2 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
Structure-R1: Dynamically Leveraging Structural Knowledge in LLM Reasoning through Reinforcement Learning
Junlin Wu, Xianrui Zhong, Jiashuo Sun +4
Large language models (LLMs) have demonstrated remarkable advances in reasoning capabilities. However, their performance remains constrained by limited access to explicit and struc…
A Psychology-based Unified Dynamic Framework for Curriculum Learning
Guangyu Meng, Qingkai Zeng, John P. Lalor +1
Directly learning from examples of varying difficulty levels is often challenging for both humans and machine learning models. A more effective strategy involves exposing learners…
ChatEL: Entity Linking with Chatbots
Yifan Ding, Qingkai Zeng, Tim Weninger
Entity Linking (EL) is an essential and challenging task in natural language processing that seeks to link some text representing an entity within a document or sentence with its c…
EntGPT: Entity Linking with Generative Large Language Models
Yifan Ding, Amrit Poudel, Qingkai Zeng +3
Entity Linking in natural language processing seeks to match text entities to their corresponding entries in a dictionary or knowledge base. Traditional approaches rely on contextu…