Standard practice within Reinforcement Learning from Human Feedback (RLHF) involves
optimizing against a Reward Model (RM), which itself is trained to reflect human preferences …

When reading texts for text classification tasks, a large number of words are irrelevant, and
in text classification tasks, the traditional self-attention mechanism has the problem of weight …

Text generation has become more accessible than ever, and the increasing interest in these
systems, especially those using large language models, has spurred an increasing number …

Adversarial attack serves as a major challenge for neural network models in NLP, which
precludes the model's deployment in safety-critical applications. A recent line of work …

Reinforcement Learning from Human Feedback (RLHF) involves training policy models
(PMs) and reward models (RMs) to align language models with human preferences. Instead …