11 citations · 14 across the 17 of their papers we have counts for
6 papers · 1 filter
Inductive-Deductive Strategy Reuse for Multi-Turn Instructional Dialogues
Jiao Ou, Jiayu Wu, Che Liu +3
Aligning large language models (LLMs) with human expectations requires high-quality instructional dialogues, which usually require instructions that are diverse and in-depth. Exist…
EVOR: Evolving Retrieval for Code Generation
Hongjin Su, Shuyang Jiang, Yuhang Lai +5
Recently the retrieval-augmented generation (RAG) has been successfully applied in code generation. However, existing pipelines for retrieval-augmented code generation (RACG) emplo…
Enhancing Role-playing Systems through Aggressive Queries: Evaluation and Improvement
Yihong Tang, Jiao Ou, Che Liu +3
The advent of Large Language Models (LLMs) has propelled dialogue generation into new realms, particularly in the field of role-playing systems (RPSs). While enhanced with ordinary…
DialogBench: Evaluating LLMs as Human-like Dialogue Systems
Jiao Ou, Junda Lu, Che Liu +4
Large language models (LLMs) have achieved remarkable breakthroughs in new dialogue capabilities by leveraging instruction tuning, which refreshes human impressions of dialogue sys…
OpenAgents: An Open Platform for Language Agents in the Wild
Tianbao Xie, Fan Zhou, Zhoujun Cheng +13
Language agents show potential in being capable of utilizing natural language for varied and intricate tasks in diverse environments, particularly when built upon large language mo…
Parrot: Enhancing Multi-Turn Instruction Following for Large Language Models
Yuchong Sun, Che Liu, Kun Zhou +6
Humans often interact with large language models (LLMs) in multi-turn interaction to obtain desired answers or more information. However, most existing studies overlook the multi-t…