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Found 8 papers, 5 papers with code
CantTalkAboutThis: Aligning Language Models to Stay on Topic in Dialogues
Recent advancements in instruction-tuning datasets have predominantly focused on specific tasks like mathematical or logical reasoning.
HelpSteer: Multi-attribute Helpfulness Dataset for SteerLM
To alleviate this problem, we collect HelpSteer, a multi-attribute helpfulness dataset annotated for the various aspects that make responses helpful.
Evolving Domain Adaptation of Pretrained Language Models for Text Classification
Adapting pre-trained language models (PLMs) for time-series text classification amidst evolving domain shifts (EDS) is critical for maintaining accuracy in applications like stance detection.
SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF
Model alignment with human preferences is an essential step in making Large Language Models (LLMs) helpful and consistent with human values.
Prompt Learning for Domain Adaptation in Task-Oriented Dialogue
We show that canonical forms offer a promising alternative to traditional methods for intent classification.
Local Byte Fusion for Neural Machine Translation
Subword tokenization schemes are the dominant technique used in current NLP models.
Learning Improvised Chatbots from Adversarial Modifications of Natural Language Feedback
The ubiquitous nature of chatbots and their interaction with users generate an enormous amount of data.
Towards Lifelong Self-Supervision For Unpaired Image-to-Image Translation
Unpaired Image-to-Image Translation (I2IT) tasks often suffer from lack of data, a problem which self-supervised learning (SSL) has recently been very popular and successful at tackling.
