20 citations · 40 across the 10 of their papers we have counts for
10 papers
On Reasoning Behind Next Occupation Recommendation
Shan Dong, Palakorn Achananuparp, Hieu Hien Mai +3
In this work, we develop a novel reasoning approach to enhance the performance of large language models (LLMs) in future occupation prediction. In this approach, a reason generator…
FedReFT: Federated Representation Fine-Tuning with All-But-Me Aggregation
Fatema Siddika, Md Anwar Hossen, J. Pablo Muñoz +3
Parameter-efficient fine-tuning (PEFT) adapts large pre-trained models by updating only a small subset of parameters. Recently, Representation Fine-Tuning (ReFT) has emerged as an…
MathHay: An Automated Benchmark for Long-Context Mathematical Reasoning in LLMs
Lei Wang, Shan Dong, Yuhui Xu +6
Recent large language models (LLMs) have demonstrated versatile capabilities in long-context scenarios. Although some recent benchmarks have been developed to evaluate the long-con…
All in an Aggregated Image for In-Image Learning
Lei Wang, Wanyu Xu, Zhiqiang Hu +5
This paper introduces a new in-context learning (ICL) mechanism called In-Image Learning (IL) that combines demonstration examples, visual cues, and chain-of-thought reasoning…
The Whole is Better than the Sum: Using Aggregated Demonstrations in In-Context Learning for Sequential Recommendation
Lei Wang, Ee-Peng Lim
Large language models (LLMs) have shown excellent performance on various NLP tasks. To use LLMs as strong sequential recommenders, we explore the in-context learning approach to se…
Mitigating Fine-Grained Hallucination by Fine-Tuning Large Vision-Language Models with Caption Rewrites
Lei Wang, Jiabang He, Shenshen Li +2
Large language models (LLMs) have shown remarkable performance in natural language processing (NLP) tasks. To comprehend and execute diverse human instructions over image data, ins…
LLM4Vis: Explainable Visualization Recommendation using ChatGPT
Lei Wang, Songheng Zhang, Yun Wang +2
Data visualization is a powerful tool for exploring and communicating insights in various domains. To automate visualization choice for datasets, a task known as visualization reco…
LLM-Based Agent Society Investigation: Collaboration and Confrontation in Avalon Gameplay
Yihuai Lan, Zhiqiang Hu, Lei Wang +6
This paper explores the open research problem of understanding the social behaviors of LLM-based agents. Using Avalon as a testbed, we employ system prompts to guide LLM agents in…
Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models
Lei Wang, Wanyu Xu, Yihuai Lan +4
Large language models (LLMs) have recently been shown to deliver impressive performance in various NLP tasks. To tackle multi-step reasoning tasks, few-shot chain-of-thought (CoT)…
LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models
Zhiqiang Hu, Lei Wang, Yihuai Lan +6
The success of large language models (LLMs), like GPT-4 and ChatGPT, has led to the development of numerous cost-effective and accessible alternatives that are created by finetunin…