9 papers
Open-Weather Robust 3D Detection via Dual-Critic Diffusion Alignment
Shuyao Li, Chuanxing Geng, Heyang Sun +2
Robust 3D object detection under adverse weather remains a critical hurdle for autonomous driving. Despite progress with LiDAR-4D radar fusion, most methods are constrained by a cl…
Reflect then Learn: Active Prompting for Information Extraction Guided by Introspective Confusion
Dong Zhao, Yadong Wang, Xiang Chen +6
Large Language Models (LLMs) show remarkable potential for few-shot information extraction (IE), yet their performance is highly sensitive to the choice of in-context examples. Con…
Beyond Dense States: Elevating Sparse Transcoders to Active Operators for Latent Reasoning
Yadong Wang, Haodong Chen, Yu Tian +3
Latent reasoning compresses the chain-of-thought (CoT) into continuous hidden states, yet existing methods rely on dense latent transitions that remain difficult to interpret and c…
LoD: Loss-difference OOD Detection by Intentionally Label-Noisifying Unlabeled Wild Data
Chuanxing Geng, Qifei Li, Xinrui Wang +3
Using unlabeled wild data containing both in-distribution (ID) and out-of-distribution (OOD) data to improve the safety and reliability of models has recently received increasing a…
ULFine: Unbiased Lightweight Fine-tuning for Foundation-Model-Assisted Long-Tailed Semi-Supervised Learning
Enhao Zhang, Chaohua Li, Chuanxing Geng +1
Based on the success of large-scale visual foundation models like CLIP in various downstream tasks, this paper initially attempts to explore their impact on Long-Tailed Semi-Superv…
Recent Advances in Out-of-Distribution Detection with CLIP-Like Models: A Survey
Chaohua Li, Enhao Zhang, Chuanxing Geng +1
Out-of-distribution detection (OOD) is a pivotal task for real-world applications that trains models to identify samples that are distributionally different from the in-distributio…