2 papers
cs.LG2026
Seq2Synth: Benchmarking Temporal Fidelity in Synthetic Sequential Tabular Data
Kiwan Kwon, Kangmin Kim, Hojin Lee +5
Synthetic sequential tabular data are increasingly used for privacy-preserving data sharing and research, yet conventional tabular metrics often overlook temporal structure. Existi…
cs.AI2026
Your AI, On a Dial: Controlling Investment Bias in LLMs with a Single Neuron
Sahong Park, Suhwan Park, Hoyoung Lee +8
Large language models (LLMs) are increasingly used in investment decision-making, yet prior work shows that they exhibit systematic, model-specific investment preferences. We study…