James Y. Zhang

James Y. Zhang has 2 papers in our library, in 2023, most of them on Language models & pretraining, Reasoning; often with Xiaoming Shi, Chenhao Tan, Fan Zhou.

2 papers in our library · 2023

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Of its works in our library, with the number of works on each.

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Time-LLM: Time Series Forecasting by Reprogramming Large Language Models (2023 · 77 citations)
Forecasting models for time series are usually built for a single task or domain. Pre-trained foundation models for this data type are scarce because large training collections are lacking. Time-LLM tackles this by adapting an existing large language model to forecasting while leaving all of its weights frozen.
Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning (2023 · 44 citations)
The paper asks whether large language models can help forecast real-world events in time-stamped sequences, such as political interactions between G20 entities, where each event carries text like a news headline.

12 of 15 co-authors with a page, the most papers together first.

Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 101 times (of the 149,439 papers whose bibliographies we read); 12 citing papers with a page here →.

Updated 2 November 2026