41 citations · 187 across the 25 of their papers we have counts for
26 papers
DeKeyNLU: Enhancing Natural Language to SQL Generation through Task Decomposition and Keyword Extraction
Jian Chen, Zhenyan Chen, Xuming Hu +7
Natural Language to SQL (NL2SQL) provides a new model-centric paradigm that simplifies database access for non-technical users by converting natural language queries into SQL comma…
Compliance-to-Code: Enhancing Financial Compliance Checking via Code Generation
Siyuan Li, Jian Chen, Rui Yao +8
Nowadays, regulatory compliance has become a cornerstone of corporate governance, ensuring adherence to systematic legal frameworks. At its core, financial regulations often compri…
BrowseComp-ZH: Benchmarking Web Browsing Ability of Large Language Models in Chinese
Peilin Zhou, Bruce Leon, Xiang Ying +13
As large language models (LLMs) evolve into tool-using agents, the ability to browse the web in real-time has become a critical yardstick for measuring their reasoning and retrieva…
FinTruthQA: A Benchmark for AI-Driven Financial Disclosure Quality Assessment in Investor -- Firm Interactions
Peilin Zhou, Ziyue Xu, Xinyu Shi +7
Accurate and transparent financial information disclosure is essential for market efficiency, investor decision-making, and corporate governance. Chinese stock exchanges' investor…
ClimateIQA: A New Dataset and Benchmark to Advance Vision-Language Models in Meteorology Anomalies Analysis
Jian Chen, Peilin Zhou, Yining Hua +7
Meteorological heatmaps play a vital role in deciphering extreme weather phenomena, yet their inherent complexities marked by irregular contours, unstructured patterns, and complex…
FinTextQA: A Dataset for Long-form Financial Question Answering
Jian Chen, Peilin Zhou, Yining Hua +5
Accurate evaluation of financial question answering (QA) systems necessitates a comprehensive dataset encompassing diverse question types and contexts. However, current financial Q…
Large Language Models in Mental Health Care: a Scoping Review
Yining Hua, Fenglin Liu, Kailai Yang +9
Objectieve:This review aims to deliver a comprehensive analysis of Large Language Models (LLMs) utilization in mental health care, evaluating their effectiveness, identifying chall…
Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case Study
Peilin Zhou, Meng Cao, You-Liang Huang +6
Large Multimodal Models (LMMs) have demonstrated impressive performance across various vision and language tasks, yet their potential applications in recommendation tasks with visu…
A Survey of Large Language Models in Medicine: Progress, Application, and Challenge
Hongjian Zhou, Fenglin Liu, Boyang Gu +16
Large language models (LLMs), such as ChatGPT, have received substantial attention due to their capabilities for understanding and generating human language. While there has been a…
Qilin-Med-VL: Towards Chinese Large Vision-Language Model for General Healthcare
Junling Liu, Ziming Wang, Qichen Ye +3
Large Language Models (LLMs) have introduced a new era of proficiency in comprehending complex healthcare and biomedical topics. However, there is a noticeable lack of models in la…
Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model
Qichen Ye, Junling Liu, Dading Chong +8
Integrating large language models (LLMs) into healthcare holds great potential but faces challenges. Pre-training LLMs from scratch for domains like medicine is resource-heavy and…
LLMRec: Benchmarking Large Language Models on Recommendation Task
Junling Liu, Chao Liu, Peilin Zhou +8
Recently, the fast development of Large Language Models (LLMs) such as ChatGPT has significantly advanced NLP tasks by enhancing the capabilities of conversational models. However,…
Attention Calibration for Transformer-based Sequential Recommendation
Peilin Zhou, Qichen Ye, Yueqi Xie +5
Transformer-based sequential recommendation (SR) has been booming in recent years, with the self-attention mechanism as its key component. Self-attention has been widely believed t…
Streamlining Social Media Information Retrieval for COVID-19 Research with Deep Learning
Yining Hua, Jiageng Wu, Shixu Lin +7
Objective: Social media-based public health research is crucial for epidemic surveillance, but most studies identify relevant corpora with keyword-matching. This study develops a s…
Benchmarking Large Language Models on CMExam -- A Comprehensive Chinese Medical Exam Dataset
Junling Liu, Peilin Zhou, Yining Hua +8
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the l…
Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems
Yueqi Xie, Jingqi Gao, Peilin Zhou +5
Existing research efforts for multi-interest candidate matching in recommender systems mainly focus on improving model architecture or incorporating additional information, neglect…
GreenPLM: Cross-Lingual Transfer of Monolingual Pre-Trained Language Models at Almost No Cost
Qingcheng Zeng, Lucas Garay, Peilin Zhou +7
Large pre-trained models have revolutionized natural language processing (NLP) research and applications, but high training costs and limited data resources have prevented their be…
Equivariant Contrastive Learning for Sequential Recommendation
Peilin Zhou, Jingqi Gao, Yueqi Xie +5
Contrastive learning (CL) benefits the training of sequential recommendation models with informative self-supervision signals. Existing solutions apply general sequential data augm…
METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweets
Peilin Zhou, Zeqiang Wang, Dading Chong +6
The COVID-19 pandemic continues to bring up various topics discussed or debated on social media. In order to explore the impact of pandemics on people's lives, it is crucial to und…
Low-resource Accent Classification in Geographically-proximate Settings: A Forensic and Sociophonetics Perspective
Qingcheng Zeng, Dading Chong, Peilin Zhou +1
Accented speech recognition and accent classification are relatively under-explored research areas in speech technology. Recently, deep learning-based methods and Transformer-based…
Calibrate and Refine! A Novel and Agile Framework for ASR-error Robust Intent Detection
Peilin Zhou, Dading Chong, Helin Wang +1
The past ten years have witnessed the rapid development of text-based intent detection, whose benchmark performances have already been taken to a remarkable level by deep learning…
Masked Spectrogram Prediction For Self-Supervised Audio Pre-Training
Dading Chong, Helin Wang, Peilin Zhou +1
Transformer-based models attain excellent results and generalize well when trained on sufficient amounts of data. However, constrained by the limited data available in the audio do…
Decoupled Side Information Fusion for Sequential Recommendation
Yueqi Xie, Peilin Zhou, Sunghun Kim
Side information fusion for sequential recommendation (SR) aims to effectively leverage various side information to enhance the performance of next-item prediction. Most state-of-t…
Joint Multiple Intent Detection and Slot Filling via Self-distillation
Lisong Chen, Peilin Zhou, Yuexian Zou
Intent detection and slot filling are two main tasks in natural language understanding (NLU) for identifying users' needs from their utterances. These two tasks are highly related…