3 citations · 7 across the 6 of their papers we have counts for
21 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)…
Analyzing Modality Robustness in Multimodal Sentiment Analysis
Devamanyu Hazarika, Yingting Li, Bo Cheng +3
Building robust multimodal models are crucial for achieving reliable deployment in the wild. Despite its importance, less attention has been paid to identifying and improving the r…
So Different Yet So Alike! Constrained Unsupervised Text Style Transfer
Abhinav Ramesh Kashyap, Devamanyu Hazarika, Min-Yen Kan +2
Automatic transfer of text between domains has become popular in recent times. One of its aims is to preserve the semantic content of text being translated from source to target do…
Exemplars-guided Empathetic Response Generation Controlled by the Elements of Human Communication
Navonil Majumder, Deepanway Ghosal, Devamanyu Hazarika +3
The majority of existing methods for empathetic response generation rely on the emotion of the context to generate empathetic responses. However, empathy is much more than generati…
Recognizing Emotion Cause in Conversations
Soujanya Poria, Navonil Majumder, Devamanyu Hazarika +9
We address the problem of recognizing emotion cause in conversations, define two novel sub-tasks of this problem, and provide a corresponding dialogue-level dataset, along with str…