3 citations · 8 across the 14 of their papers we have counts for
14 papers
MMMMM: A Unified Taxonomy for Investigating the Mechanisms of Multilingual MultiModal Misinformation
Nadav Borenstein, Greta Warren, Desmond Elliott +1
Multimodal misinformation on social media is highly prevalent, potent, and harmful, yet difficult to detect and counter, and still poorly understood compared to its text-only count…
BiasGym: A Simple and Generalizable Framework for Analyzing and Removing Biases through Injection
Sekh Mainul Islam, Nadav Borenstein, Siddhesh Milind Pawar +3
Understanding biases and stereotypes encoded in the weights of Large Language Models (LLMs) is crucial for developing effective mitigation strategies. However, biased behavior is o…
Revisiting Noise in Natural Language Processing for Computational Social Science
Nadav Borenstein
Computational Social Science (CSS) is an emerging field driven by the unprecedented availability of human-generated content for researchers. This field, however, presents a unique…
Can Community Notes Replace Professional Fact-Checkers?
Nadav Borenstein, Greta Warren, Desmond Elliott +1
Two commonly employed strategies to combat the rise of misinformation on social media are (i) fact-checking by professional organisations and (ii) community moderation by platform…
Can Transformers Learn -gram Language Models?
Anej Svete, Nadav Borenstein, Mike Zhou +2
Much theoretical work has described the ability of transformers to represent formal languages. However, linking theoretical results to empirical performance is not straightforward…
Revealing Fine-Grained Values and Opinions in Large Language Models
Dustin Wright, Arnav Arora, Nadav Borenstein +3
Uncovering latent values and opinions embedded in large language models (LLMs) can help identify biases and mitigate potential harm. Recently, this has been approached by prompting…
What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages
Nadav Borenstein, Anej Svete, Robin Chan +5
What can large language models learn? By definition, language models (LM) are distributions over strings. Therefore, an intuitive way of addressing the above question is to formali…
Investigating Human Values in Online Communities
Nadav Borenstein, Arnav Arora, Lucie-Aimée Kaffee +1
Studying human values is instrumental for cross-cultural research, enabling a better understanding of preferences and behaviour of society at large and communities therein. To stud…
Imitation of Life: A Search Engine for Biologically Inspired Design
Hen Emuna, Nadav Borenstein, Xin Qian +4
Biologically Inspired Design (BID), or Biomimicry, is a problem-solving methodology that applies analogies from nature to solve engineering challenges. For example, Speedo engineer…
PHD: Pixel-Based Language Modeling of Historical Documents
Nadav Borenstein, Phillip Rust, Desmond Elliott +1
The digitisation of historical documents has provided historians with unprecedented research opportunities. Yet, the conventional approach to analysing historical documents involve…
Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers
Yuxia Wang, Revanth Gangi Reddy, Zain Muhammad Mujahid +10
The increased use of large language models (LLMs) across a variety of real-world applications calls for mechanisms to verify the factual accuracy of their outputs. In this work, we…
Measuring Intersectional Biases in Historical Documents
Nadav Borenstein, Karolina Stańczak, Thea Rolskov +3
Data-driven analyses of biases in historical texts can help illuminate the origin and development of biases prevailing in modern society. However, digitised historical documents po…
Multilingual Event Extraction from Historical Newspaper Adverts
Nadav Borenstein, Natalia da Silva Perez, Isabelle Augenstein
NLP methods can aid historians in analyzing textual materials in greater volumes than manually feasible. Developing such methods poses substantial challenges though. First, acquiri…
How Did This Get Funded?! Automatically Identifying Quirky Scientific Achievements
Chen Shani, Nadav Borenstein, Dafna Shahaf
Humor is an important social phenomenon, serving complex social and psychological functions. However, despite being studied for millennia humor is computationally not well understo…