2 citations · 3 across the 5 of their papers we have counts for
5 papers
BayLing 2: A Multilingual Large Language Model with Efficient Language Alignment
Shaolei Zhang, Kehao Zhang, Qingkai Fang +4
Large language models (LLMs), with their powerful generative capabilities and vast knowledge, empower various tasks in everyday life. However, these abilities are primarily concent…
Map-Free Trajectory Prediction with Map Distillation and Hierarchical Encoding
Xiaodong Liu, Yucheng Xing, Xin Wang
Reliable motion forecasting of surrounding agents is essential for ensuring the safe operation of autonomous vehicles. Many existing trajectory prediction methods rely heavily on h…
StreamAdapter: Efficient Test Time Adaptation from Contextual Streams
Dilxat Muhtar, Yelong Shen, Yaming Yang +11
In-context learning (ICL) allows large language models (LLMs) to adapt to new tasks directly from the given demonstrations without requiring gradient updates. While recent advances…
DIM: Dynamic Integration of Multimodal Entity Linking with Large Language Model
Shezheng Song, Shasha Li, Jie Yu +6
Our study delves into Multimodal Entity Linking, aligning the mention in multimodal information with entities in knowledge base. Existing methods are still facing challenges like a…
Knowledge-Rich Self-Supervision for Biomedical Entity Linking
Sheng Zhang, Hao Cheng, Shikhar Vashishth +6
Entity linking faces significant challenges such as prolific variations and prevalent ambiguities, especially in high-value domains with myriad entities. Standard classification ap…