Search Results for author: Xingxuan Li

Found 9 papers, 5 papers with code

ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?

no code implementations28 Nov 2023 Hailin Chen, Fangkai Jiao, Xingxuan Li, Chengwei Qin, Mathieu Ravaut, Ruochen Zhao, Caiming Xiong, Shafiq Joty

Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of AI, both in research and commerce.

Is GPT-4 a Good Data Analyst?

1 code implementation24 May 2023 Liying Cheng, Xingxuan Li, Lidong Bing

As large language models (LLMs) have demonstrated their powerful capabilities in plenty of domains and tasks, including context understanding, code generation, language generation, data storytelling, etc., many data analysts may raise concerns if their jobs will be replaced by artificial intelligence (AI).

Code Generation Text Generation

Unlocking Temporal Question Answering for Large Language Models Using Code Execution

1 code implementation24 May 2023 Xingxuan Li, Liying Cheng, Qingyu Tan, Hwee Tou Ng, Shafiq Joty, Lidong Bing

Our preliminary experiments show that generating intermediate reasoning steps does not always boost the performance of complex temporal question-answering tasks.

Logical Reasoning Question Answering

Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework

1 code implementation5 May 2023 Ruochen Zhao, Xingxuan Li, Shafiq Joty, Chengwei Qin, Lidong Bing

As large language models (LLMs) have become the norm in NLP, demonstrating good performance in generation and reasoning tasks, one of its most fatal disadvantages is the lack of factual correctness.

Open-Domain Question Answering

Retrieving Multimodal Information for Augmented Generation: A Survey

no code implementations20 Mar 2023 Ruochen Zhao, Hailin Chen, Weishi Wang, Fangkai Jiao, Xuan Long Do, Chengwei Qin, Bosheng Ding, Xiaobao Guo, Minzhi Li, Xingxuan Li, Shafiq Joty

As Large Language Models (LLMs) become popular, there emerged an important trend of using multimodality to augment the LLMs' generation ability, which enables LLMs to better interact with the world.


Does GPT-3 Demonstrate Psychopathy? Evaluating Large Language Models from a Psychological Perspective

no code implementations20 Dec 2022 Xingxuan Li, Yutong Li, Shafiq Joty, Linlin Liu, Fei Huang, Lin Qiu, Lidong Bing

On the basis of the findings, we recommended the application of more systematic and comprehensive psychological metrics to further evaluate and improve the safety of LLMs.

Towards Robust Low-Resource Fine-Tuning with Multi-View Compressed Representations

1 code implementation16 Nov 2022 Linlin Liu, Xingxuan Li, Megh Thakkar, Xin Li, Shafiq Joty, Luo Si, Lidong Bing

Due to the huge amount of parameters, fine-tuning of pretrained language models (PLMs) is prone to overfitting in the low resource scenarios.

YEDDA: A Lightweight Collaborative Text Span Annotation Tool

1 code implementation ACL 2018 Jie Yang, Yue Zhang, Linwei Li, Xingxuan Li

And the annotation time can be further compressed by 16. 47\% through intelligent recommendation.

text annotation

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