collaborators

5 papers

cs.LG2026

Bayesian Data Reweighting Improves Multimodal Retrieval for Knowledge-Based Visual Question Answering

Jingchen Sun, Shaobo Han, Ruiyi Zhang +5

Multimodal retrievers are essential for knowledge-based visual question answering, where they retrieve external evidence for image-question pairs. However, existing contrastive tra…

cs.CV2026

SimpleOCR: Rendering Visualized Questions to Teach MLLMs to Read

Yibo Peng, Peng Xia, Ding Zhong +6

Despite the rapid advancements in Multimodal Large Language Models (MLLMs), a critical question regarding their visual grounding mechanism remains unanswered: do these models genui…

cs.CL2026

Reasoning-Based Personalized Generation for Users with Sparse Data

Bo Ni, Branislav Kveton, Samyadeep Basu +14

Large Language Model (LLM) personalization holds great promise for tailoring responses by leveraging personal context and history. However, real-world users usually possess sparse…

cs.CV2025

VisR-Bench: An Empirical Study on Visual Retrieval-Augmented Generation for Multilingual Long Document Understanding

Jian Chen, Ming Li, Jihyung Kil +6

Most organizational data in this world are stored as documents, and visual retrieval plays a crucial role in unlocking the collective intelligence from all these documents. However…

cs.CV2025

CaughtCheating: Is Your MLLM a Good Cheating Detective? Exploring the Boundary of Visual Perception and Reasoning

Ming Li, Chenguang Wang, Yijun Liang +6

Recent agentic Multi-Modal Large Language Models (MLLMs) such as GPT-o3 have achieved near-ceiling scores on various existing benchmarks, motivating a demand for more challenging t…