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cs.CL2024
Theoretical Proof that Auto-regressive Language Models Collapse when Real-world Data is a Finite Set
Lecheng Wang, Xianjie Shi, Ge Li +5
Auto-regressive language models (LMs) have been widely used to generate data in data-scarce domains to train new LMs, compensating for the scarcity of real-world data. Previous wor…
cs.CL2024
Generating Equivalent Representations of Code By A Self-Reflection Approach
Jia Li, Ge Li, Lecheng Wang +2
Equivalent Representations (ERs) of code are textual representations that preserve the same semantics as the code itself, e.g., natural language comments and pseudocode. ERs play a…