7 papers
In-Context Learning as Implicit Policy Gradient
Masahiro Kaneko, Timothy Baldwin
Recent work has shown that large language models (LLMs) can iteratively improve their outputs by incorporating generated samples and their corresponding evaluation scores as in-con…
EconSimulacra: A Digital Twin Platform of Socio-Economic Systems Powered by LLM Agents
Ryuji Hashimoto, Masahiro Kaneko, Kentaro Ueda +2
Real-world social behavior emerges from tightly coupled domains: economic conditions shape mobility and social interactions, while online attention and offline activity feed back i…
From Heard to Lived Opinions: Simulating Opinion Dynamics with Grounded LLM Agents in Economic Environments
Ryuji Hashimoto, Masahiro Kaneko, Ryosuke Takata +2
Opinion dynamics (OD) studies how individual opinions evolve and generate collective patterns such as consensus and polarization. While recent work explores OD using populations of…
Beyond the Resumé: A Rubric-Aware Automatic Interview System for Information Elicitation
Harry Stuart, Masahiro Kaneko, Timothy Baldwin
Effective hiring is integral to the success of an organisation, but it is very challenging to find the most suitable candidates because expert evaluation (e.g.\ interviews conducte…
JailNewsBench: Multi-Lingual and Regional Benchmark for Fake News Generation under Jailbreak Attacks
Masahiro Kaneko, Ayana Niwa, Timothy Baldwin
Fake news undermines societal trust and decision-making across politics, economics, health, and international relations, and in extreme cases threatens human lives and societal saf…
Online Learning Defense against Iterative Jailbreak Attacks via Prompt Optimization
Masahiro Kaneko, Zeerak Talat, Timothy Baldwin
Iterative jailbreak methods that repeatedly rewrite and input prompts into large language models (LLMs) to induce harmful outputs -- using the model's previous responses to guide e…