Publications (88)
Towards Understanding Fine-Tuning Mechanisms of LLMs via Circuit Analysis
Xu Wang, Yan Hu, Wenyu Du +3
Fine-tuning significantly improves the performance of Large Language Models (LLMs), yet its underlying mechanisms remain poorly understood. This paper aims to provide an in-depth i…
Memory-Augmented Multimodal LLMs for Surgical VQA via Self-Contained Inquiry
Wenjun Hou, Yi Cheng, Kaishuai Xu +3
Comprehensively understanding surgical scenes in Surgical Visual Question Answering (Surgical VQA) requires reasoning over multiple objects. Previous approaches address this task u…
Degradation-invariant Enhancement of Fundus Images via Pyramid Constraint Network
Haofeng Liu, Heng Li, Huazhu Fu +4
As an economical and efficient fundus imaging modality, retinal fundus images have been widely adopted in clinical fundus examination. Unfortunately, fundus images often suffer fro…
Apollo: A Lightweight Multilingual Medical LLM towards Democratizing Medical AI to 6B People
Xidong Wang, Nuo Chen, Junyin Chen +9
Despite the vast repository of global medical knowledge predominantly being in English, local languages are crucial for delivering tailored healthcare services, particularly in are…
GARI: Graph Attention for Relative Isomorphism of Arabic Word Embeddings
Muhammad Asif Ali, Maha Alshmrani, Jianbin Qin +2
Bilingual Lexical Induction (BLI) is a core challenge in NLP, it relies on the relative isomorphism of individual embedding spaces. Existing attempts aimed at controlling the relat…
Mamba Hawkes Process
Anningzhe Gao, Shan Dai, Yan Hu
Irregular and asynchronous event sequences are prevalent in many domains, such as social media, finance, and healthcare. Traditional temporal point processes (TPPs), like Hawkes pr…
The structure of deformed double complexes on the Iwasawa manifold
Yan Hu, Wei Xia
The Kuranishi family of the Iwasawa manifold give rise naturally to a family of (deformed) double complexes. By using the structure theorem of double complexes due to Stelzig and Q…
Toward Federated Large Language Models in Medicine: A Parameter-Efficient Framework for Privacy-Preserving, Multi-Institutional Adaptation
Anran Li, Yuanyuan Chen, Wenjun Long +16
Large language models (LLMs) are increasingly adapted for medical applications, but most are trained using data from a single institution because privacy and governance constraints…
High signal-to-noise ratio reconstruction of low bit-depth optical coherence tomography using deep learning
Qiangjiang Hao, Kang Zhou, Jianlong Yang +6
Reducing the bit-depth is an effective approach to lower the cost of optical coherence tomography (OCT) systems and increase the transmission efficiency in data acquisition and tel…
Deformed Aeppli cohomology: canonical deformations and jumping formulas
Yan Hu, Wei Xia
Given a complex analytic family of complex manifolds, we consider canonical Aeppli deformations of -forms and study its relations to the varying of dimension of the deformed…
Multi-Label Classification with Generative AI Models in Healthcare: A Case Study of Suicidality and Risk Factors
Ming Huang, Zehan Li, Yan Hu +9
Suicide remains a pressing global health crisis, with over 720,000 deaths annually and millions more affected by suicide ideation (SI) and suicide attempts (SA). Early identificati…
Can LLM Agents Generate Real-World Evidence? Evaluating Observational Studies in Medical Databases
Dubai Li, Yuxiang He, Yan Hu +2
Observational studies can yield clinically actionable evidence at scale, but executing them on real-world databases is open-ended and requires coherent decisions across cohort cons…
SuperVessel: Segmenting High-resolution Vessel from Low-resolution Retinal Image
Yan Hu, Zhongxi Qiu, Dan Zeng +3
Vascular segmentation extracts blood vessels from images and serves as the basis for diagnosing various diseases, like ophthalmic diseases. Ophthalmologists often require high-reso…
Towards the Law of Capacity Gap in Distilling Language Models
Chen Zhang, Qiuchi Li, Dawei Song +3
Language model (LM) distillation aims at distilling the knowledge in a large teacher LM to a small student one. As a critical issue facing LM distillation, a superior student often…
PrinciplismQA: A Philosophy-Grounded Approach to Assessing LLM-Human Clinical Medical Ethics Alignment
Chang Hong, Minghao Wu, Qingying Xiao +5
