3 citations · 7 across the 9 of their papers we have counts for
10 papers
MUSE: Benchmarking Assembly Structure and Interface Geometry in Multi-Component Text-to-CAD Generation
Xiaoyu Dong, Zhi Li, Zeng Chenbo +1
Large language models (LLMs) have recently advanced text-driven 3D generation, yet generating CAD models that satisfy practical design requirements remains challenging. Existing be…
Accelerating Generative Recommendation via Simple Categorical User Sequence Compression
Qijiong Liu, Lu Fan, Zhongzhou Liu +7
Although generative recommenders demonstrate improved performance with longer sequences, their real-time deployment is hindered by substantial computational costs. To address this…
AIMMerging: Adaptive Iterative Model Merging Using Training Trajectories for Language Model Continual Learning
Yujie Feng, Jian Li, Xiaoyu Dong +8
Continual learning (CL) is essential for deploying large language models (LLMs) in dynamic real-world environments without the need for costly retraining. Recent model merging-base…
Evaluating Recabilities of Foundation Models: A Multi-Domain, Multi-Dataset Benchmark
Qijiong Liu, Jieming Zhu, Yingxin Lai +5
Comprehensive evaluation of the recommendation capabilities of existing foundation models across diverse datasets and domains is essential for advancing the development of recommen…
Evaluating Conversational Recommender Systems via Large Language Models: A User-Centric Framework
Nuo Chen, Quanyu Dai, Xiaoyu Dong +5
Conversational recommender systems (CRSs) integrate both recommendation and dialogue tasks, making their evaluation uniquely challenging. Existing approaches primarily assess CRS p…
GEMeX: A Large-Scale, Groundable, and Explainable Medical VQA Benchmark for Chest X-ray Diagnosis
Bo Liu, Ke Zou, Liming Zhan +7
Medical Visual Question Answering (Med-VQA) combines computer vision and natural language processing to automatically answer clinical inquiries about medical images. However, curre…
AI Can Be Cognitively Biased: An Exploratory Study on Threshold Priming in LLM-Based Batch Relevance Assessment
Nuo Chen, Jiqun Liu, Xiaoyu Dong +3
Cognitive biases are systematic deviations in thinking that lead to irrational judgments and problematic decision-making, extensively studied across various fields. Recently, large…
Understanding Layer Significance in LLM Alignment
Guangyuan Shi, Zexin Lu, Xiaoyu Dong +4
Aligning large language models (LLMs) through supervised fine-tuning is essential for tailoring them to specific applications. Recent studies suggest that alignment primarily adjus…
Continual Dialogue State Tracking via Reason-of-Select Distillation
Yujie Feng, Bo Liu, Xiaoyu Dong +4
An ideal dialogue system requires continuous skill acquisition and adaptation to new tasks while retaining prior knowledge. Dialogue State Tracking (DST), vital in these systems, o…
Vector Quantization for Recommender Systems: A Review and Outlook
Qijiong Liu, Xiaoyu Dong, Jiaren Xiao +6
Vector quantization, renowned for its unparalleled feature compression capabilities, has been a prominent topic in signal processing and machine learning research for several decad…