29 citations · 66 across the 14 of their papers we have counts for
6 papers · 1 filter
Controlling the Extraction of Memorized Data from Large Language Models via Prompt-Tuning
Mustafa Safa Ozdayi, Charith Peris, Jack FitzGerald +5
Large Language Models (LLMs) are known to memorize significant portions of their training data. Parts of this memorized content have been shown to be extractable by simply querying…
Differentially Private Decoding in Large Language Models
Jimit Majmudar, Christophe Dupuy, Charith Peris +3
Recent large-scale natural language processing (NLP) systems use a pre-trained Large Language Model (LLM) on massive and diverse corpora as a headstart. In practice, the pre-traine…
Canary Extraction in Natural Language Understanding Models
Rahil Parikh, Christophe Dupuy, Rahul Gupta
Natural Language Understanding (NLU) models can be trained on sensitive information such as phone numbers, zip-codes etc. Recent literature has focused on Model Inversion Attacks (…
An Efficient DP-SGD Mechanism for Large Scale NLP Models
Christophe Dupuy, Radhika Arava, Rahul Gupta +1
Recent advances in deep learning have drastically improved performance on many Natural Language Understanding (NLU) tasks. However, the data used to train NLU models may contain pr…
FedNLP: Benchmarking Federated Learning Methods for Natural Language Processing Tasks
Bill Yuchen Lin, Chaoyang He, Zihang Zeng +7
Increasing concerns and regulations about data privacy and sparsity necessitate the study of privacy-preserving, decentralized learning methods for natural language processing (NLP…
Self-Attention Gazetteer Embeddings for Named-Entity Recognition
Stanislav Peshterliev, Christophe Dupuy, Imre Kiss
Recent attempts to ingest external knowledge into neural models for named-entity recognition (NER) have exhibited mixed results. In this work, we present GazSelfAttn, a novel gazet…