collaborators

17 papers

cs.IR2026

MG-RAG: Multi-Granularity Graph for Multimodal Retrieval-Augmented Generation

Sijun Dai, Qiang Huang, Xiaoxing You +1

Retrieval-Augmented Generation (RAG) mitigates hallucinations in Multimodal Large Language Models (MLLMs), yet existing systems struggle with complex cross-modal reasoning. Flat ve…

cs.CL2026

One Interaction Is Worth a Thousand Guesses: Benchmarking the Interactive Capabilities of Deep Research Agents

Yingchaojie Feng, Qiang Huang, Xiaoya Xie +4

Deep research agents powered by Large Language Models (LLMs) can perform multi-step reasoning, web exploration, and long-form report generation. However, existing systems remain la…

cs.CL2026

Position: Text Embeddings Should Capture Implicit Semantics, Not Just Surface Meaning

Yiqun Sun, Qiang Huang, Anthony K. H. Tung +1

This position paper argues that text embedding research should move beyond surface meaning and embrace implicit semantics as a central modeling objective. Text embeddings are a fou…

cs.CV2026

Measuring Social Bias in Vision-Language Models with Face-Only Counterfactuals from Real Photos

Haodong Chen, Qiang Huang, Jiaqi Zhao +3

Vision-Language Models (VLMs) are increasingly deployed in socially consequential settings, raising concerns about social bias driven by demographic cues. A central challenge in me…

cs.LG2026

Weight-Informed Self-Explaining Clustering for Mixed-Type Tabular Data

Lehao Li, Qiang Huang, Yihao Ang +3

Clustering mixed-type tabular data is fundamental for exploratory analysis, yet remains challenging due to misaligned numerical-categorical representations, uneven and context-depe…

cs.CV2026

Cut to the Chase: Training-free Multimodal Summarization via Chain-of-Events

Xiaoxing You, Qiang Huang, Lingyu Li +2

Multimodal Summarization (MMS) aims to generate concise textual summaries by understanding and integrating information across videos, transcripts, and images. However, existing app…