1 code implementation • 13 Mar 2024 • Ruiyi Wang, Haofei Yu, Wenxin Zhang, Zhengyang Qi, Maarten Sap, Graham Neubig, Yonatan Bisk, Hao Zhu
Motivated by this gap, we propose an interactive learning method, SOTOPIA-$\pi$, improving the social intelligence of language agents.
no code implementations • 16 Nov 2023 • Haofei Yu, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency
Multimodal machine learning, which studies the information and interactions across various input modalities, has made significant advancements in understanding the relationship between images and descriptive text.
1 code implementation • 24 Oct 2023 • Haofei Yu, Cunxiang Wang, Yue Zhang, Wei Bi
The Transformer architecture is crucial for numerous AI models, but it still faces challenges in long-range language modeling.
no code implementations • 23 Oct 2023 • Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban, Anna Cai, Ritam Dutt, Amey Hengle, Anubha Kabra, Atharva Kulkarni, Abhishek Vijayakumar, Haofei Yu, Hinrich Schütze, Kemal Oflazer, David R. Mortensen
Large language models (LLMs) have recently reached an impressive level of linguistic capability, prompting comparisons with human language skills.
1 code implementation • 18 Oct 2023 • Xuhui Zhou, Hao Zhu, Leena Mathur, Ruohong Zhang, Haofei Yu, Zhengyang Qi, Louis-Philippe Morency, Yonatan Bisk, Daniel Fried, Graham Neubig, Maarten Sap
We present SOTOPIA, an open-ended environment to simulate complex social interactions between artificial agents and evaluate their social intelligence.
1 code implementation • 26 May 2023 • Cunxiang Wang, Haofei Yu, Yue Zhang
Open-Domain Question Answering (ODQA) systems necessitate a reader model capable of generating answers by simultaneously referring to multiple passages.
1 code implementation • 2 Jun 2021 • Chiyu Song, Hongliang He, Haofei Yu, Pengfei Fang, Leyang Cui, Zhenzhong Lan
The current state-of-the-art ranking methods mainly use an encoding paradigm called Cross-Encoder, which separately encodes each context-candidate pair and ranks the candidates according to their fitness scores.
Ranked #1 on Conversational Response Selection on Persona-Chat