As medical LLMs transition to clinical deployment, assessing their ethical reasoning capability becomes critical. While achieving high accuracy on knowledge benchmarks, LLMs lack v…
BlueLM-2.5-3B Technical Report
Baojiao Xiong, Boheng Chen, Chengzhi Wang +58
We present BlueLM-2.5-3B, a compact and unified dense Multimodal Large Language Model (MLLM) designed for efficient edge-device deployment, offering strong general-purpose and reas…
Frequency-mixed Single-source Domain Generalization for Medical Image Segmentation
Heng Li, Haojin Li, Wei Zhao +4
The annotation scarcity of medical image segmentation poses challenges in collecting sufficient training data for deep learning models. Specifically, models trained on limited data…
Structure-consistent Restoration Network for Cataract Fundus Image Enhancement
Heng Li, Haofeng Liu, Huazhu Fu +5
Fundus photography is a routine examination in clinics to diagnose and monitor ocular diseases. However, for cataract patients, the fundus image always suffers quality degradation…
Hard Exudate Segmentation Supplemented by Super-Resolution with Multi-scale Attention Fusion Module
Jiayi Zhang, Xiaoshan Chen, Zhongxi Qiu +3
Hard exudates (HE) is the most specific biomarker for retina edema. Precise HE segmentation is vital for disease diagnosis and treatment, but automatic segmentation is challenged b…
An Annotation-free Restoration Network for Cataractous Fundus Images
Heng Li, Haofeng Liu, Yan Hu +4
Cataracts are the leading cause of vision loss worldwide. Restoration algorithms are developed to improve the readability of cataract fundus images in order to increase the certain…
Microscopic 3D measurement of shiny surfaces based on a multi-frequency phase-shifting scheme
Yan Hu, Qian Chen, Yichao Liang +3
Microscopic fringe projection profilometry is a powerful 3D measurement technique with a theoretical measurement accuracy better than one micron provided that the measured targets…
Suicide Phenotyping from Clinical Notes in Safety-Net Psychiatric Hospital Using Multi-Label Classification with Pre-Trained Language Models
Zehan Li, Yan Hu, Scott Lane +7
Accurate identification and categorization of suicidal events can yield better suicide precautions, reducing operational burden, and improving care quality in high-acuity psychiatr…
Learnable Ophthalmology SAM
Zhongxi Qiu, Yan Hu, Heng Li +1
Segmentation is vital for ophthalmology image analysis. But its various modal images hinder most of the existing segmentation algorithms applications, as they rely on training base…
Hierarchical Context Transformer for Multi-level Semantic Scene Understanding
Luoying Hao, Yan Hu, Yang Yue +4
A comprehensive and explicit understanding of surgical scenes plays a vital role in developing context-aware computer-assisted systems in the operating theatre. However, few works…
Adaptive Wavelet Filters as Practical Texture Feature Amplifiers for Parkinson's Disease Screening in OCT
Xiaoqing Zhang, Hanfeng Shi, Xiangyu Li +7
Parkinson's disease (PD) is a prevalent neurodegenerative disorder globally. The eye's retina is an extension of the brain and has great potential in PD screening. Recent studies h…
LLMs for Mathematical Modeling: Towards Bridging the Gap between Natural and Mathematical Languages
Xuhan Huang, Qingning Shen, Yan Hu +2
Large Language Models (LLMs) have demonstrated strong performance across various natural language processing tasks, yet their proficiency in mathematical reasoning remains a key ch…
Probabilistic Latent Factor Model for Collaborative Filtering with Bayesian Inference
Jiansheng Fang, Xiaoqing Zhang, Yan Hu +3
Latent Factor Model (LFM) is one of the most successful methods for Collaborative filtering (CF) in the recommendation system, in which both users and items are projected into a jo…
Deep learning enables extraction of capillary-level angiograms from single OCT volume
Jianlong Yang, Peng Liu, Lixin Duan +2
Optical coherence tomography angiography (OCTA) has drawn numerous attentions in ophthalmology. However, its data acquisition is time-consuming, because it is based on temporal-dec…
Pyramid Pixel Context Adaption Network for Medical Image Classification with Supervised Contrastive Learning
Xiaoqing Zhang, Zunjie Xiao, Xiao Wu +4
Spatial attention mechanism has been widely incorporated into deep neural networks (DNNs), significantly lifting the performance in computer vision tasks via long-range dependency…
