510 citations · 998 across the 19 of their papers we have counts for
25 papers
Learning Private Representations through Entropy-based Adversarial Training
Tassilo Klein, Moin Nabi
How can we learn a representation with high predictive power while preserving user privacy? We present an adversarial representation learning method for sanitizing sensitive conten…
Contrastive Perplexity for Controlled Generation: An Application in Detoxifying Large Language Models
Tassilo Klein, Moin Nabi
The generation of toxic content by large language models (LLMs) remains a critical challenge for the safe deployment of language technology. We propose a novel framework for implic…
miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings
Tassilo Klein, Moin Nabi
This paper presents miCSE, a mutual information-based contrastive learning framework that significantly advances the state-of-the-art in few-shot sentence embedding. The proposed a…
Mixture-of-experts VAEs can disregard variation in surjective multimodal data
Jannik Wolff, Tassilo Klein, Moin Nabi +2
Machine learning systems are often deployed in domains that entail data from multiple modalities, for example, phenotypic and genotypic characteristics describe patients in healthc…
SCD: Self-Contrastive Decorrelation for Sentence Embeddings
Tassilo Klein, Moin Nabi
In this paper, we propose Self-Contrastive Decorrelation (SCD), a self-supervised approach. Given an input sentence, it optimizes a joint self-contrastive and decorrelation objecti…
Attention-based Contrastive Learning for Winograd Schemas
Tassilo Klein, Moin Nabi
Self-supervised learning has recently attracted considerable attention in the NLP community for its ability to learn discriminative features using a contrastive objective. This pap…