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of 3 599
pro vyhledávání: '"Jiang, Han"'
Warning: this paper contains model outputs exhibiting unethical information. Large Language Models (LLMs) have achieved significant breakthroughs, but their generated unethical content poses potential risks. Measuring value alignment of LLMs becomes
Externí odkaz:
http://arxiv.org/abs/2406.14230
Understanding the evolution of 3D scenes is important for effective autonomous driving. While conventional methods mode scene development with the motion of individual instances, world models emerge as a generative framework to describe the general s
Externí odkaz:
http://arxiv.org/abs/2405.20337
Despite the remarkable achievements of language models (LMs) across a broad spectrum of tasks, their propensity for generating toxic outputs remains a prevalent concern. Current solutions involving finetuning or auxiliary models usually require exten
Externí odkaz:
http://arxiv.org/abs/2404.10464
Autor:
Yang, Shu, Su, Jiayuan, Jiang, Han, Li, Mengdi, Cheng, Keyuan, Ali, Muhammad Asif, Hu, Lijie, Wang, Di
With the rise of large language models (LLMs), ensuring they embody the principles of being helpful, honest, and harmless (3H), known as Human Alignment, becomes crucial. While existing alignment methods like RLHF, DPO, etc., effectively fine-tune LL
Externí odkaz:
http://arxiv.org/abs/2404.00486
Current Neural Radiance Fields (NeRF) can generate photorealistic novel views. For editing 3D scenes represented by NeRF, with the advent of generative models, this paper proposes Inpaint4DNeRF to capitalize on state-of-the-art stable diffusion model
Externí odkaz:
http://arxiv.org/abs/2401.00208
Autor:
Wang, Lening, Ren, Yilong, Jiang, Han, Cai, Pinlong, Fu, Daocheng, Wang, Tianqi, Cui, Zhiyong, Yu, Haiyang, Wang, Xuesong, Zhou, Hanchu, Huang, Helai, Wang, Yinhai
Traffic accidents, being a significant contributor to both human casualties and property damage, have long been a focal point of research for many scholars in the field of traffic safety. However, previous studies, whether focusing on static environm
Externí odkaz:
http://arxiv.org/abs/2312.13156
Warning: this paper includes model outputs showing offensive content. Recent large-scale Visual-Language Generative Models (VLGMs) have achieved unprecedented improvement in multimodal image/text generation. However, these models might also generate
Externí odkaz:
http://arxiv.org/abs/2312.11523
Recently, temporal action localization (TAL) has garnered significant interest in information retrieval community. However, existing supervised/weakly supervised methods are heavily dependent on extensive labeled temporal boundaries and action catego
Externí odkaz:
http://arxiv.org/abs/2312.07384
Unsupervised rationale extraction aims to extract concise and contiguous text snippets to support model predictions without any annotated rationale. Previous studies have used a two-phase framework known as the Rationalizing Neural Prediction (RNP) f
Externí odkaz:
http://arxiv.org/abs/2311.02344
Opinion summarization is expected to digest larger review sets and provide summaries from different perspectives. However, most existing solutions are deficient in epitomizing extensive reviews and offering opinion summaries from various angles due t
Externí odkaz:
http://arxiv.org/abs/2310.13340