Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Detoxifying Text with MaRCo: Controllable Revision with Experts and Anti-Experts
Text detoxification has the potential to miti- 001 gate the harms of toxicity by rephrasing text to 002 remove offensive meaning, but subtle toxicity 003 remains challenging to tackle. We introduce…
DISCO: Distilling Phrasal Counterfactuals with Large Language Models
Recent methods demonstrate that data augmentation using counterfactual knowledge can teach models the causal structure of a task, leading to robust and generalizable models. However, such…
From Dogwhistles to Bullhorns: Unveiling Coded Rhetoric with Language Models
Dogwhistles are coded expressions that simultaneously convey one meaning to a broad audience and a second one, often hateful or provocative, to a narrow in-group; they are deployed to evade both…
HINT: Hypernetwork Instruction Tuning for Efficient Few- and Zero-Shot Generalisation
Recent NLP models have shown the remarkable ability to effectively generalise `zero-shot' to new tasks using only natural language instructions as guidance. However, many of these approaches suffer…
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions
Prompting-based large language models (LLMs) are surprisingly powerful at generating natural language reasoning steps or Chains-of-Thoughts (CoT) for multi-step question answering (QA). They…
NLPositionality: Characterizing Design Biases of Datasets and Models
Design biases in NLP systems, such as performance differences for different populations, often stem from their creator's positionality, i.e., views and lived experiences shaped by identity and…
Reproducibility in NLP: What Have We Learned from the Checklist?
Scientific progress in NLP rests on the reproducibility of researchers' claims. The *CL conferences created the NLP Reproducibility Checklist in 2020 to be completed by authors at submission to…
Are Layout-Infused Language Models Robust to Layout Distribution Shifts? A Case Study with Scientific Documents
Recent work has shown that infusing layout features into language models (LMs) improves processing of visually-rich documents such as scientific papers. Layout-infused LMs are often evaluated on…
ClarifyDelphi: Reinforced Clarification Questions with Defeasibility Rewards for Social and Moral Situations
Context is everything, even in commonsense moral reasoning. Changing contexts can flip the moral judgment of an action; Lying to a friend is wrong in general, but may be morally acceptable if it is…
CREPE: Open-Domain Question Answering with False Presuppositions
When asking about unfamiliar topics, information seeking users often pose questions with false presuppositions. Most existing question answering (QA) datasets, in contrast, assume all questions have…