Improving Large Language Models for Clinical Named Entity Recognition via Prompt Engineering
Yan Hu, Qingyu Chen, Jingcheng Du +9
Objective: This study quantifies the capabilities of GPT-3.5 and GPT-4 for clinical named entity recognition (NER) tasks and proposes task-specific prompts to improve their perform…
Automatic Segmentation and Visualization of Choroid in OCT with Knowledge Infused Deep Learning
Huihong Zhang, Jianlong Yang, Kang Zhou +6
The choroid provides oxygen and nourishment to the outer retina thus is related to the pathology of various ocular diseases. Optical coherence tomography (OCT) is advantageous in v…
Instrument-tissue Interaction Detection Framework for Surgical Video Understanding
Wenjun Lin, Yan Hu, Huazhu Fu +5
Instrument-tissue interaction detection task, which helps understand surgical activities, is vital for constructing computer-assisted surgery systems but with many challenges. Firs…
Universal digital filtering for denoising volumetric retinal OCT and OCT angiography in 3D shearlet domain
Jianlong Yang, Yan Hu, Liyang Fang +2
Retinal optical coherence tomography (OCT) and OCT angiography (OCTA) suffer from the degeneration of image quality due to speckle noise and bulk-motion noise, respectively. Becaus…
Eye-Tracking, Mouse Tracking, Stimulus Tracking,and Decision-Making Datasets in Digital Pathology
Veronica Thai, Rui Li, Meng Ling +7
Interpretation of giga-pixel whole-slide images (WSIs) is an important but difficult task for pathologists. Their diagnostic accuracy is estimated to average around 70%. Adding a s…
SHAP-Integrated Convolutional Diagnostic Networks for Feature-Selective Medical Analysis
Yan Hu, Ahmad Chaddad
This study introduces the SHAP-integrated convolutional diagnostic network (SICDN), an interpretable feature selection method designed for limited datasets, to address the challeng…
Identifying and Extracting Rare Disease Phenotypes with Large Language Models
Cathy Shyr, Yan Hu, Paul A. Harris +1
Rare diseases (RDs) are collectively common and affect 300 million people worldwide. Accurate phenotyping is critical for informing diagnosis and treatment, but RD phenotypes are o…
A Span-based Model for Extracting Overlapping PICO Entities from RCT Publications
Gongbo Zhang, Yiliang Zhou, Yan Hu +3
Objectives Extraction of PICO (Populations, Interventions, Comparison, and Outcomes) entities is fundamental to evidence retrieval. We present a novel method PICOX to extract overl…
Does higher interpretability imply better utility? A Pairwise Analysis on Sparse Autoencoders
Xu Wang, Yan Hu, Benyou Wang +1
Sparse Autoencoders (SAEs) are widely used to steer large language models (LLMs), based on the assumption that their interpretable features naturally enable effective model behavio…
Approximating the Backbone in the Weighted Maximum Satisfiability Problem
He Jiang, Jifeng Xuan, Yan Hu
The weighted Maximum Satisfiability problem (weighted MAX-SAT) is a NP-hard problem with numerous applications arising in artificial intelligence. As an efficient tool for heuristi…
ICON: Improving Inter-Report Consistency in Radiology Report Generation via Lesion-aware Mixup Augmentation
Wenjun Hou, Yi Cheng, Kaishuai Xu +3
Previous research on radiology report generation has made significant progress in terms of increasing the clinical accuracy of generated reports. In this paper, we emphasize anothe…
Concealed Object Detection for Passive Millimeter-Wave Security Imaging Based on Task-Aligned Detection Transformer
Cheng Guo, Fei Hu, Yan Hu
Passive millimeter-wave (PMMW) is a significant potential technique for human security screening. Several popular object detection networks have been used for PMMW images. However,…
A systematic literature review of cloud computing in eHealth
Yan Hu, Guohua Bai
Cloud computing in eHealth is an emerging area for only few years. There needs to identify the state of the art and pinpoint challenges and possible directions for researchers and…
An artificial intelligence framework for end-to-end rare disease phenotyping from clinical notes using large language models
Cathy Shyr, Yan Hu, Rory J. Tinker +8
Phenotyping is fundamental to rare disease diagnosis, but manual curation of structured phenotypes from clinical notes is labor-intensive and difficult to scale. Existing artificia…
Information Extraction from Clinical Notes: Are We Ready to Switch to Large Language Models?
