Results 261 to 270 of about 1,557,530 (322)

MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning

Annual Meeting of the Association for Computational Linguistics, 2023
Large language models (LLMs), despite their remarkable progress across various general domains, encounter significant barriers in medicine and healthcare.
Xiangru Tang, Anni Zou, Zhuosheng Zhang, Yilun Zhao, Xingyao Zhang, Arman Cohan, Mark B. Gerstein   +6 more
semanticscholar   +1 more source

Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels

North American Chapter of the Association for Computational Linguistics, 2023
Zero-shot text rankers powered by recent LLMs achieve remarkable ranking performance by simply prompting. Existing prompts for pointwise LLM rankers mostly ask the model to choose from binary relevance labels like “Yes” and “No”.
Honglei Zhuang, Zhen Qin, Kai Hui, Junru Wu, Le Yan, Xuanhui Wang, Michael Bendersky   +6 more
semanticscholar   +1 more source

The two-person and zero-sum matrix game with probabilistic linguistic information

Information Sciences, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mi, Xiaomei, Liao, Huchang, Zeng, Xiao-Jun, Xu, Zeshui   +3 more
openaire   +2 more sources

LLM Comparative Assessment: Zero-shot NLG Evaluation through Pairwise Comparisons using Large Language Models

Conference of the European Chapter of the Association for Computational Linguistics, 2023
Current developments in large language models (LLMs) have enabled impressive zero-shot capabilities across various natural language tasks. An interesting application of these systems is in the automated assessment of natural language generation (NLG), a ...
Adian Liusie, Potsawee Manakul, M. Gales
semanticscholar   +1 more source

VoiceCraft: Zero-Shot Speech Editing and Text-to-Speech in the Wild

Annual Meeting of the Association for Computational Linguistics
We introduce VoiceCraft, a token infilling neural codec language model, that achieves state-of-the-art performance on both speech editing and zero-shot text-to-speech (TTS) on audiobooks, internet videos, and podcasts.
Puyuan Peng, Po-Yao (Bernie) Huang, Shang-Wen Li, Abdelrahman Mohamed, David Harwath   +4 more
semanticscholar   +1 more source

LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models

North American Chapter of the Association for Computational Linguistics, 2023
Today’s large language models (LLMs) typically train on short text segments (e.g.,
Chi Han, Qifan Wang, Hao Peng, Wenhan Xiong, Yu Chen, Heng Ji, Sinong Wang   +6 more
semanticscholar   +1 more source

Teams of LLM Agents can Exploit Zero-Day Vulnerabilities

Conference of the European Chapter of the Association for Computational Linguistics
LLM agents have become increasingly sophisticated, especially in the realm of cybersecurity. Researchers have shown that LLM agents can exploit real-world vulnerabilities when given a description of the vulnerability and toy capture-the-flag problems ...
Richard Fang, R. Bindu, Akul Gupta, Qiusi Zhan, Daniel Kang   +4 more
semanticscholar   +1 more source

LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting

Annual Meeting of the Association for Computational Linguistics
Time-series forecasting (TSF) finds broad applications in real-world scenarios. Prompting off-the-shelf Large Language Models (LLMs) demonstrates strong zero-shot TSF capabilities while preserving computational efficiency.
Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, B. Prakash   +4 more
semanticscholar   +1 more source

GLiREL - Generalist Model for Zero-Shot Relation Extraction

North American Chapter of the Association for Computational Linguistics
We introduce GLiREL (Generalist Lightweight model for zero-shot Relation Extraction), an efficient architecture and training paradigm for zero-shot relation classification.
Jack Boylan, Chris Hokamp, D. Ghalandari
semanticscholar   +1 more source