Papers by Wenjie Zhong
Agent Trading Arena: A Study on Numerical Understanding in LLM-Based Agents (2025.findings-emnlp)
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| Challenge: | Existing approaches to large language models are limited to historical backtesting and static data. |
| Approach: | a new large-language model is developed to simulate real-time trading in a virtual stock market . the agent trading arena simulates real-world bid-ask interactions and provides real-life trading scenarios . |
| Outcome: | The Agent Trading Arena simulates real-world market conditions and directly impacts price dynamics. |
Fiction-Writing Mode: An Effective Control for Human-Machine Collaborative Writing (2023.eacl-main)
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| Challenge: | Large-scale pre-trained language models (PLMs) have demonstrated an exceptional aptitude for generating text with an exceptional degree of fluency and structure. |
| Approach: | They propose to integrate writing skills curricula into human-machine collaborative writing scenarios by adding writing modes as a control for text generation models. |
| Outcome: | The proposed model can be used to generate narrative fiction with a high level of accuracy and similarity with the professionally written target story. |
Who Said What: Formalization and Benchmarks for the Task of Quote Attribution (2024.lrec-main)
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| Challenge: | Existing methods for quote attribution are poorly understood, despite advances in research . previous approaches have used hand-crafted features to identify speaker names . |
| Approach: | They formalize the task of quote attribution and establish a basis for comparison . they compare CEQA and ChatGPT models on available datasets in both English and Chinese . |
| Outcome: | The proposed model outperforms all supervised methods on English and Chinese datasets. |
Length Controlled Generation for Black-box LLMs (2025.acl-long)
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Yuxuan Gu, Wenjie Wang, Xiaocheng Feng, Weihong Zhong, Kun Zhu, Lei Huang, Ting Liu, Bing Qin, Tat-Seng Chua
| Challenge: | Existing length control methods involve fine-tuning the parameters of LLMs, which is inefficient and suboptimal for practical use. |
| Approach: | They propose an iterative sampling framework that regulates LLMs to generate length-constrained text without modifying the underlying parameters. |
| Outcome: | The proposed method achieves 100% success rates on Llama3.1 tasks with minimal additional computational overhead. |