23 citations · 64 across the 22 of their papers we have counts for
13 papers · 1 filter
Quantifying Fairness in LLMs Beyond Tokens: A Semantic and Statistical Perspective
Weijie Xu, Yiwen Wang, Chi Xue +4
Large Language Models (LLMs) often generate responses with inherent biases, undermining their reliability in real-world applications. Existing evaluation methods often overlook bia…
SATA-BENCH: Select All That Apply Benchmark for Multiple Choice Questions
Weijie Xu, Shixian Cui, Xi Fang +3
Large language models (LLMs) are increasingly evaluated on single-answer multiple-choice tasks, yet many real-world problems require identifying all correct answers from a set of o…
FalseReject: A Resource for Improving Contextual Safety and Mitigating Over-Refusals in LLMs via Structured Reasoning
Zhehao Zhang, Weijie Xu, Fanyou Wu +1
Safety alignment approaches in large language models (LLMs) often lead to the over-refusal of benign queries, significantly diminishing their utility in sensitive scenarios. To add…
Neural Topic Modeling with Large Language Models in the Loop
Xiaohao Yang, He Zhao, Weijie Xu +4
Topic modeling is a fundamental task in natural language processing, allowing the discovery of latent thematic structures in text corpora. While Large Language Models (LLMs) have d…
HR-Agent: A Task-Oriented Dialogue (TOD) LLM Agent Tailored for HR Applications
Weijie Xu, Jay Desai, Fanyou Wu +2
Recent LLM (Large Language Models) advancements benefit many fields such as education and finance, but HR has hundreds of repetitive processes, such as access requests, medical cla…
Synthesizing Conversations from Unlabeled Documents using Automatic Response Segmentation
Fanyou Wu, Weijie Xu, Chandan K. Reddy +1
In this study, we tackle the challenge of inadequate and costly training data that has hindered the development of conversational question answering (ConvQA) systems. Enterprises h…
PHAnToM: Persona-based Prompting Has An Effect on Theory-of-Mind Reasoning in Large Language Models
Fiona Anting Tan, Gerard Christopher Yeo, Kokil Jaidka +6
The use of LLMs in natural language reasoning has shown mixed results, sometimes rivaling or even surpassing human performance in simpler classification tasks while struggling with…
Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey
Xi Fang, Weijie Xu, Fiona Anting Tan +7
Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, ta…
HR-MultiWOZ: A Task Oriented Dialogue (TOD) Dataset for HR LLM Agent
Weijie Xu, Zicheng Huang, Wenxiang Hu +5
Recent advancements in Large Language Models (LLMs) have been reshaping Natural Language Processing (NLP) task in several domains. Their use in the field of Human Resources (HR) ha…
Sequence-Level Certainty Reduces Hallucination In Knowledge-Grounded Dialogue Generation
Yixin Wan, Fanyou Wu, Weijie Xu +1
In this work, we propose sequence-level certainty as a common theme over hallucination in Knowledge Grounded Dialogue Generation (KGDG). We explore the correlation between the leve…
DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLM
Weijie Xu, Wenxiang Hu, Fanyou Wu +1
In the burgeoning field of natural language processing (NLP), Neural Topic Models (NTMs) , Large Language Models (LLMs) and Diffusion model have emerged as areas of significant res…
S2vNTM: Semi-supervised vMF Neural Topic Modeling
Weijie Xu, Jay Desai, Srinivasan Sengamedu +2
Language model based methods are powerful techniques for text classification. However, the models have several shortcomings. (1) It is difficult to integrate human knowledge such a…
KDSTM: Neural Semi-supervised Topic Modeling with Knowledge Distillation
Weijie Xu, Xiaoyu Jiang, Jay Desai +3
In text classification tasks, fine tuning pretrained language models like BERT and GPT-3 yields competitive accuracy; however, both methods require pretraining on large text datase…