For An Exciting Tomorrow
arXiv:2512.10734v2 Announce Type: replace-cross Abstract: Textual data used to train large language models (LLMs) exhibits multifaceted bias manifestations encompassing harmful…
arXiv:2312.04180v3 Announce Type: replace Abstract: This study investigates how artificial intelligence (AI) influences various online labor markets (OLMs) over time.…
arXiv:2405.21047v3 Announce Type: replace Abstract: Large Language Models (LLMs) struggle with reliably generating highly structured outputs, such as program code,…
arXiv:2512.10926v2 Announce Type: replace-cross Abstract: Temporal-difference (TD) methods learn state and action values efficiently by bootstrapping from their own future…
arXiv:2512.11169v1 Announce Type: new Abstract: Combinatorial sequential decision making problems are typically modeled as mixed integer linear programs (MILPs) and…
arXiv:2512.09443v2 Announce Type: replace-cross Abstract: We investigate how large language models can be used as research tools in scientific computing…