2 citations · 4 across the 6 of their papers we have counts for
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3 papers · 1 filter
cs.LG2024★ 2 cited
GLBench: A Comprehensive Benchmark for Graph with Large Language Models
Yuhan Li, Peisong Wang, Xiao Zhu +5
The emergence of large language models (LLMs) has revolutionized the way we interact with graphs, leading to a new paradigm called GraphLLM. Despite the rapid development of GraphL…
cs.CL2024
On the Transformations across Reward Model, Parameter Update, and In-Context Prompt
Deng Cai, Huayang Li, Tingchen Fu +11
Despite the general capabilities of pre-trained large language models (LLMs), they still need further adaptation to better serve practical applications. In this paper, we demonstra…
cs.CL2024★ 2 cited
With Greater Text Comes Greater Necessity: Inference-Time Training Helps Long Text Generation
Y. Wang, D. Ma, D. Cai
Long text generation, such as novel writing and discourse-level translation with extremely long contexts, presents significant challenges to current language models. Existing metho…