35 citations · 38 across the 10 of their papers we have counts for
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cs.CL2026
Embodied Task Planning via Graph-Informed Action Generation with Large Language Models
Xiang Li, Ning Yan, Masood Mortazavi
While Large Language Models (LLMs) have demonstrated strong zero-shot reasoning capabilities, their deployment as embodied agents still faces fundamental challenges in long-horizon…
cs.CL2024
Graph-DPEP: Decomposed Plug and Ensemble Play for Few-Shot Document Relation Extraction with Graph-of-Thoughts Reasoning
Tao Zhang, Ning Yan, Masood Mortazavi +3
Large language models (LLMs) pre-trained on massive corpora have demonstrated impressive few-shot learning capability on many NLP tasks. Recasting an NLP task into a text-to-text g…
cs.CL2024
Enhancing Long Context Performance in LLMs Through Inner Loop Query Mechanism
Yimin Tang, Yurong Xu, Ning Yan +1
Transformers have a quadratic scaling of computational complexity with input size, which limits the input context window size of large language models (LLMs) in both training and i…