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cs.AI2026
DERELAB: Probing Defeasible Reasoning and Confirmation Bias in LLMs with a Generative Benchmark
Jayanta Sadhu, Sayem Shahad, Kenneth Marino
Defeasible reasoning is a type of reasoning where inferences are drawn from plausible current evidence, but can be retracted upon the introduction of newer evidence. Although recen…
cs.AI2026
TimeWarp: Evaluating Web Agents by Revisiting the Past
Md Farhan Ishmam, Kenneth Marino
As web agents close the gap with humans on benchmarks, one question arises: Do today's agents perform just as well on tomorrow's web? We introduce TimeWarp, a benchmark that emulat…
cs.AI2025
Language Agents Mirror Human Causal Reasoning Biases. How Can We Help Them Think Like Scientists?
Anthony GX-Chen, Dongyan Lin, Mandana Samiei +4
Language model (LM) agents are increasingly used as autonomous decision-makers which need to actively gather information to guide their decisions. A crucial cognitive skill for suc…