4 papers
MNIST-PRO: MNIST is Back as a Partially Observable World for AI Agents
Vernon Toh, Navonil Majumder, Zhengyuan Liu +2
AI agents in partially observable environments need to coordinate active sensing with working memory to maintain an evolving perceptual state. However, existing benchmarks struggle…
ScrambleToolBench: Agents Search Exhaustively Even When Their Own Map Points to the Next Step
Vernon Toh, Navonil Majumder, Zhengyuan Liu +2
To operate robustly in open-world environments, autonomous agents should be able to infer the behavior of unfamiliar systems through interaction alone, even in the absence of docum…
Bridging Talk and Thought: Understanding Dialogue Dynamics Across Collaborative Problem-Solving Contexts
Zhengyuan Liu, Stella Xin Yin, Min-Yen Kan +1
We present a conceptual framework for analyzing dialogue in collaborative problem-solving contexts, with an emphasis on the emerging dynamics of human-AI and multi-agent collaborat…
Can Persona-Prompted LLMs Emulate Subgroup Values? An Empirical Analysis of Generalisability and Fairness in Cultural Alignment
Bryan Chen Zhengyu Tan, Zhengyuan Liu, Xiaoyuan Yi +4
Despite their global prevalence, many Large Language Models (LLMs) are aligned to a monolithic, often Western-centric set of values. This paper investigates the more challenging ta…