3 papers
cs.CL2026
Hallucination, Monofacts, and Miscalibration: An Empirical Investigation
Miranda Muqing Miao, Michael Kearns
Hallucinated facts in large language models (LLMs) have recently been shown to obey a statistical lower bound determined by the monofact rate (related to the classical Good-Turing…
cs.GT2025
Algorithmic Aspects of Strategic Trading
Michael Kearns, Mirah Shi
Algorithmic trading in modern financial markets is widely acknowledged to exhibit strategic, game-theoretic behaviors whose complexity can be difficult to model. A recent series of…
cs.LG2024
Improving LLM Group Fairness on Tabular Data via In-Context Learning
Valeriia Cherepanova, Chia-Jung Lee, Nil-Jana Akpinar +4
Large language models (LLMs) have been shown to be effective on tabular prediction tasks in the low-data regime, leveraging their internal knowledge and ability to learn from instr…