activity
20232025
most citedYi: Open Foundation Models by 01.AI

47 citations · 88 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL2025

MCTS-KBQA: Monte Carlo Tree Search with Information Gain Rewards for Knowledge Base Question Answering

Guanming Xiong, Haochen Li, Zonghong Dai +2

This work investigates how to improve large language model (LLM)-based reasoning for knowledge base question answering (KBQA) via Monte Carlo Tree Search (MCTS). Applying MCTS to L…

cs.IR2024

Zero-Indexing Internet Search Augmented Generation for Large Language Models

Guangxin He, Zonghong Dai, Jiangcheng Zhu +6

Retrieval augmented generation has emerged as an effective method to enhance large language model performance. This approach typically relies on an internal retrieval module that u…

cs.CL2024★ 47 cited

Yi: Open Foundation Models by 01.AI

01. AI, :, Alex Young +30

We introduce the Yi model family, a series of language and multimodal models that demonstrate strong multi-dimensional capabilities. The Yi model family is based on 6B and 34B pret…

cs.HC2023★ 31 cited

The DiffuseStyleGesture+ entry to the GENEA Challenge 2023

Sicheng Yang, Haiwei Xue, Zhensong Zhang +5

In this paper, we introduce the DiffuseStyleGesture+, our solution for the Generation and Evaluation of Non-verbal Behavior for Embodied Agents (GENEA) Challenge 2023, which aims t…

cs.AI2023★ 2 cited

JiangJun: Mastering Xiangqi by Tackling Non-Transitivity in Two-Player Zero-Sum Games

Yang Li, Kun Xiong, Yingping Zhang +6

This paper presents an empirical exploration of non-transitivity in perfect-information games, specifically focusing on Xiangqi, a traditional Chinese board game comparable in game…

cs.LG2023★ 8 cited

An Empirical Study on Google Research Football Multi-agent Scenarios

Yan Song, He Jiang, Zheng Tian +6

Few multi-agent reinforcement learning (MARL) research on Google Research Football (GRF) focus on the 11v11 multi-agent full-game scenario and to the best of our knowledge, no open…