1 citations · 1 across the 16 of their papers we have counts for
17 papers
Noisy Test-Time Reinforcement Learning for Code LLMs
Xikai Yang, Hieu Trung Nguyen, Dunyuan Xu +4
Large language models (LLMs) have demonstrated remarkable performance across various code-related tasks. However, unlike carefully curated datasets that are typically high-quality…
Revolutionizing Turn-by-Turn Navigation with Cloud-Edge Deep Learning
Yiming Yang, Hao Fu, Fanxiang Zeng +3
Turn-by-turn (TBT) navigation systems are integral to modern driving experiences, providing real-time audio instructions to guide drivers safely to destinations. However, existing…
What Process Evaluation of Coding Agents Actually Measures: Action, Task, and Step Are Three Different Levels
Jiawei He, Mengyu Shi, Jie jia +2
Coding agents are increasingly evaluated not only by whether they solve a task, but also by how they execute it. However, existing process-level evaluations often treat action pred…
DeepDiscovery: A Location-Inference Framework for Task-Level Repository Understanding
Jiawei He, Weisong Sun, Mengyu Shi +4
Large language models have shown strong performance on software engineering (SE) tasks, yet understanding large industrial repositories remains challenging. Existing methods often…
SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction
Jiawei He, Mengyu Shi, Jiawei Liu +6
Joint Entity and Relation Extraction (JERE) is highly sensitive to training data quality, making data augmentation a natural way to improve generalization. However, existing augmen…
ProcCtrlBench: Evaluating Process-Level Defects and Control Preservation in LLM Coding Agents
Jiawei He, Jie Jia, Chenbo Liu +4
Existing benchmarks for LLM coding agents primarily evaluate final outcomes. While useful for measuring overall capability, these metrics provide limited visibility and often miss…
SurgLQA: Scalable Long-Horizon Surgical Video Question Answering
Diandian Guo, Xikai Yang, Ruiyang Li +2
Surgical Video Question Answering (VideoQA) provides a promising paradigm for dynamic intraoperative interpretation, enabling real-time decision support and context-aware retrieval…
Med-Evo: Test-time Self-evolution for Medical Multimodal Large Language Models
Dunyuan Xu, Xikai Yang, Juzheng Miao +3
Medical Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across diverse healthcare tasks. However, current post-training strategies, such as super…
CaliCausalRank: Calibrated Multi-Objective Ad Ranking with Robust Counterfactual Utility Optimization
Xikai Yang, Sebastian Sun, Yilin Li +3
Ad ranking systems must simultaneously optimize multiple objectives including click-through rate (CTR), conversion rate (CVR), revenue, and user experience metrics. However, produc…
Semantics-Aware Denoising: A PLM-Guided Sample Reweighting Strategy for Robust Recommendation
Xikai Yang, Yang Wang, Yilin Li +1
Implicit feedback, such as user clicks, serves as the primary data source for modern recommender systems. However, click interactions inherently contain substantial noise, includin…
Perceive and Calibrate: Analyzing and Enhancing Robustness of Medical Multi-Modal Large Language Models
Dunyuan XU, Xikai Yang, Yaoqian Li +3
Medical Multi-modal Large Language Models (MLLMs) have shown promising clinical performance. However, their sensitivity to real-world input perturbations, such as imaging artifacts…
SurgPub-Video: A Comprehensive Surgical Video Dataset for Enhanced Surgical Intelligence in Vision-Language Model
Yaoqian Li, Xikai Yang, Dunyuan Xu +5
Vision-Language Models (VLMs) have shown significant potential in surgical scene analysis, yet existing models are limited by frame-level datasets and lack high-quality video data…
From Learning to Unlearning: Biomedical Security Protection in Multimodal Large Language Models
Dunyuan Xu, Xikai Yang, Yaoqian Li +2
The security of biomedical Multimodal Large Language Models (MLLMs) has attracted increasing attention. However, training samples easily contain private information and incorrect k…
Medical Large Vision Language Models with Multi-Image Visual Ability
Xikai Yang, Juzheng Miao, Yuchen Yuan +4
Medical large vision-language models (LVLMs) have demonstrated promising performance across various single-image question answering (QA) benchmarks, yet their capability in process…
Decoupling Feature Representations of Ego and Other Modalities for Incomplete Multi-modal Brain Tumor Segmentation
Kaixiang Yang, Wenqi Shan, Xudong Li +6
Multi-modal brain tumor segmentation typically involves four magnetic resonance imaging (MRI) modalities, while incomplete modalities significantly degrade performance. Existing so…
Multi-scale Spatio-temporal Transformer-based Imbalanced Longitudinal Learning for Glaucoma Forecasting from Irregular Time Series Images
Xikai Yang, Jian Wu, Xi Wang +3
Glaucoma is one of the major eye diseases that leads to progressive optic nerve fiber damage and irreversible blindness, afflicting millions of individuals. Glaucoma forecast is a…
CPSC: Conformal prediction with shrunken centroids for efficient prediction reliability quantification and data augmentation, a case in alternative herbal medicine classification with electronic nose
Li Liu, Xianghao Zhan, Xikai Yang +6
In machine learning applications, the reliability of predictions is significant for assisted decision and risk control. As an effective framework to quantify the prediction reliabi…