4 papers
CitySeeker: How Do VLMS Explore Embodied Urban Navigation With Implicit Human Needs?
Siqi Wang, Chao Liang, Yunfan Gao +5
Vision-Language Models (VLMs) have made significant progress in explicit instruction-based navigation; however, their ability to interpret implicit human needs (e.g., "I am thirsty…
Sighted by Default: Addressing Implicit Vision Assumptions in Real-Time VLM Assistance for BLV Users
Yi Zhao, Siqi Wang, Qiqun Geng +2
Vision-Language Model (VLM)-based assistance is reshaping independence for blind and low-vision (BLV) users, yet current tools fail in dynamic settings. While request-response arch…
OASIS: Order-Augmented Strategy for Improved Code Search
Zuchen Gao, Zizheng Zhan, Xianming Li +6
Code embeddings capture the semantic representations of code and are crucial for various code-related large language model (LLM) applications, such as code search. Previous trainin…
UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on Large Language Models
Boyang Xue, Fei Mi, Qi Zhu +6
Despite demonstrating impressive capabilities, Large Language Models (LLMs) still often struggle to accurately express the factual knowledge they possess, especially in cases where…