activity
20142024
most citedChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate

56 citations · 210 across the 24 of their papers we have counts for

collaborators

24 papers

cs.CL2024

The Right Time Matters: Data Arrangement Affects Zero-Shot Generalization in Instruction Tuning

Bingxiang He, Ning Ding, Cheng Qian +10

Understanding alignment techniques begins with comprehending zero-shot generalization brought by instruction tuning, but little of the mechanism has been understood. Existing work…

cs.AI2024★ 7 cited

Scaling Large Language Model-based Multi-Agent Collaboration

Chen Qian, Zihao Xie, YiFei Wang +9

Recent breakthroughs in large language model-driven autonomous agents have revealed that multi-agent collaboration often surpasses each individual through collective reasoning. Ins…

cs.CL2024★ 3 cited

RLAIF-V: Open-Source AI Feedback Leads to Super GPT-4V Trustworthiness

Tianyu Yu, Haoye Zhang, Qiming Li +13

Traditional feedback learning for hallucination reduction relies on labor-intensive manual labeling or expensive proprietary models. This leaves the community without foundational…

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.CL2023

Experiential Co-Learning of Software-Developing Agents

Chen Qian, Yufan Dang, Jiahao Li +9

Recent advancements in large language models (LLMs) have brought significant changes to various domains, especially through LLM-driven autonomous agents. A representative scenario…

cs.HC2023★ 3 cited

Empowering Private Tutoring by Chaining Large Language Models

Yulin Chen, Ning Ding, Hai-Tao Zheng +3

Artificial intelligence has been applied in various aspects of online education to facilitate teaching and learning. However, few approaches has been made toward a complete AI-powe…