Yan Hu, Xu Zuo, Yujia Zhou +9
Backgrounds: Information extraction (IE) is critical in clinical natural language processing (NLP). While large language models (LLMs) excel on generative tasks, their performance…
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas, Mauricio Reyes, Andras Jakab +421
Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritum…
A Random Walk Based Algorithm for Structural Test Case Generation
Jifeng Xuan, He Jiang, Zhilei Ren +2
Structural testing is a significant and expensive process in software development. By converting test data generation into an optimization problem, search-based software testing is…
Deep-learning-enabled geometric constraints and phase unwrapping for single-shot absolute 3D shape measurement
Jiaming Qian, Shijie Feng, Tianyang Tao +4
Fringe projection profilometry (FPP) is one of the most popular three-dimensional (3D) shape measurement techniques, and has becoming more prevalently adopted in intelligent manufa…
Open-Medical-R1: How to Choose Data for RLVR Training at Medicine Domain
Zhongxi Qiu, Zhang Zhang, Yan Hu +2
This paper explores optimal data selection strategies for Reinforcement Learning with Verified Rewards (RLVR) training in the medical domain. While RLVR has shown exceptional poten…
MedPMC: A Systematic Framework for Scaling High-Fidelity Medical Multimodal Data for Foundation Models
Hyunjae Kim, Dain Kim, Pan Xiao +25
Medicine is inherently multimodal, requiring clinicians to synthesize information across diverse data streams. Yet the development of multimodal foundation models is constrained by…
Can Multimodal LLMs See Materials Clearly? A Multimodal Benchmark on Materials Characterization
Zhengzhao Lai, Youbin Zheng, Zhenyang Cai +5
Materials characterization is fundamental to acquiring materials information, revealing the processing-microstructure-property relationships that guide material design and optimiza…
ACT-Net: Anchor-context Action Detection in Surgery Videos
Luoying Hao, Yan Hu, Wenjun Lin +5
Recognition and localization of surgical detailed actions is an essential component of developing a context-aware decision support system. However, most existing detection algorith…
Debt-Prone Bugs: Technical Debt in Software Maintenance
Jifeng Xuan, Yan Hu, He Jiang
Fixing bugs is an important phase in software development and maintenance. In practice, the process of bug fixing may conflict with the release schedule. Such confliction leads to…
Model Unlearning via Sparse Autoencoder Subspace Guided Projections
Xu Wang, Zihao Li, Benyou Wang +2
Large language models (LLMs) store vast amounts of information, making them powerful yet raising privacy and safety concerns when selective knowledge removal is required. Existing…
COph100: A comprehensive fundus image registration dataset from infants constituting the "RIDIRP" database
Yan Hu, Mingdao Gong, Zhongxi Qiu +7
Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on adult retinal pathologies with…
GRI: Graph-based Relative Isomorphism of Word Embedding Spaces
Muhammad Asif Ali, Yan Hu, Jianbin Qin +1
Automated construction of bilingual dictionaries using monolingual embedding spaces is a core challenge in machine translation. The end performance of these dictionaries relies upo…
Fringe pattern analysis using deep learning
Shijie Feng, Qian Chen, Guohua Gu +5
In many optical metrology techniques, fringe pattern analysis is the central algorithm for recovering the underlying phase distribution from the recorded fringe patterns. Despite e…
VSR-Net: Vessel-like Structure Rehabilitation Network with Graph Clustering
Haili Ye, Xiaoqing Zhang, Yan Hu +2
The morphologies of vessel-like structures, such as blood vessels and nerve fibres, play significant roles in disease diagnosis, e.g., Parkinson's disease. Deep network-based refin…
3D Vessel Reconstruction in OCT-Angiography via Depth Map Estimation
Shuai Yu, Jianyang Xie, Jinkui Hao +5
Optical Coherence Tomography Angiography (OCTA) has been increasingly used in the management of eye and systemic diseases in recent years. Manual or automatic analysis of blood ves…
Rationality of Darmon points over genus fields of non-maximal orders
Matteo Longo, Kimball Martin, Yan Hu
Stark-Heegner points, also known as Darmon points, were introduced by H. Darmon as certain local points on rational elliptic curves, conjecturally defined over abelian extensions o…
