13 papers
NS-Copilot: An LLM-Driven Agent System for Autonomous Neuroscience Analysis
Wuche Liu, Yiran Qiao, Linlin Hou +4
AI is rapidly advancing neuroscience, yet many laboratories fail to fully unleash its potential due to significant interdisciplinary barriers. While pre-trained neural models for p…
Valerant: An Automatic Navigable Game Map Generator via Action-Conditioned World Model Exploration
Yiran Qiao, Feng Wang, Jing Ma
World Action Models (WAMs) couple predictive world modeling with action generation, allowing anticipated future states to guide agent behavior. Although WAMs are rapidly advancing…
Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion
Yiran Qiao, Yiren Lu, Yunlai Zhou +5
3D asset generation plays a pivotal role in fields such as gaming and virtual reality, enabling the rapid synthesis of high-fidelity 3D objects from a single or multiple images. Bu…
AdvSplat: Adversarial Attacks on Feed-Forward Gaussian Splatting Models
Yiran Qiao, Yiren Lu, Yunlai Zhou +4
3D Gaussian Splatting (3DGS) is increasingly recognized as a powerful paradigm for real-time, high-fidelity 3D reconstruction. However, its per-scene optimization pipeline limits s…
DefenseSplat: Enhancing the Robustness of 3D Gaussian Splatting via Frequency-Aware Filtering
Yiran Qiao, Yiren Lu, Yunlai Zhou +4
3D Gaussian Splatting (3DGS) has emerged as a powerful paradigm for real-time and high-fidelity 3D reconstruction from posed images. However, recent studies reveal its vulnerabilit…
Counterfactual Visual Explanation via Causally-Guided Adversarial Steering
Yiran Qiao, Disheng Liu, Yiren Lu +3
Recent work on counterfactual visual explanations has contributed to making artificial intelligence models more explainable by providing visual perturbation to flip the prediction.…
When 'YES' Meets 'BUT': Can Large Models Comprehend Contradictory Humor Through Comparative Reasoning?
Tuo Liang, Zhe Hu, Jing Li +8
Understanding humor-particularly when it involves complex, contradictory narratives that require comparative reasoning-remains a significant challenge for large vision-language mod…
Segment then Splat: Unified 3D Open-Vocabulary Segmentation via Gaussian Splatting
Yiren Lu, Yunlai Zhou, Yiran Qiao +5
Open-vocabulary querying in 3D space is crucial for enabling more intelligent perception in applications such as robotics, autonomous systems, and augmented reality. However, most…
CAUSAL3D: A Comprehensive Benchmark for Causal Learning from Visual Data
Disheng Liu, Yiran Qiao, Wuche Liu +5
True intelligence hinges on the ability to uncover and leverage hidden causal relations. Despite significant progress in AI and computer vision (CV), there remains a lack of benchm…
SAIF: A Sparse Autoencoder Framework for Interpreting and Steering Instruction Following of Language Models
Zirui He, Haiyan Zhao, Yiran Qiao +4
The ability of large language models (LLMs) to follow instructions is crucial for their practical applications, yet the underlying mechanisms remain poorly understood. This paper p…
View-consistent Object Removal in Radiance Fields
Yiren Lu, Jing Ma, Yu Yin
Radiance Fields (RFs) have emerged as a crucial technology for 3D scene representation, enabling the synthesis of novel views with remarkable realism. However, as RFs become more w…
Certified Causal Defense with Generalizable Robustness
Yiran Qiao, Yu Yin, Chen Chen +1
While machine learning models have proven effective across various scenarios, it is widely acknowledged that many models are vulnerable to adversarial attacks. Recently, there have…
Cracking the Code of Juxtaposition: Can AI Models Understand the Humorous Contradictions
Zhe Hu, Tuo Liang, Jing Li +5
Recent advancements in large multimodal language models have demonstrated remarkable proficiency across a wide range of tasks. Yet, these models still struggle with understanding t…