Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework | Paper Citation Record

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This paper cites The complexities of physician supply and demand: Projections from 2021 to 2036, 03 2024.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework The complexities of physician supply and demand: Projections from 2021 to 2036, 03 2024

Reference 1

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This paper cites A brief review: history to understand fundamentals of electrocardiography.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework A brief review: history to understand fundamentals of electrocardiography

Reference 2

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This paper cites Classification of 12-lead ecgs: The physionet/computing in cardiology challenge 2020, 07 2022.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Classification of 12-lead ecgs: The physionet/computing in cardiology challenge 2020, 07 2022

Reference 3

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This paper cites Meteor: An automatic metric for mt evaluation with improved correlation with human judgments.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Meteor: An automatic metric for mt evaluation with improved correlation with human judgments

Reference 4

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This paper cites Llm-abba: Understand time series via symbolic approximation, 2024 a.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Llm-abba: Understand time series via symbolic approximation, 2024 a

Reference 5

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This paper cites Quantized symbolic time series approximation.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Quantized symbolic time series approximation

Reference 6

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This paper cites Yhdego, Fatemeh Khadem, and Fatemeh Afghah.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Yhdego, Fatemeh Khadem, and Fatemeh Afghah

Reference 7

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This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 8

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This paper cites An image is worth 16x16 words: Transformers for image recognition at scale, 2021.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework An image is worth 16x16 words: Transformers for image recognition at scale, 2021

Reference 9

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework ABBA: Adaptive Brownian bridge-based symbolic aggregation of time series

Reference 10

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This paper cites A new algorithm for data compression.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework A new algorithm for data compression

Reference 11

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This paper cites The Llama 3 Herd of Models.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework The Llama 3 Herd of Models

Reference 12

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This paper cites ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling

Reference 13

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This paper cites Interpretation of Intracardiac Electrograms Through Textual Representations.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Interpretation of Intracardiac Electrograms Through Textual Representations

Reference 14

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This paper cites Hannun, Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Hannun, Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H

Reference 15

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This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework LoRA: Low-Rank Adaptation of Large Language Models

Reference 16

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This paper cites Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Reading Your Heart: Learning ECG Words and Sentences via Pre-training ECG Language Model

Reference 17

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Unresolved cited work

Reference 18

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This paper cites Counties most in need of cardiologists are the most likely to have none, 07 2024.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Counties most in need of cardiologists are the most likely to have none, 07 2024

Reference 19

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This paper cites Scaling Laws for Neural Language Models.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Scaling Laws for Neural Language Models

Reference 20

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Kingma and Jimmy Ba

Reference 21

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This paper cites CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients

Reference 22

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This paper cites A simple weight decay can improve generalization.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework A simple weight decay can improve generalization

Reference 23

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This paper cites Gem: Empowering mllm for grounded ecg understanding with time series and images, 2025.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Gem: Empowering mllm for grounded ecg understanding with time series and images, 2025

Reference 24

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This paper cites Time Series as Images: Vision Transformer for Irregularly Sampled Time Series.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Time Series as Images: Vision Transformer for Irregularly Sampled Time Series

Reference 25

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

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Rouge: A package for automatic evaluation of summaries

Reference 26

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This paper cites Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement

Reference 27

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Visual Instruction Tuning

Reference 28

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This paper cites Teach Multimodal LLMs to Comprehend Electrocardiographic Images.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Teach Multimodal LLMs to Comprehend Electrocardiographic Images

Reference 29

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This paper cites Real-time frequency-independent single-lead and single-beat myocardial infarction detection.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Real-time frequency-independent single-lead and single-beat myocardial infarction detection

Reference 30

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram

Reference 31

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Harnessing Vision Models for Time Series Analysis: A Survey

Reference 32

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Electrocardiogram classification by modified efficientnet with data augmentation

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Lead-agnostic Self-supervised Learning for Local and Global Representations of Electrocardiogram

Reference 34

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This paper cites ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogram.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogram

Reference 35

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Cardiovascular diseases, 2024

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Bleu: a method for automatic evaluation of machine translation

Reference 37

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Boosting Masked ECG-Text Auto-Encoders as Discriminative Learners

Reference 38

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Unresolved cited work

Reference 39

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Rosenberg, Emerson Liu, Douglas Weber, and Ding Zhao

Reference 40

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Qwen2.5 Technical Report

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Learning transferable visual models from natural language supervision

