Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Luo, Haozheng"'
Autor:
Luo, Haozheng, Yu, Jiahao, Zhang, Wenxin, Li, Jialong, Hu, Jerry Yao-Chieh, Xing, Xinyu, Liu, Han
We introduce a low-resource safety enhancement method for aligning large language models (LLMs) without the need for supervised fine-tuning (SFT) or reinforcement learning from human feedback (RLHF). Our main idea is to exploit knowledge distillation
Externí odkaz:
http://arxiv.org/abs/2406.01514
Along with the remarkable successes of Language language models, recent research also started to explore the security threats of LLMs, including jailbreaking attacks. Attackers carefully craft jailbreaking prompts such that a target LLM will respond
Externí odkaz:
http://arxiv.org/abs/2405.20653
We present a Conversational Chain-of-Action (Conv-CoA) framework for Open-domain Conversational Question Answering (OCQA). Compared with literature, Conv-CoA addresses three major challenges: (i) unfaithful hallucination that is inconsistent with rea
Externí odkaz:
http://arxiv.org/abs/2405.17822
We present a Chain-of-Action (CoA) framework for multimodal and retrieval-augmented Question-Answering (QA). Compared to the literature, CoA overcomes two major challenges of current QA applications: (i) unfaithful hallucination that is inconsistent
Externí odkaz:
http://arxiv.org/abs/2403.17359
We introduce SMUTF, a unique approach for large-scale tabular data schema matching (SM), which assumes that supervised learning does not affect performance in open-domain tasks, thereby enabling effective cross-domain matching. This system uniquely c
Externí odkaz:
http://arxiv.org/abs/2402.01685
Weak labeling is a popular weak supervision strategy for Named Entity Recognition (NER) tasks, with the goal of reducing the necessity for hand-crafted annotations. Although there are numerous remarkable annotation tools for NER labeling, the subject
Externí odkaz:
http://arxiv.org/abs/2208.10241
In high dimensions, most machine learning method perform fragile even there are a little outliers. To address this, we hope to introduce a new method with the base learner, such as Bayesian regression or stochastic gradient descent to solve the probl
Externí odkaz:
http://arxiv.org/abs/2206.07139
In this work, we build recent advances in distributional reinforcement learning to give a state-of-art distributional variant of the model based on the IQN. We achieve this by using the GAN model's generator and discriminator function with the quanti
Externí odkaz:
http://arxiv.org/abs/2206.05860
Idioms are special fixed phrases usually derived from stories. They are commonly used in casual conversations and literary writings. Their meanings are usually highly non-compositional. The idiom cloze task is a challenge problem in Natural Language
Externí odkaz:
http://arxiv.org/abs/2112.02994
In this paper, we introduce a robotic agent specifically designed to analyze external environments and address participants' questions. The primary focus of this agent is to assist individuals using language-based interactions within video-based scen
Externí odkaz:
http://arxiv.org/abs/2012.00822