activity
20192022
most citedBetter than Average: Paired Evaluation of NLP Systems

14 citations · 52 across the 13 of their papers we have counts for

collaborators
Showing cs.CLShow all

7 papers · 1 filter

cs.CL202114 cited

Better than Average: Paired Evaluation of NLP Systems

Maxime Peyrard, Wei Zhao, Steffen Eger +1

Evaluation in NLP is usually done by comparing the scores of competing systems independently averaged over a common set of test instances. In this work, we question the use of aver…

cs.CL2021

Classifying Dyads for Militarized Conflict Analysis

Niklas Stoehr, Lucas Torroba Hennigen, Samin Ahbab +2

Understanding the origins of militarized conflict is a complex, yet important undertaking. Existing research seeks to build this understanding by considering bi-lateral relationshi…

cs.CL2021

Laughing Heads: Can Transformers Detect What Makes a Sentence Funny?

Maxime Peyrard, Beatriz Borges, Kristina Gligorić +1

The automatic detection of humor poses a grand challenge for natural language processing. Transformer-based systems have recently achieved remarkable results on this task, but they…

cs.CL2020

KLearn: Background Knowledge Inference from Summarization Data

Maxime Peyrard, Robert West

The goal of text summarization is to compress documents to the relevant information while excluding background information already known to the receiver. So far, summarization rese…

cs.CL2020

Crosslingual Topic Modeling with WikiPDA

Tiziano Piccardi, Robert West

We present Wikipedia-based Polyglot Dirichlet Allocation (WikiPDA), a crosslingual topic model that learns to represent Wikipedia articles written in any language as distributions…

cs.CL20204 cited

On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation

Wei Zhao, Goran Glavaš, Maxime Peyrard +3

Evaluation of cross-lingual encoders is usually performed either via zero-shot cross-lingual transfer in supervised downstream tasks or via unsupervised cross-lingual textual simil…