Results 11 to 20 of about 3,152,438 (133)
Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 We present Video-LLaMA a multi-modal framework that empowers Large Language Models (LLMs) with the capability of understanding both visual and auditory content in the video.
Hang Zhang, Xin Li, Lidong Bing
semanticscholar +1 more source
Is ChatGPT a General-Purpose Natural Language Processing Task Solver? [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 Spurred by advancements in scale, large language models (LLMs) have demonstrated the ability to perform a variety of natural language processing (NLP) tasks zero-shot -- i.e., without adaptation on downstream data.
Chengwei Qin +5 more
semanticscholar +1 more source
SpeechGPT: Empowering Large Language Models with Intrinsic Cross-Modal Conversational Abilities [PDF]
Conference on Empirical Methods in Natural Language Processing, 2023 Multi-modal large language models are regarded as a crucial step towards Artificial General Intelligence (AGI) and have garnered significant interest with the emergence of ChatGPT.
Dong Zhang +6 more
semanticscholar +1 more source
Red Teaming Language Models with Language Models [PDF]
Conference on Empirical Methods in Natural Language Processing, 2022 Language Models (LMs) often cannot be deployed because of their potential to harm users in hard-to-predict ways. Prior work identifies harmful behaviors before deployment by using human annotators to hand-write test cases.
Ethan Perez +8 more
semanticscholar +1 more source
A Survey of GPT-3 Family Large Language Models Including ChatGPT and GPT-4 [PDF]
Natural Language Processing Journal, 2023 Large language models (LLMs) are a special class of pretrained language models obtained by scaling model size, pretraining corpus and computation. LLMs, because of their large size and pretraining on large volumes of text data, exhibit special abilities ...
Katikapalli Subramanyam Kalyan
semanticscholar +1 more source
AudioLM: A Language Modeling Approach to Audio Generation [PDF]
IEEE/ACM Transactions on Audio Speech and Language Processing, 2022 We introduce AudioLM, a framework for high-quality audio generation with long-term consistency. AudioLM maps the input audio to a sequence of discrete tokens and casts audio generation as a language modeling task in this representation space. We show how
Zalán Borsos +10 more
semanticscholar +1 more source
Annals of Human Genetics, Volume 87, Issue 5, Page 210-221, September 2023., 2023 Abstract During the colonial period in South America, many autochthonous populations were affected by relocation by European missionary reductions and other factors that impacted and reconfigured their genetic makeup. Presently, the descendants of some “reduced” and other isolated groups are distributed in the Amazonian areas of Peru, Bolivia, and ...
José R. Sandoval +6 more
wiley +1 more source
OF FERAL AND OBEDIENT COWS: Colonization as Domestication in the Paraguayan Chaco
Cultural Anthropology, Volume 38, Issue 1, Page 8-35, February 2023., 2023 ABSTRACT In the Paraguayan Chaco, cattle evoke images of power, prosperity, and celebration, but they also trigger one of the quickest deforestation processes in the world. The presence of cattle in the region has deep historical roots, dating back to the beginning of the colonization process, when the establishment of a double economy based on cattle ...
VALENTINA BONIFACIO
wiley +1 more source
Diverse Articulations of Urban Indigeneity among Lowland Indigenous Groups in Santa Cruz, Bolivia
Bulletin of Latin American Research, Volume 41, Issue 1, Page 37-52, January 2022., 2022 This article contrasts politico‐legal understandings of indigeneity to the lived experiences of urban residents in Santa Cruz (Bolivia) who belong to distinct lowland indigenous groups and whose specific demands are often not addressed by government authorities.
Philipp Horn
wiley +1 more source
SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing [PDF]
Conference on Empirical Methods in Natural Language Processing, 2018 This paper describes SentencePiece, a language-independent subword tokenizer and detokenizer designed for Neural-based text processing, including Neural Machine Translation. It provides open-source C++ and Python implementations for subword units.
Taku Kudo, John Richardson
semanticscholar +1 more source