22 citations · 31 across the 9 of their papers we have counts for
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cs.CL2024★ 1 cited
Improving Model Factuality with Fine-grained Critique-based Evaluator
Yiqing Xie, Wenxuan Zhou, Pradyot Prakash +9
Factuality evaluation aims to detect factual errors produced by language models (LMs) and hence guide the development of more factual models. Towards this goal, we train a factuali…
cs.CL2024
ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?
Siddhant Waghjale, Vishruth Veerendranath, Zora Zhiruo Wang +1
Although large language models (LLMs) have been largely successful in generating functionally correct programs, conditioning models to produce efficient solutions while ensuring co…