Discourse Based Evaluation of Language Understanding
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Updated
Jan 28, 2023 - Jupyter Notebook
Discourse Based Evaluation of Language Understanding
Code to reproduce experiments from the paper "Continual Pre-Training Mitigates Forgetting in Language and Vision" https://arxiv.org/abs/2205.09357
Fair quantitative comparison of NLP embeddings from GloVe to RoBERTa with Sequential Bayesian Optimization fine-tuning using Flair and SentEval. Extension of HyperOpt library to log_b priors.
Reinforcement Calibration SimCSE, combining contrastive learning, artificial potential fields, perceptual loss, and RLHF to achieve improved Semantic Textual Similarity (STS) embeddings. PyTorch-based implementations of PerceptualBERT and ForceBasedInfoNCE, along with fine-tuning capabilities via RLHF and evaluation using SentEval.
Composition of embeddings
Code for "Model Agnostic Knowledge Transfer Methods for Sentence Embedding Models" paper by Gunel and Amasyali.
Advanced Topics in Computational Semantics (ATCS) - Practical 1
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