Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement | Paper Citation Record

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This paper cites Unsupervised Label Noise Modeling and Loss Correction.

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unsupervised Label Noise Modeling and Loss Correction

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement A Closer Look at Memorization in Deep Networks

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Language Models are Few-Shot Learners

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This paper cites Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision.

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

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This paper cites Learning with Instance-Dependent Label Noise: A Sample Sieve Approach.

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Learning with Instance-Dependent Label Noise: A Sample Sieve Approach

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement The Llama 3 Herd of Models

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This paper cites Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels.

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels

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This paper cites Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction.

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement CARD: Classification and Regression Diffusion Models

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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This paper cites SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals.

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals

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This paper cites Hastings, Sherri Weitl-Harms, Joseph Doty, Zachary J.

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Hastings, Sherri Weitl-Harms, Joseph Doty, Zachary J

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Mixtral of Experts

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This paper cites Learning with Neighbor Consistency for Noisy Labels.

Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Learning with Neighbor Consistency for Noisy Labels

Reference 22

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Adam: A Method for Stochastic Optimization

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Dirichlet Variational Autoencoder

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Open-world Multi-label Text Classification with Extremely Weak Supervision

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Relative representations enable zero-shot latent space communication

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement TESS: Text-to-Text Self-Conditioned Simplex Diffusion

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement SELF: Learning to Filter Noisy Labels with Self-Ensembling

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement GPT-4 Technical Report

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement PyTorch: An Imperative Style, High-Performance Deep Learning Library

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Zero is Not Hero Yet: Benchmarking Zero-Shot Performance of LLMs for Financial Tasks

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Is ChatGPT a General-Purpose Natural Language Processing Task Solver?

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Weiss, Niru Maheswaranathan, and Surya Ganguli

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Large Language Models for Data Annotation and Synthesis: A Survey

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement A Survey on Data Synthesis and Augmentation for Large Language Models

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Numerical Claim Detection in Finance: A New Financial Dataset, Weak-Supervision Model, and Market Analysis

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement HuggingFace's Transformers: State-of-the-art Natural Language Processing

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement T-SciQ: Teaching Multimodal Chain-of-Thought Reasoning via Mixed Large Language Model Signals for Science Question Answering

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Unresolved cited work

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement How does Disagreement Help Generalization against Label Corruption?

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Part-dependent Label Noise: Towards Instance-dependent Label Noise

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement WRENCH: A Comprehensive Benchmark for Weak Supervision

Reference 60

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement PRBoost: Prompt-Based Rule Discovery and Boosting for Interactive Weakly-Supervised Learning

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Instance-dependent Label-noise Learning under a Structural Causal Model

Reference 62

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Learning Noise Transition Matrix from Only Noisy Labels via Total Variation Regularization

Reference 63

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels

Reference 64

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning

Reference 66

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach

Reference 67

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling

Reference 68

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Weaker Than You Think: A Critical Look at Weakly Supervised Learning

Reference 74

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Tasks

Reference 75

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement For the provided text below, determine the most appropri- ate category based on the descriptions above

Reference 96

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Reference 2015

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach

Reference 2017

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement WinoGrande: An Adversarial Winograd Schema Challenge at Scale

Reference 2019

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Confidence Scores Make Instance-dependent Label-noise Learning Possible

Reference 2021

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Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations

Reference 2022

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