activity
20182023
most citedPredicting human decisions with behavioral theories and machine learning

15 citations · 17 across the 5 of their papers we have counts for

collaborators

6 papers

cs.CL2023

MeeQA: Natural Questions in Meeting Transcripts

Reut Apel, Tom Braude, Amir Kantor +1

We present MeeQA, a dataset for natural-language question answering over meeting transcripts. It includes real questions asked during meetings by its participants. The dataset cont…

cs.LG2023★ 1 cited

Human Choice Prediction in Language-based Persuasion Games: Simulation-based Off-Policy Evaluation

Eilam Shapira, Omer Madmon, Reut Apel +2

Recent advances in Large Language Models (LLMs) have spurred interest in designing LLM-based agents for tasks that involve interaction with human and artificial agents. This paper…

cs.CL2021

Designing an Automatic Agent for Repeated Language based Persuasion Games

Maya Raifer, Guy Rotman, Reut Apel +2

Persuasion games are fundamental in economics and AI research and serve as the basis for important applications. However, work on this setup assumes communication with stylized mes…

cs.AI2020

Predicting Decisions in Language Based Persuasion Games

Reut Apel, Ido Erev, Roi Reichart +1

Sender-receiver interactions, and specifically persuasion games, are widely researched in economic modeling and artificial intelligence. However, in the classic persuasion games se…

cs.AI2019★ 15 cited

Predicting human decisions with behavioral theories and machine learning

Ori Plonsky, Reut Apel, Eyal Ert +9

Predicting human decisions under risk and uncertainty remains a fundamental challenge across disciplines. Existing models often struggle even in highly stylized tasks like choice b…

cs.SI2018★ 1 cited

Characterizing Efficient Referrals in Social Networks

Reut Apel, Elad Yom-Tov, Moshe Tennenholtz

Users of social networks often focus on specific areas of that network, leading to the well-known "filter bubble" effect. Connecting people to a new area of the network in a way th…