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Found 4 papers, 3 papers with code
Can Large Language Model Agents Simulate Human Trust Behaviors?
In addition, we probe into the biases in agent trust and the differences in agent trust towards agents and humans.
An Empirical Study on Challenging Math Problem Solving with GPT-4
Employing Large Language Models (LLMs) to address mathematical problems is an intriguing research endeavor, considering the abundance of math problems expressed in natural language across numerous science and engineering fields.
Uncovering Adversarial Risks of Test-Time Adaptation
Recently, test-time adaptation (TTA) has been proposed as a promising solution for addressing distribution shifts.
RoCourseNet: Distributionally Robust Training of a Prediction Aware Recourse Model
To address this problem, we propose RoCourseNet, a training framework that jointly optimizes predictions and recourses that are robust to future data shifts.
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