8 citations · 38 across the 28 of their papers we have counts for
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cs.CL2025
Harnessing Consistency for Robust Test-Time LLM Ensemble
Zhichen Zeng, Qi Yu, Xiao Lin +6
Different large language models (LLMs) exhibit diverse strengths and weaknesses, and LLM ensemble serves as a promising approach to integrate their complementary capabilities. Desp…
cs.CL2025★ 1 cited
SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence
Zhining Liu, Rana Ali Amjad, Ravinarayana Adkathimar +2
Providing Language Models (LMs) with relevant evidence in the context (either via retrieval or user-provided) can significantly improve their ability to provide better-grounded res…
cs.CL2024
How to Make LMs Strong Node Classifiers?
Zhe Xu, Kaveh Hassani, Si Zhang +7
Language Models (LMs) are increasingly challenging the dominance of domain-specific models, such as Graph Neural Networks (GNNs) and Graph Transformers (GTs), in graph learning tas…