3 papers indexed here
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Large language model (LLM) agents are increasingly evaluated on long-horizon tasks, including autonomously running a business. Existing benchmarks for this setting are almost exclusively English-language, Western in retail context, and single-agent, with the agent observing the business directly. We study how these res...
DiSCo is proposed, a distribution-first forced-choice evaluation framework that isolates default cultural priors and tests steerability via a four-level context gradient (C0--C3) and confirms that cultural preference bias cannot be resolved through prompt-based personalisation alone.
Working baseline levels of capability are provided with respect to current LLM-based solutions in 6G mission-critical and public safety contexts, and specific research directions to advance LLM-driven cybersecurity toward robust, adaptable, explainable, and life-safety-aware solutions are mapped out.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
