Исследование абляции
Related Papers
Understanding the Value of Features for Coreference Resolution
In recent years there has been substantial work on the important problem of coreference res- olution, most of which has concentrated on the development of new models and algo- rithmic …...
GU IRLAB at SemEval-2018 Task 7: Tree-LSTMs for Scientific Relation Classification
AbstractSemEval 2018 Task 7 focuses on relation extraction and classification in scientific literature. In this work, we present our tree-based LSTM network for this shared task. Our approach placed 9th …...
Plot and Rework: Modeling Storylines for Visual Storytelling
Writing a coherent and engaging story is not easy. Creative writers use their knowledge and worldview to put disjointed elements together to form a coherent storyline, and work and rework …...
Improving In-Context Few-Shot Learning via Self-Supervised Training
AbstractSelf-supervised pretraining has made few-shot learning possible for many NLP tasks. But the pretraining objectives are not typically adapted specifically for in-context few-shot learning. In this paper, we propose to …...
Papago’s Submission to the WMT22 Quality Estimation Shared Task
AbstractThis paper describes anonymous submission to the WMT 2022 Quality Estimation shared task. We participate in Task 1: Quality Prediction for both sentence and word-level quality prediction tasks. Our system …...
Textless Speech Emotion Conversion using Discrete & Decomposed Representations
AbstractSpeech emotion conversion is the task of modifying the perceived emotion of a speech utterance while preserving the lexical content and speaker identity. In this study, we cast the problem …...
mCPT at SemEval-2023 Task 3: Multilingual Label-Aware Contrastive Pre-Training of Transformers for Few- and Zero-shot Framing Detection
AbstractThis paper presents the winning system for the zero-shot Spanish framing detection task, which also achieves competitive places in eight additional languages. The challenge of the framing detection task lies …...
Revisiting Offline Compression: Going Beyond Factorization-based Methods for Transformer Language Models
AbstractRecent transformer language models achieve outstanding results in many natural language processing (NLP) tasks. However, their enormous size often makes them impractical on memory-constrained devices, requiring practitioners to compress them …...