Introduces a method to design structure-specific relational inductive biases for a base transformer architecture, enabling end-to-end transcription of documents with intrinsic structures, demonstrated on sheet music, shape drawings, and mechanical engineering drawings.
Compositional semantic parsing on semi-structured tables
6 Pith papers cite this work. Polarity classification is still indexing.
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NeuralEmu uses machine learning trained on real 5G telemetry to predict resource blocks and modulation for multiple users, cutting emulation error by 51-57% versus prior tools for web, video, and gaming metrics.
FinBERT adapts BERT to the financial domain and outperforms prior state-of-the-art methods on financial sentiment analysis tasks.
FoNE encodes numbers as single tokens via Fourier features and outperforms subword and digit-wise embeddings on addition, subtraction, and multiplication with far less data.
Presents REMOD, a graph-based supervised method for extracting semantic relations between entities in text to support modeling of online discourse and potential misinformation.
DenoGrad refines noisy tabular and time-series data by optimizing inputs via gradients from a fixed model, yielding better downstream predictions on ten real-world datasets while preserving data statistics.
citing papers explorer
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A document is worth a structured record: Principled inductive bias design for document recognition
Introduces a method to design structure-specific relational inductive biases for a base transformer architecture, enabling end-to-end transcription of documents with intrinsic structures, demonstrated on sheet music, shape drawings, and mechanical engineering drawings.
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NeuralEmu: in situ Measurement-Driven, ML-based, High-Fidelity 5G Network Emulation
NeuralEmu uses machine learning trained on real 5G telemetry to predict resource blocks and modulation for multiple users, cutting emulation error by 51-57% versus prior tools for web, video, and gaming metrics.
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FinBERT: Financial Sentiment Analysis with Pre-trained Language Models
FinBERT adapts BERT to the financial domain and outperforms prior state-of-the-art methods on financial sentiment analysis tasks.
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FoNE: Precise Single-Token Number Embeddings via Fourier Features
FoNE encodes numbers as single tokens via Fourier features and outperforms subword and digit-wise embeddings on addition, subtraction, and multiplication with far less data.
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REMOD: Relation Extraction for Modeling Online Discourse
Presents REMOD, a graph-based supervised method for extracting semantic relations between entities in text to support modeling of online discourse and potential misinformation.
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DenoGrad: A Gradient-Based Framework for Data Refinement in Tabular and Time-Series Learning
DenoGrad refines noisy tabular and time-series data by optimizing inputs via gradients from a fixed model, yielding better downstream predictions on ten real-world datasets while preserving data statistics.