Summary of Grounded Answers For Multi-agent Decision-making Problem Through Generative World Model, by Zeyang Liu et al.
Grounded Answers for Multi-agent Decision-making Problem through Generative World Modelby Zeyang Liu, Xinrui Yang, Shiguang…
Grounded Answers for Multi-agent Decision-making Problem through Generative World Modelby Zeyang Liu, Xinrui Yang, Shiguang…
Approximately Aligned Decodingby Daniel Melcer, Sujan Gonugondla, Pramuditha Perera, Haifeng Qian, Wen-Hao Chiang, Yanjun Wang,…
CONTESTS: a Framework for Consistency Testing of Span Probabilities in Language Modelsby Eitan Wagner, Yuli…
Model-based Preference Optimization in Abstractive Summarization without Human Feedbackby Jaepill Choi, Kyubyung Chae, Jiwoo Song,…
Scoring rule nets: beyond mean target prediction in multivariate regressionby Daan Roordink, Sibylle HessFirst submitted…
Fact Probability Vector Based Goal Recognitionby Nils Wilken, Lea Cohausz, Christian Bartelt, Heiner StuckenschmidtFirst submitted…
Understanding Epistemic Language with a Bayesian Theory of Mindby Lance Ying, Tan Zhi-Xuan, Lionel Wong,…
Probabilistic Medical Predictions of Large Language Modelsby Bowen Gu, Rishi J. Desai, Kueiyu Joshua Lin,…
Promoting Equality in Large Language Models: Identifying and Mitigating the Implicit Bias based on Bayesian…
Empathy Level Alignment via Reinforcement Learning for Empathetic Response Generationby Hui Ma, Bo Zhang, Bo…