RADAR: Enhancing Radiology Report Generation with Supplementary Knowledge Injection
Wenjun Hou, Yi Cheng, Kaishuai Xu +4
Large language models (LLMs) have demonstrated remarkable capabilities in various domains, including radiology report generation. Previous approaches have attempted to utilize mult…
Reconstruction and Quantification of 3D Iris Surface for Angle-Closure Glaucoma Detection in Anterior Segment OCT
Jinkui Hao, Huazhu Fu, Yanwu Xu +5
Precise characterization and analysis of iris shape from Anterior Segment OCT (AS-OCT) are of great importance in facilitating diagnosis of angle-closure-related diseases. Existing…
Learning to Select, Not Relearn: Hard-Routed Mixtures of Reasoning LoRAs
Seyed Alireza Molavi, Zhan Su, Yan Hu +3
Composing independently trained LoRA adapters into a single large language model is useful for multi-domain adaptation, especially when the original training data cannot be shared.…
Attention-based Saliency Hashing for Ophthalmic Image Retrieval
Jiansheng Fang, Yanwu Xu, Xiaoqing Zhang +2
Deep hashing methods have been proved to be effective for the large-scale medical image search assisting reference-based diagnosis for clinicians. However, when the salient region…
A Hybrid ACO Algorithm for the Next Release Problem
He Jiang, Jingyuan Zhang, Jifeng Xuan +2
In this paper, we propose a Hybrid Ant Colony Optimization algorithm (HACO) for Next Release Problem (NRP). NRP, a NP-hard problem in requirement engineering, is to balance custome…
Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implications
Anran Li, Lingfei Qian, Mengmeng Du +18
Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pre-training or fine-tuning on medical data to e…
Eliminating Shadow Artifacts via Generative Inpainting Networks to Quantify Vascular Changes of the Choroid
Huihong Zhang, Jianlong Yang, Kang Zhou +5
Shadow artifacts from retinal vessels hinder the development of quantitative choroidal biomarkers in Optical Coherence Tomography (OCT), which limits the clinical applications of t…
CDEMapper: Enhancing NIH Common Data Element Normalization using Large Language Models
Yan Wang, Jimin Huang, Huan He +13
Common Data Elements (CDEs) standardize data collection and sharing across studies, enhancing data interoperability and improving research reproducibility. However, implementing CD…
Machine Learning for Cataract Classification and Grading on Ophthalmic Imaging Modalities: A Survey
Xiaoqing Zhang, Yan Hu, Zunjie Xiao +3
Cataracts are the leading cause of visual impairment and blindness globally. Over the years, researchers have achieved significant progress in developing state-of-the-art machine l…
Benchmarking large language models for biomedical natural language processing applications and recommendations
Qingyu Chen, Yan Hu, Xueqing Peng +18
The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While…
Towards Effective Bug Triage with Towards Effective Bug Triage with Software Data Reduction Techniques
Jifeng Xuan, He Jiang, Yan Hu +4
Software companies spend over 45 percent of cost in dealing with software bugs. An inevitable step of fixing bugs is bug triage, which aims to correctly assign a developer to a new…
Federated Linear Dueling Bandits
Xuhan Huang, Yan Hu, Zhiyan Li +3
Contextual linear dueling bandits have recently garnered significant attention due to their widespread applications in important domains such as recommender systems and large langu…
BlueLM-V-3B: Algorithm and System Co-Design for Multimodal Large Language Models on Mobile Devices
Xudong Lu, Yinghao Chen, Cheng Chen +19
The emergence and growing popularity of multimodal large language models (MLLMs) have significant potential to enhance various aspects of daily life, from improving communication t…
Metasurface Sensing Approach to DOA Estimation of Coherent Signals
Yishuo Zhao, Yan Hu, Yougen Xu
The DOA estimation method of coherent signals based on periodical coding metasurface is proposed. After periodical coding, the DOA information of incident signals in the time domai…
Generalizable and Explainable Deep Learning for Medical Image Computing: An Overview
Ahmad Chaddad, Yan Hu, Yihang Wu +2
