1 citations · 1 across the 3 of their papers we have counts for
4 papers
Resprompt: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models
Song Jiang, Zahra Shakeri, Aaron Chan +8
Chain-of-thought (CoT) prompting, which offers step-by-step problem-solving rationales, has impressively unlocked the reasoning potential of large language models (LLMs). Yet, the…
Meta-training with Demonstration Retrieval for Efficient Few-shot Learning
Aaron Mueller, Kanika Narang, Lambert Mathias +2
Large language models show impressive results on few-shot NLP tasks. However, these models are memory and computation-intensive. Meta-training allows one to leverage smaller models…
Defending Against Patch-based Backdoor Attacks on Self-Supervised Learning
Ajinkya Tejankar, Maziar Sanjabi, Qifan Wang +4
Recently, self-supervised learning (SSL) was shown to be vulnerable to patch-based data poisoning backdoor attacks. It was shown that an adversary can poison a small part of the un…
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation
Nan Wang, Qifan Wang, Yi-Chia Wang +5
As language models become increasingly integrated into our digital lives, Personalized Text Generation (PTG) has emerged as a pivotal component with a wide range of applications. H…