activity
20152022
most citedScaling Up Models and Data with and

48 citations · 75 across the 3 of their papers we have counts for

collaborators

7 papers

cs.LG202248 cited

Scaling Up Models and Data with and

Adam Roberts, Hyung Won Chung, Anselm Levskaya +40

Recent neural network-based language models have benefited greatly from scaling up the size of training datasets and the number of parameters in the models themselves. Scaling can…

cs.CL2021

Fool Me Twice: Entailment from Wikipedia Gamification

Julian Martin Eisenschlos, Bhuwan Dhingra, Jannis Bulian +2

We release FoolMeTwice (FM2 for short), a large dataset of challenging entailment pairs collected through a fun multi-player game. Gamification encourages adversarial examples, dra…

cs.CL202124 cited

CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims

Thomas Diggelmann, Jordan Boyd-Graber, Jannis Bulian +2

We introduce CLIMATE-FEVER, a new publicly available dataset for verification of climate change-related claims. By providing a dataset for the research community, we aim to facilit…

cs.CL2019

Meta Answering for Machine Reading

Benjamin Borschinger, Jordan Boyd-Graber, Christian Buck +7

We investigate a framework for machine reading, inspired by real world information-seeking problems, where a meta question answering system interacts with a black box environment.…

cs.LG2018

Learning to Coordinate Multiple Reinforcement Learning Agents for Diverse Query Reformulation

Rodrigo Nogueira, Jannis Bulian, Massimiliano Ciaramita

We propose a method to efficiently learn diverse strategies in reinforcement learning for query reformulation in the tasks of document retrieval and question answering. In the prop…

cs.CL20183 cited

Analyzing Language Learned by an Active Question Answering Agent

Christian Buck, Jannis Bulian, Massimiliano Ciaramita +4

We analyze the language learned by an agent trained with reinforcement learning as a component of the ActiveQA system [Buck et al., 2017]. In ActiveQA, question answering is framed…