Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:27:17.758470Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2505.18847.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:27:17.758470Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T12:44:55.338961Z
A source-named dated measurement, never combined with another source.
Source: cited_works
64 of 64 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 212d2261-3633-4cf1-a74f-3c27f8fea54e · outbound
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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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
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Observation 63e84086-0153-4415-bc15-78ff6da034b7 · outbound
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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Observation 2b79888d-f8ea-44b8-85dc-47cdba0f3ffe · outbound
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
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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Yhdego, Fatemeh Khadem, and Fatemeh Afghah
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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
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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
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Observation 557a3b9c-f106-4a93-8881-baa023801c61 · outbound
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
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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework A new algorithm for data compression
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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework The Llama 3 Herd of Models
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Observation 5bd3f457-ba4f-4686-b92a-5c34d1ba9734 · outbound
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
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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Interpretation of Intracardiac Electrograms Through Textual Representations
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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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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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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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Observation e5887e88-87a5-49e2-be66-2243bce3462b · outbound
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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Observation 6a87eba3-bea0-4a8a-b135-49f2784ead25 · outbound
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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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Scaling Laws for Neural Language Models
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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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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
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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework A simple weight decay can improve generalization
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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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Observation 7ca8b53f-82e0-4a78-809b-3b5acf4ad5f3 · outbound
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
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Observation 5cd563a0-ac45-485b-b142-9267f32d4ab0 · outbound
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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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
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Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Teach Multimodal LLMs to Comprehend Electrocardiographic Images
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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
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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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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
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Observation 5586bfcf-b532-449a-b8b9-ae5fde386ecb · outbound
Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Cardiovascular diseases, 2024
Reference 36
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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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Observation c0b1643f-42a3-4bd2-bbe5-e29d7f7db5d8 · outbound
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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Observation b9d90865-a356-4718-99e5-1104c373bb3e · outbound
Signal, Image, or Symbolic: Exploring the Best Input Representation for Electrocardiogram-Language Models Through a Unified Framework Qwen2.5 Technical Report
Reference 41
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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
Reference 42
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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
Reference 44
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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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Reference 46
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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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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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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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Reference 50
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Reference 52
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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
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Observation e091550e-dd75-4e69-bd75-553681a6f0dc · outbound
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
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Reference 55
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Reference 56
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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
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Observation 1070e08c-2266-4250-a3c9-dc5120b19022 · outbound
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
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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
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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
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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
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Reference 62
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Reference 63
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Reference 2025
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