Objective. This paper presents an overview of generalizable and explainable artificial intelligence (XAI) in deep learning (DL) for medical imaging, aimed at addressing the urgent…
Do LLMs Triage Like Clinicians? A Dynamic Study of Outpatient Referral
Xiaoxiao Liu, Qingying Xiao, Bingquan Zhang +8
Outpatient referral (OR) is a core clinical workflow that assigns patients to hospital departments under incomplete and evolving information, yet it is commonly simplified as a sta…
Exploring Large Language Models in Healthcare: Insights into Corpora Sources, Customization Strategies, and Evaluation Metrics
Shuqi Yang, Mingrui Jing, Shuai Wang +5
This study reviewed the use of Large Language Models (LLMs) in healthcare, focusing on their training corpora, customization techniques, and evaluation metrics. A systematic search…
Open-Vocabulary Spatio-Temporal Scene Graph for Robot Perception and Teleoperation Planning
Yi Wang, Zeyu Xue, Mujie Liu +5
Teleoperation via natural-language reduces operator workload and enhances safety in high-risk or remote settings. However, in dynamic remote scenes, transmission latency during bid…
Medical Image Registration and Its Application in Retinal Images: A Review
Qiushi Nie, Xiaoqing Zhang, Yan Hu +2
Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse information of images, which may be captured under different times, angles…
TwinMarket: A Scalable Behavioral and Social Simulation for Financial Markets
Yuzhe Yang, Yifei Zhang, Minghao Wu +5
The study of social emergence has long been a central focus in social science. Traditional modeling approaches, such as rule-based Agent-Based Models (ABMs), struggle to capture th…
Me LLaMA: Foundation Large Language Models for Medical Applications
Qianqian Xie, Qingyu Chen, Aokun Chen +15
Recent advancements in large language models (LLMs) like ChatGPT and LLaMA show promise in medical applications, yet challenges remain in medical language comprehension. This study…
Label-noise-tolerant medical image classification via self-attention and self-supervised learning
Hongyang Jiang, Mengdi Gao, Yan Hu +3
Deep neural networks (DNNs) have been widely applied in medical image classification and achieve remarkable classification performance. These achievements heavily depend on large-s…
Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image Enhancement
Heng Li, Ziqin Lin, Zhongxi Qiu +4
Medical imaging provides many valuable clues involving anatomical structure and pathological characteristics. However, image degradation is a common issue in clinical practice, whi…
Digital resolution enhancement in low transverse sampling optical coherence tomography angiography using deep learning
Ting Zhou, Kang Zhou, Jianlong Yang +7
Optical coherence tomography angiography (OCTA) requires high transverse sampling density for visualizing retinal and choroidal capillaries. Low transverse sampling causes resoluti…
Towards Training Set Reduction for Bug Triage
Weiqin Zou, Yan Hu, Jifeng Xuan +1
Bug triage is an important step in the process of bug fixing. The goal of bug triage is to assign a new-coming bug to the correct potential developer. The existing bug triage appro…
A Generic Fundus Image Enhancement Network Boosted by Frequency Self-supervised Representation Learning
Heng Li, Haofeng Liu, Huazhu Fu +5
Fundus photography is prone to suffer from image quality degradation that impacts clinical examination performed by ophthalmologists or intelligent systems. Though enhancement algo…
Antonym vs Synonym Distinction using InterlaCed Encoder NETworks (ICE-NET)
Muhammad Asif Ali, Yan Hu, Jianbin Qin +1
Antonyms vs synonyms distinction is a core challenge in lexico-semantic analysis and automated lexical resource construction. These pairs share a similar distributional context whi…
UCFE: A User-Centric Financial Expertise Benchmark for Large Language Models
Yuzhe Yang, Yifei Zhang, Yan Hu +10
This paper introduces the UCFE: User-Centric Financial Expertise benchmark, an innovative framework designed to evaluate the ability of large language models (LLMs) to handle compl…
BlenderLLM: Training Large Language Models for Computer-Aided Design with Self-improvement
Yuhao Du, Shunian Chen, Wenbo Zan +6
The application of Large Language Models (LLMs) in Computer-Aided Design (CAD) remains an underexplored area, despite their remarkable advancements in other domains. In this paper,…