On the resilience of llm-based multi-agent collaboration with faulty agents,.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction On the resilience of llm-based multi-agent collaboration with faulty agents,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:04.020028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 84bd94c6-4127-4afd-b982-a4a3c6dfd195 · outbound

This paper cites MMLU-pro: A more robust and challenging multi- task language understanding benchmark.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction MMLU-pro: A more robust and challenging multi- task language understanding benchmark

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:03.717184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5edc5ee4-e8b6-49dc-b16a-f44e03f9b66e · outbound

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

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Chain-of-thought prompting elicits reasoning in large language models,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:03.401974Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9d1d8289-1671-4485-8ffc-2c88c39c1b83 · outbound

This paper cites Autogen: Enabling next-gen LLM applications via multi-agent conversations.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Autogen: Enabling next-gen LLM applications via multi-agent conversations

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:03.117929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ac14f2e0-438c-4be8-930b-155ecd6c1dba · outbound

This paper cites AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation

Reference 24

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Source-reported events for the cited work

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Observation 47230c89-3e4f-439e-914b-5f378e90563b · outbound

This paper cites [Yanget al., 2025 ] An Yang, Anfeng Li, Baosong Yang, et al.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction [Yanget al., 2025 ] An Yang, Anfeng Li, Baosong Yang, et al

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:02.826956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e6e84edf-0735-4745-933e-f13b615e2b1f · outbound

This paper cites React: Synergizing reasoning and acting in language mod- els.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction React: Synergizing reasoning and acting in language mod- els

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:02.599842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bd729305-cc2d-4f8e-8952-d85cdc811c46 · outbound

This paper cites AFlow: Automating agentic workflow generation.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction AFlow: Automating agentic workflow generation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:02.341776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ebfdde46-29e7-4c8d-8eb5-15a4d157a01e · outbound

This paper cites Improving alignment and robustness with circuit breakers, 2024.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Improving alignment and robustness with circuit breakers, 2024

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:02.109552Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a7117114-d2b3-4405-a56f-b881e1a21aad · outbound

This paper cites Why do multi-agent LLM systems fail? InThe Thirty-ninth An- nual Conference on Neural Information Processing Sys- tems Datasets and Benchmarks Track,.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Why do multi-agent LLM systems fail? InThe Thirty-ninth An- nual Conference on Neural Information Processing Sys- tems Datasets and Benchmarks Track,

Reference 2015

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:08.572328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 51dc5adc-c0f6-4679-82bd-da985bdad001 · outbound

This paper cites Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors,.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors,

Reference 2021

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:07.824165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b6fbb770-be89-42a4-aae8-c72ad6019632 · outbound

This paper cites an unresolved cited work.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Unresolved cited work

Reference 2023

Resolution: unresolved; raw_fallback, observed 2026-08-05T18:56:07.540689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ea0b5fe7-afb6-4d25-a1ae-d2bc7b0a1a44 · outbound

This paper cites The llama 3 herd of models,.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction The llama 3 herd of models,

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:06.339116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9f5f819b-0a40-4560-8da3-7e25b8d40cfc · outbound

This paper cites Collab: Con- trolled decoding using mixture of agents for LLM alignment.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Collab: Con- trolled decoding using mixture of agents for LLM alignment

Reference 2025

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:08.307905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 50810784-5bf8-49ba-a0ce-fd7369da4aad · outbound

This paper cites Re- thinking external slow-thinking: From snowball errors to probability of correct reasoning.

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction Re- thinking external slow-thinking: From snowball errors to probability of correct reasoning

Reference 2026

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T18:56:06.874159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.