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20242026
most citedLarge Language Models and Causal Inference in Collaboration: A Survey

14 citations · 32 across the 38 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

SceneAlign: Aligning Multimodal Reasoning to Scene Graphs in Complex Visual Scenes

Chuhan Wang, Xintong Li, Jennifer Yuntong Zhang +5

Multimodal large language models often struggle with faithful reasoning in complex visual scenes, where intricate entities and relations require precise visual grounding at each st…

cs.CV2025

Importance Sampling for Multi-Negative Multimodal Direct Preference Optimization

Xintong Li, Chuhan Wang, Junda Wu +4

Direct Preference Optimization (DPO) has recently been extended from text-only models to vision-language models. However, existing methods rely on oversimplified pairwise compariso…

cs.CV2025

PDB-Eval: An Evaluation of Large Multimodal Models for Description and Explanation of Personalized Driving Behavior

Junda Wu, Jessica Echterhoff, Kyungtae Han +3

Understanding a driver's behavior and intentions is important for potential risk assessment and early accident prevention. Safety and driver assistance systems can be tailored to i…

cs.CV2025

Weakly-supervised VLM-guided Partial Contrastive Learning for Visual Language Navigation

Ruoyu Wang, Tong Yu, Junda Wu +3

Visual Language Navigation (VLN) is a fundamental task within the field of Embodied AI, focusing on the ability of agents to navigate complex environments based on natural language…

cs.CV2024

Personalized Multimodal Large Language Models: A Survey

Junda Wu, Hanjia Lyu, Yu Xia +24

Multimodal Large Language Models (MLLMs) have become increasingly important due to their state-of-the-art performance and ability to integrate multiple data modalities, such as tex…