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Cardiologist-Level Arrhythmia Detection with Convolutional Neural Networks

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Ribeiro, Gabriela M.M

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Mortazavi, Adrian D

Reference 45

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Image-based time series forecasting: A deep convolutional neural network approach

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This paper cites ECG-Image-Kit: A Synthetic Image Generation Toolbox to Facilitate Deep Learning-Based Electrocardiogram Digitization.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework ECG-Image-Kit: A Synthetic Image Generation Toolbox to Facilitate Deep Learning-Based Electrocardiogram Digitization

Reference 47

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This paper cites Deep learning for ecg analysis: Benchmarks and insights from ptb-xl.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Deep learning for ecg analysis: Benchmarks and insights from ptb-xl

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This paper cites HeartBERT: A Self-Supervised ECG Embedding Model for Efficient and Effective Medical Signal Analysis.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework HeartBERT: A Self-Supervised ECG Embedding Model for Efficient and Effective Medical Signal Analysis

Reference 49

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Observation 5994817c-556c-4e59-9af9-1d5fc63bca13 · outbound

This paper cites Electrocardiogram-Language Model for Few-Shot Question Answering with Meta Learning.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Electrocardiogram-Language Model for Few-Shot Question Answering with Meta Learning

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Observation 74cd79f4-6e16-4e27-98f0-e4a904f5b64b · outbound

This paper cites Electrocardiogram Report Generation and Question Answering via Retrieval-Augmented Self-Supervised Modeling.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Electrocardiogram Report Generation and Question Answering via Retrieval-Augmented Self-Supervised Modeling

Reference 51

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Observation 961b959b-2f27-4f01-9aaf-6f76fbb6283d · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Gemma 2: Improving Open Language Models at a Practical Size

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.147110Z

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Observation fa8d9a44-01f9-4c82-a1c7-196ee7b0e065 · outbound

This paper cites Heartbeit: Vision transformer for electrocardiogram data improves diagnostic performance at low sample sizes, 2022.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Heartbeit: Vision transformer for electrocardiogram data improves diagnostic performance at low sample sizes, 2022

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:27:20.218987Z

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Observation e091550e-dd75-4e69-bd75-553681a6f0dc · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.224868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ef24b06-9b4a-4b26-9ce0-a2d777dc7206 · outbound

This paper cites Lunze, Wojciech Samek, and Tobias Schaeffter.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Lunze, Wojciech Samek, and Tobias Schaeffter

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.275996Z

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Observation ff66dc9e-dd2c-4cee-a1c0-f5d019e73b49 · outbound

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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Unresolved cited work

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.319818Z

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Observation c38d68a9-0103-4f18-9fc3-c4372084196e · outbound

This paper cites Routine electrocardiogram screening and cardiovascular disease events in adults.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Routine electrocardiogram screening and cardiovascular disease events in adults

Reference 57

Resolution: verified exact; raw_fallback, observed 2026-08-07T14:27:18.716310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1070e08c-2266-4250-a3c9-dc5120b19022 · outbound

This paper cites Sigmoid Loss for Language Image Pre-Training.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Sigmoid Loss for Language Image Pre-Training

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.423758Z

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Unavailable: canonical work link unavailable.

Observation 049af18a-c409-4ea4-810b-7fb38831f457 · outbound

This paper cites Maefe: Masked autoencoders family of electrocardiogram for self-supervised pretraining and transfer learning.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Maefe: Masked autoencoders family of electrocardiogram for self-supervised pretraining and transfer learning

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.476512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d41704b9-5cf6-442f-a7af-d419b65370cc · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework BERTScore: Evaluating Text Generation with BERT

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.516583Z

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Unavailable: canonical work link unavailable.

Observation 8942c84c-f456-44c2-90a7-30903e261426 · outbound

This paper cites ECG-Chat: A Large ECG-Language Model for Cardiac Disease Diagnosis.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework ECG-Chat: A Large ECG-Language Model for Cardiac Disease Diagnosis

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.600151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7a1cd14-dee7-4f98-8a8e-27e2961c45fd · outbound

This paper cites A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.663497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c8f6ebb-54f3-4e32-8df6-1f226a754d4b · outbound

This paper cites P Xing, Hao Zhang, Joseph E.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework P Xing, Hao Zhang, Joseph E

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.718143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eca5c8ab-4fb8-404a-aec2-81a973d64ec0 · outbound

This paper cites See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers.

Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T14:27:17.758470Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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