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cs.AI2024
MixEval-X: Any-to-Any Evaluations from Real-World Data Mixtures
Jinjie Ni, Yifan Song, Deepanway Ghosal +10
Perceiving and generating diverse modalities are crucial for AI models to effectively learn from and engage with real-world signals, necessitating reliable evaluations for their de…
cs.SE2024★ 1 cited
CodexGraph: Bridging Large Language Models and Code Repositories via Code Graph Databases
Xiangyan Liu, Bo Lan, Zhiyuan Hu +5
Large Language Models (LLMs) excel in stand-alone code tasks like HumanEval and MBPP, but struggle with handling entire code repositories. This challenge has prompted research on e…