2 citations · 3 across the 18 of their papers we have counts for
9 papers · 1 filter
VisAudit: Evaluating Multimodal Agents for Visual Diagnosis and Repair
Shicheng Liu, Adam Kahirov, Qi Zhang +5
Multimodal agents are increasingly used for data visualization tasks but remain limited in autonomous review. Unlike humans, they may fail to recognize when a visualization is inco…
CoDS: Robust Collaborative Perception via Expert-driven Detection and BEV Segmentation
Jinlong Wang, Yuang Jia, Junhong Lin +2
Collaborative perception breaks through single-view limitations via multi-agent information exchange. However, multi-source noise such as pose errors and communication delays degra…
Visual Geometry Foundation-Aware Gaussians for Single-Frame Surround-View Driving Reconstruction
Junhong Lin, Jinlong Wang, Xianda Guo +6
Single-frame surround-view reconstruction faces severe geometric instability and rendering artifacts due to minimal inter-camera overlap. While existing methods rely on complex dec…
VGOcc: Learning Visual-Geometric Gaussians for Vision-Centric 3D Driving Occupancy Prediction
Junhong Lin, Xianda Guo, Kangli Wang +4
Vision-only occupancy prediction requires recovering a semantic 3D occupancy field from calibrated surround-view images, where each view provides observations with ambiguous depth…
CoSAG: Compact Semantic Anchor Gaussians via Training-Free Rate-Distortion Coding
Yuang Jia, Jinlong Wang, Junhong Lin +2
Open-vocabulary 3D scene understanding is commonly achieved by embedding 2D vision-language features such as CLIP into a 3D Gaussian Splatting scene, turning it into a text-queryab…
HalluGuard: Demystifying Data-Driven and Reasoning-Driven Hallucinations in LLMs
Xinyue Zeng, Junhong Lin, Yujun Yan +4
The reliability of Large Language Models (LLMs) in high-stakes domains such as healthcare, law, and scientific discovery is often compromised by hallucinations. These failures typi…
How Much Reasoning Do Retrieval-Augmented Models Add beyond LLMs? A Benchmarking Framework for Multi-Hop Inference over Hybrid Knowledge
Junhong Lin, Bing Zhang, Song Wang +4
Large language models (LLMs) continue to struggle with knowledge-intensive questions that require up-to-date information and multi-hop reasoning. Augmenting LLMs with hybrid extern…
Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces
Mike A. Merrill, Alexander G. Shaw, Nicholas Carlini +82
AI agents may soon become capable of autonomously completing valuable, long-horizon tasks in diverse domains. Current benchmarks either do not measure real-world tasks, or are not…
Layered Division and Global Allocation for Community Detection in Multilayer Network
Fanghao Hu, Zhi Cai, Bang Wang
Community detection in multilayer networks (CDMN) is to divide a set of entities with multiple relation types into a few disjoint subsets, which has many applications in the Web, t…