Tong Xiang — accepted AI-conference papers

2024

Can Multiple-choice Questions Really Be Useful in Detecting the Abilities of LLMs?

Wangyue Li, Liangzhi Li, Tong Xiang, Xiao Liu, Wei Deng, Noa Garcia

COLING 2024main

Multiple-choice questions (MCQs) are widely used in the evaluation of large language models (LLMs) due to their simplicity and efficiency. However, there are concerns about whether MCQs can truly measure LLM’s capabilities, particularly in knowledge-intensive scenarios where long-form generation (LF…

Cited by 36 Source ↗PDF ↗code ↗Scholar ↗

2023

TCRA-LLM: Token Compression Retrieval Augmented Large Language Model for Inference Cost Reduction

Junyi Liu, Liangzhi Li, Tong Xiang, Bowen Wang, Yiming Qian

EMNLP 2023long findings

Since ChatGPT released its API for public use, the number of applications built on top of commercial large language models (LLMs) increase exponentially. One popular usage of such models is leveraging its in-context learning ability and generating responses given user queries leveraging knowledge ob…

Cited by 0 Source ↗Scholar ↗