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Hits 421 – 440 of 20.397

421
How to Train BERT with an Academic Budget ...
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422
Improving Span Representation for Domain-adapted Coreference Resolution ...
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423
Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level ...
Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.334 Abstract: Larger language models have higher accuracy on average, but are they better on every single instance (datapoint)? Some work suggests larger models have higher out-of-distribution robustness, while other work suggests they have lower accuracy on rare subgroups. To understand these differences, we investigate these models at the level of individual instances. However, one major challenge is that individual predictions are highly sensitive to noise in the randomness in training. We develop statistically rigorous methods to address this, and after accounting for pretraining and finetuning noise, we find that our BERT-Large is worse than BERT-Mini on at least 1-4% of instances across MNLI, SST-2, and QQP, compared to the overall accuracy improvement of 2-10%. We also find that finetuning noise increases with model size, and that instance-level accuracy has momentum: improvement from BERT-Mini to BERT-Medium correlates with improvement from ...
Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
URL: https://dx.doi.org/10.48448/yyy2-1q93
https://underline.io/lecture/26425-are-larger-pretrained-language-models-uniformly-betterquestion-comparing-performance-at-the-instance-level
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424
Temporal Adaptation of BERT and Performance on Downstream Document Classification: Insights from Social Media ...
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425
An Empirical Study on Multiple Information Sources for Zero-Shot Fine-Grained Entity Typing ...
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426
Looking for Confirmations: An Effective and Human-Like Visual Dialogue Strategy ...
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427
Context Sensitivity Estimation in Toxicity Detection ...
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428
MRF-Chat: Improving Dialogue with Markov Random Fields ...
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429
Exploring Metaphoric Paraphrase Generation ...
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430
CrossVQA: Scalably Generating Benchmarks for Systematically Testing VQA Generalization ...
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431
Latent Hatred: A Benchmark for Understanding Implicit Hate Speech ...
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432
HypMix: Hyperbolic Interpolative Data Augmentation ...
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433
Risk Minimization for Zero-shot Sequence Labeling ...
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434
STaCK: Sentence Ordering with Temporal Commonsense Knowledge ...
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435
ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning ...
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436
GTM: A Generative Triple-wise Model for Conversational Question Generation ...
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437
Keep It Simple: Unsupervised Simplification of Multi-Paragraph Text ...
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438
GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot Filling ...
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439
Discovering Dialog Structure Graph for Coherent Dialog Generation ...
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440
Time-implicit Hierarchies in Different Languages ...
Anonymous. - : Zenodo, 2021
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