15 citations · 21 across the 8 of their papers we have counts for
10 papers
Data-Efficient Alignment of Large Language Models with Human Feedback Through Natural Language
Di Jin, Shikib Mehri, Devamanyu Hazarika +4
Learning from human feedback is a prominent technique to align the output of large language models (LLMs) with human expectations. Reinforcement learning from human feedback (RLHF)…
Inducer-tuning: Connecting Prefix-tuning and Adapter-tuning
Yifan Chen, Devamanyu Hazarika, Mahdi Namazifar +3
Prefix-tuning, or more generally continuous prompt tuning, has become an essential paradigm of parameter-efficient transfer learning. Using a large pre-trained language model (PLM)…
Correcting Automated and Manual Speech Transcription Errors using Warped Language Models
Mahdi Namazifar, John Malik, Li Erran Li +2
Masked language models have revolutionized natural language processing systems in the past few years. A recently introduced generalization of masked language models called warped l…
Language Model is All You Need: Natural Language Understanding as Question Answering
Mahdi Namazifar, Alexandros Papangelis, Gokhan Tur +1
Different flavors of transfer learning have shown tremendous impact in advancing research and applications of machine learning. In this work we study the use of a specific family o…
Warped Language Models for Noise Robust Language Understanding
Mahdi Namazifar, Gokhan Tur, Dilek Hakkani Tür
Masked Language Models (MLM) are self-supervised neural networks trained to fill in the blanks in a given sentence with masked tokens. Despite the tremendous success of MLMs for va…
Joint Contextual Modeling for ASR Correction and Language Understanding
Yue Weng, Sai Sumanth Miryala, Chandra Khatri +8
The quality of automatic speech recognition (ASR) is critical to Dialogue Systems as ASR errors propagate to and directly impact downstream tasks such as language understanding (LU…