4 citations · 27 across the 34 of their papers we have counts for
35 papers
ProRetrieval: Learning to Orchestrate Hybrid Search via Executable Program Synthesis
Chengsong You, Zhen Sun, Yunhai Hu +17
Real-world retrieval often composes structured constraints with semantic intents over text and images through arbitrary Boolean logic. Existing hybrid pipelines such as reciprocal…
DocPC: Document-Level Visual Retrieval via Representative Page Composition
Chengsong You, Qiyi Jiang, Junwei Zhou +12
Visual document retrieval has advanced by encoding page screenshots with vision-language models, bypassing OCR pipelines. However, existing methods remain page-centric, misaligned…
Omni-Interactive Universal Embedder
Wei-Yao Wang, Kazuya Tateishi, Shuyang Cui +4
Multimodal representation learning has been shifting from traditional two-tower architectures to large language model (LLM)-based embedders due to their strong instruction-followin…
SF-Mamba: Rethinking State Space Model for Vision
Masakazu Yoshimura, Teruaki Hayashi, Yuki Hoshino +2
Visual Mamba models have recently emerged as alternatives to Vision Transformers (ViTs), which suffer from quadratic complexity. While the recurrent scanning mechanism of Mamba off…
Echoes Over Time: Unlocking Length Generalization in Video-to-Audio Generation Models
Christian Simon, Masato Ishii, Wei-Yao Wang +8
Scaling multimodal alignment between video and audio is challenging, particularly due to limited data and the mismatch between text descriptions and frame-level video information.…
MCA: Modality Composition Awareness for Robust Composed Multimodal Retrieval
Qiyu Wu, Shuyang Cui, Satoshi Hayakawa +3
Multimodal retrieval, which seeks to retrieve relevant content across modalities such as text or image, supports applications from AI search to contents production. Despite the suc…
WebGen-V Bench: Structured Representation for Enhancing Visual Design in LLM-based Web Generation and Evaluation
Kuang-Da Wang, Zhao Wang, Yotaro Shimose +2
Witnessed by the recent advancements on leveraging LLM for coding and multimodal understanding, we present WebGen-V, a new benchmark and framework for instruction-to-HTML generatio…
VIRTUE: Visual-Interactive Text-Image Universal Embedder
Wei-Yao Wang, Kazuya Tateishi, Qiyu Wu +2
Multimodal representation learning models have demonstrated successful operation across complex tasks, and the integration of vision-language models (VLMs) has further enabled embe…
Benchmarking Agentic Newswriting via Journalistic Workflows
Yen-Che Chien, Kuang-Da Wang, Wei-Yao Wang +1
Recent advances in autonomous digital agents from industry (e.g., Manus AI and Gemini's research mode) highlight their potential for structured tasks through autonomous decision-ma…
Mixture Experts with Test-Time Self-Supervised Aggregation for Tabular Imbalanced Regression
Yung-Chien Wang, Kuang-Da Wang, Wei-Yao Wang +1
Tabular data serve as a fundamental and ubiquitous representation of structured information in numerous real-world applications, e.g., finance and urban planning. In the realm of t…
Seeing is Understanding: Unlocking Causal Attention into Modality-Mutual Attention for Multimodal LLMs
Wei-Yao Wang, Zhao Wang, Helen Suzuki +1
Recent Multimodal Large Language Models (MLLMs) have demonstrated significant progress in perceiving and reasoning over multimodal inquiries, ushering in a new research era for fou…
Talk Structurally, Act Hierarchically: A Collaborative Framework for LLM Multi-Agent Systems
Zhao Wang, Sota Moriyama, Wei-Yao Wang +2
Recent advancements in LLM-based multi-agent (LLM-MA) systems have shown promise, yet significant challenges remain in managing communication and refinement when agents collaborate…
APAR: Modeling Irregular Target Functions in Tabular Regression via Arithmetic-Aware Pre-Training and Adaptive-Regularized Fine-Tuning
Hong-Wei Wu, Wei-Yao Wang, Kuang-Da Wang +1
Tabular data are fundamental in common machine learning applications, ranging from finance to genomics and healthcare. This paper focuses on tabular regression tasks, a field where…
Self-Supervised Learning of Disentangled Representations for Multivariate Time-Series
Ching Chang, Chiao-Tung Chan, Wei-Yao Wang +2
Multivariate time-series data in fields like healthcare and industry are informative but challenging due to high dimensionality and lack of labels. Recent self-supervised learning…
Offline Imitation of Badminton Player Behavior via Experiential Contexts and Brownian Motion
Kuang-Da Wang, Wei-Yao Wang, Ping-Chun Hsieh +1
In the dynamic and rapid tactic involvements of turn-based sports, badminton stands out as an intrinsic paradigm that requires alter-dependent decision-making of players. While the…
Root Cause Analysis In Microservice Using Neural Granger Causal Discovery
Cheng-Ming Lin, Ching Chang, Wei-Yao Wang +2
In recent years, microservices have gained widespread adoption in IT operations due to their scalability, maintenance, and flexibility. However, it becomes challenging for site rel…
A Survey on Self-Supervised Learning for Non-Sequential Tabular Data
Wei-Yao Wang, Wei-Wei Du, Derek Xu +2
Self-supervised learning (SSL) has been incorporated into many state-of-the-art models in various domains, where SSL defines pretext tasks based on unlabeled datasets to learn cont…
Style-News: Incorporating Stylized News Generation and Adversarial Verification for Neural Fake News Detection
Wei-Yao Wang, Yu-Chieh Chang, Wen-Chih Peng
With the improvements in generative models, the issues of producing hallucinations in various domains (e.g., law, writing) have been brought to people's attention due to concerns a…
ShuttleSHAP: A Turn-Based Feature Attribution Approach for Analyzing Forecasting Models in Badminton
Wei-Yao Wang, Wen-Chih Peng, Wei Wang +1
Agent forecasting systems have been explored to investigate agent patterns and improve decision-making in various domains, e.g., pedestrian predictions and marketing bidding. Badmi…
SeGA: Preference-Aware Self-Contrastive Learning with Prompts for Anomalous User Detection on Twitter
Ying-Ying Chang, Wei-Yao Wang, Wen-Chih Peng
In the dynamic and rapidly evolving world of social media, detecting anomalous users has become a crucial task to address malicious activities such as misinformation and cyberbully…
TimeDRL: Disentangled Representation Learning for Multivariate Time-Series
Ching Chang, Chiao-Tung Chan, Wei-Yao Wang +2
Multivariate time-series data in numerous real-world applications (e.g., healthcare and industry) are informative but challenging due to the lack of labels and high dimensionality.…
RSVP: Customer Intent Detection via Agent Response Contrastive and Generative Pre-Training
Yu-Chien Tang, Wei-Yao Wang, An-Zi Yen +1
The dialogue systems in customer services have been developed with neural models to provide users with precise answers and round-the-clock support in task-oriented conversations by…
DoRA: Domain-Based Self-Supervised Learning Framework for Low-Resource Real Estate Appraisal
Wei-Wei Du, Wei-Yao Wang, Wen-Chih Peng
The marketplace system connecting demands and supplies has been explored to develop unbiased decision-making in valuing properties. Real estate appraisal serves as one of the high-…
ShuttleSet: A Human-Annotated Stroke-Level Singles Dataset for Badminton Tactical Analysis
Wei-Yao Wang, Yung-Chang Huang, Tsi-Ui Ik +1
With the recent progress in sports analytics, deep learning approaches have demonstrated the effectiveness of mining insights into players' tactics for improving performance qualit…