3 citations · 8 across the 4 of their papers we have counts for
4 papers
See What LLMs Cannot Answer: A Self-Challenge Framework for Uncovering LLM Weaknesses
Yulong Chen, Yang Liu, Jianhao Yan +6
The impressive performance of Large Language Models (LLMs) has consistently surpassed numerous human-designed benchmarks, presenting new challenges in assessing the shortcomings of…
CoDi-2: In-Context, Interleaved, and Interactive Any-to-Any Generation
Zineng Tang, Ziyi Yang, Mahmoud Khademi +3
We present CoDi-2, a versatile and interactive Multimodal Large Language Model (MLLM) that can follow complex multimodal interleaved instructions, conduct in-context learning (ICL)…
Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models
Zhihan Zhang, Shuohang Wang, Wenhao Yu +6
Large language models (LLMs) can perform a wide range of tasks by following natural language instructions, without the necessity of task-specific fine-tuning. Unfortunately, the pe…
The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions
Siru Ouyang, Shuohang Wang, Yang Liu +7
Recent progress in Large Language Models (LLMs) has produced models that exhibit remarkable performance across a variety of NLP tasks. However, it remains unclear whether the exist…