7 papers
LLMs can persuade only psychologically susceptible humans on societal issues, via trust in AI and emotional appeals, amid logical fallacies
Alexis Carrillo, Salvatore Citraro, Ali Aghazhadeh Ardebili +5
Scarce longitudinal evidence examines LLMs' persuasiveness and humanness along time-evolving psychological frameworks. We introduce Talk2AI, a longitudinal framework quantifying ps…
The role of System 1 and System 2 semantic memory structure in human and LLM biases
Katherine Abramski, Giulio Rossetti, Massimo Stella
Implicit biases in both humans and large language models (LLMs) pose significant societal risks. Dual process theories propose that biases arise primarily from associative System 1…
The Corporate Bond Factor Replication Crisis
Alexander Dickerson, Cesare Robotti, Giulio Rossetti
Corporate bond factor research faces a replication crisis. The crisis stems from two sources that inflate reported factor premia: transaction prices whose measurement error enters…
A word association network methodology for evaluating implicit biases in LLMs compared to humans
Katherine Abramski, Giulio Rossetti, Massimo Stella
As Large language models (LLMs) become increasingly integrated into our lives, their inherent social biases remain a pressing concern. Detecting and evaluating these biases can be…
SpreadPy: A Python tool for modelling spreading activation and superdiffusion in cognitive multiplex networks
Salvatore Citraro, Edith Haim, Alessandra Carini +3
We introduce SpreadPy as a Python library for simulating spreading activation in cognitive single-layer and multiplex networks. Our tool is designed to perform numerical simulation…
The "LLM World of Words" English free association norms generated by large language models
Katherine Abramski, Riccardo Improta, Giulio Rossetti +1
Free associations have been extensively used in cognitive psychology and linguistics for studying how conceptual knowledge is organized. Recently, the potential of applying a simil…